Name: Natural Language Processing with Real-World Projects
Price: 338.99 GBP
Availability: InStock

Redhill

<h3><b>Network management technologies course description</b></h3>
        <p>A comprehensive tour of the available network
management technologies available for todays
networks. The course starts with basic tools such as
syslog along with Python network automation. SNMP is
then covered with the *flow technologies and streaming
telemetry. Configuration management with ansible,
Python, NETCONF and RESTCONF is then studied.
The final part of the course looks at SDN. Hands on
sessions are used throughout to reinforce the theory
rather than teach specific manufacturer equipment.
Note that sections are available as individual courses.
</p>
        
				<h5><b>What will you learn</b></h5>
				<ul>
				 
     <li> Evaluate network management technologies.</li>
           					 <li> Evaluate network management technologies.</li>
<li> Recognise the weaknesses of SNMP versus
NETCONF and streaming telemetry.</li>
<li>Explain the role of NETCONF and RESTCONF.</li>
<li>Compare &amp; contrast *flow and streaming telemetry.</li>
<li> Explain the role of SDN in network management.</li>
<li>Automate network configuration with ansible and
Python.
</li>
                  </ul>
        <h5>
        <b>Network management technologies course details</b> </h5>
				<div>
					<div>
						<ul>
							<li><b> Who will benefit:</b> </li>
							
							<p>Those wishing to manage networks.<br />(Previous Python experience is NOT needed)
</p>
              
							<li><b>Prerequisites:</b></li>
							
              <p>Intro to data comms</p>
              
							<li><b>Duration</b></li>
							
              <p>5 days</p>
              
							
              
              
						</ul>
					</div>
				</div>
			
				 <h3><b>Network management technologies course content</b></h3>
				<h4>Basic network management</h4>

				 <ul>
		<li>Network management</li><p>
What is network management? Benefits, issues.
FCAPS model. Fault management, Configuration
management, accounting, performance, security.
What to manage, what not to manage. Managing
network devices, managing servers.</p>
				</ul>
<h4>Monitoring networks</h4> <ul>					 
<li>Traditional network tools</li><p>
Ping..., SSH, syslog, TFTP for configurations.
nmap. Wireshark. CLI. Web based management.
Splunk. Nessus, snort, Kali. 
<br /><span>Hands on</span> syslog, network inventories.

</p> </ul> <ul><li>Network automation using the CLI</li><p>
Programming and automating networks, netOps.
Python, Git. Python network modules, SSH,
paramiko, netmiko. EVE-NG.
<br /><span>Hands on</span>Python
network modules.

</p></ul> <ul><li>Structured versus unstructured data</li><p>
				
Problems with automation and unstructured data.
XML, JSON, YAML. The role of YANG. <br /><span>Hands on</span>
Parsing data.
				
</p></ul> <ul><li>SNMP</li><p>
SNMP architecture, SNMP MIBs, SMI, the SNMP
protocol, polling security. Configuring SNMP.
SNMPv1, v2, v3, SNMP security. Which version
should you use? MIBs and MIB structure. mib-2,
extra parts of mib-2, Private enterprise MIBs.
Summary: What SNMP is good/bad at.<br /><span>Hands on</span>
Configuring agents and a NMS. MIB browsing.
				
</p></ul> <ul><li>Server management</li><p>
Microsoft, Linux, application polling. WMI vs
SNMP. Hands on: Application polling.</p></ul>
				
<h4>Performance management</h4>
 <ul><li>*flow</li><p>
Polling, push vs pull, netflow, sflow, IPFIX, *flow.
Flows. Where to monitor traffic. Comparing *flow
with SNMP. Architecture: Generators and
collectors. When flows are exported. NetFlow
reporting products. SolarWinds. <br /><span>Hands on</span> Netflow
configuration. Collectors.

</p></ul> <ul><li>Streaming telemetry</li><p>
Model driven telemetry, periodic/on change.
Structured data. Telemetry protocol stack. gRPC
and gNMI. Protobuf. gNMI operations. Telemetry
architecture. Telegraf, databases, Grafana. <br /><span>Hands on</span> Telemetry example.
</p></ul>		
<h4>Configuration management</h4>
 <ul><li>Configuration management tools</li><p>
Chef, puppet, ansible, saltstack. Ansible
architecture, controlling machines, nodes,
agentless, SSH, modules. Inventories, playbooks,
modules, network modules, jinja2 templates.
<br /><span>Hands on</span> Network configuration with ansible.
	
</p></ul> <ul><li>NETCONF</li><p>
What is NETCONF? Protocol stack, Data stores,
traffic flows, validating configurations, rollback.
YANG data models and how YANG is used by
NETCONF. XML. Explorers and other tools.
<br /><span>Hands on</span> anx, Python and NETCONF.

</p></ul> <ul><li>RESTCONF</li><p>
The REST API, HTTP, What is RESTCONF?
Tools including Postman. Comparison with
NETCONF. <br /><span>Hands on</span> Configuration with
RESTCONF.
	
</p></ul> <ul><li>Python network automation: configuration</li><p>
SSH issues. Using structured data. Jinja2.
ncclient, requests, NAPALM, Nornir. Automated
testing. <br /><span>Hands on</span> Python network device
configuration with nornir.</p></ul>
	
<h4>Software Defined Networks and orchestration</h4>
 <ul><li>Classic SDN</li><p>
What is SDN? benefits. SDN architecture. SDN
applications, SDN switches, SDN controllers,
Network Operating Systems. Control plane, data
plane. Northbound interfaces. SDN components.
Southbound interfaces. OpenFlow. ONF,
OpenFlow ports, Flow tables.
	
</p></ul> <ul><li>Network virtualization</li><p>
Virtual networks, virtual switches, NfV. Service
chaining. NfV and SDN.
	
</p></ul> <ul><li>SDN implementations</li><p>
Classic SDN, Hybrid SDN, SDN via APIs, SDN
via overlays. Data centre SDN, VXLAN, Service
Provider SDN, SD WAN, Enterprise SDN, WiFi.
	
</p></ul> <ul><li>SDN and open source</li><p>
OpenDaylight, OpenVSwitch, Open Networking
Forum, Open Network Operating System.<br /><span>Hands on</span>OpenStack.
	
</p></ul> <ul><li>SD-WAN</li><p>
What is SD-WAN? Architecture: Edge, gateway,
orchestrator, controller. Overlay and underlay.
Use of MPLS, 4G/5G. Benefits and features.
Secure Access Service Edge (SASE).
</p>
     
      
				
				
				   </ul>

Systems & Network Training

Network & Security

Network Engineer

Network management technologies

General Admission

<strong>This is an introductory course on machine learning. The course covers a wide range of topics, from handling a dataset to model delivery. Some prior training in Python programming and basic calculus knowledge will help you get the best out of this course.</strong>
        <p>Machine learning is a branch of AI and computer science that focuses on the use of data to imitate the way humans learn and improve its accuracy.

The course is divided into two parts. The first part starts with a brief history of how machine learning started and introduces you to the basics of statistical learning. You will also understand linear regression and classification, which is the logistic regression model. Understand what cross-validation, sampling, and Bootstrap are. Explore how to go beyond linearity; we will specifically look at a couple of interesting examples to improve the linear regression model to see if we can create models that are non-linear.

The second part of the course is completely hands-on labs, which start with an example of predicting fuel efficiency in linear regression. We will then look at a lab on logistic regression with a little bit of mathematics behind it. Understand another lab session on random forests and do a review of decision trees as well. Next, we will look at a lab session on Eigenfaces by using Principle Component Analysis (PCA) and wrap up a course with a lab on ROC-AUC (Receiver Operating Characteristic Curve-Area Under Curve).

By the end of the course, you would have given yourself the skills and confidence to start programming machine learning algorithms.

All resources and code files are placed here: https://github.com/PacktPublishing/Fundamentals-of-Machine-Learning</p>
        <h2>What You Will Learn</h2><p>Learn the basics of statistical learning <br>Understand linear regression, classification, and supervised learning <br>Understand sampling and Bootstrap in machine learning <br>Explore model selection and regularization <br>Understand random forests and decision trees <br>Explore labs on Multilayer Perceptron (MLP)?and RNN</p>
        <h2>Audience</h2><p>This course can be taken by beginners in Python programming, machine learning, and data science. Scientists, data scientists, and data analysts can also opt for this course. The course assumes no prior knowledge. However, some prior training in Python programming and some basic calculus knowledge is helpful for the course.</p>
        <h2>Approach</h2><p>Each topic has its designated video. The video walks through the technical component of a model to prepare students with a mathematical background. <br><br>Each lab session covers one single topic, which will ensure that the topics covered in the course are well understood.</p>
        <h2>Key Features</h2><p>Build customized deep learning models to start your own data science career  * Build customized models to use for different data science projects  * Learn about the fundamental principles of machine learning</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Fundamentals-of-Machine-Learning</p>
        <h2>About the Author</h2><h3>Yiqiao Yin</h3><p>Yiqiao Yin was a PhD student in statistics at Columbia University. He has a BA in mathematics and an MS in finance from the University of Rochester. He also has a wide range of research interests in representation learning: feature learning, deep learning, computer vision, and NLP.

Yiqiao Yin is a senior data scientist at an S&P 500 company LabCorp, developing AI-driven solutions for drug diagnostics and development. He has held professional positions as an enterprise-level data scientist at EURO STOXX 50 company Bayer, a quantitative researcher at AQR working on alternative quantitative strategies to portfolio management and factor-based trading, and equity trader at T3 Trading on Wall Street.</p>
        <h2>Course Outline</h2><h4>1. Lectures</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Welcome</p><p style='margin: 0'>This video explains the contents of the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Introduction</p><p style='margin: 0'>This video explains a brief history of where machine learning started.</p></td></tr><tr><td style='padding: 15px;'><p>3. Basics in Statistical Learning</p><p style='margin: 0'>This video explains some basic notations in statistical learning, such as Xij.</p></td></tr><tr><td style='padding: 15px;'><p>4. Linear Regression</p><p style='margin: 0'>This video explains the foundation of the linear regression model, which is the very first approach to supervised learning.</p></td></tr><tr><td style='padding: 15px;'><p>5. Classification</p><p style='margin: 0'>This video explains one of the most basic forms of classification, which is the logistic regression model.</p></td></tr><tr><td style='padding: 15px;'><p>6. Sampling and Bootstrap</p><p style='margin: 0'>This video explains the two most famous and common procedures-cross-validation and Bootstrap.</p></td></tr><tr><td style='padding: 15px;'><p>7. Model Selection</p><p style='margin: 0'>This video explains model selection and regularization.</p></td></tr><tr><td style='padding: 15px;'><p>8. Going Beyond Linearity</p><p style='margin: 0'>This video explains going beyond linearity; specifically, we will look at a couple of interesting examples to improve the linear regression model to see if we can create models that are non-linear.</p></td></tr><tr><td style='padding: 15px;'><p>9. Tree-Based Methods - Part 1</p><p style='margin: 0'>This part of the video explains decision tree.</p></td></tr><tr><td style='padding: 15px;'><p>10. Tree-Based Methods - Part 2</p><p style='margin: 0'>The second part of the tree-based methods explains random forests.</p></td></tr><tr><td style='padding: 15px;'><p>11. Support Vector Machine (SVM)</p><p style='margin: 0'>This video explains the support vector machine called SVM and its introduction.</p></td></tr><tr><td style='padding: 15px;'><p>12. Deep Learning</p><p style='margin: 0'>This video introduces you to deep learning, artificial neural networks, recurrent neural networks, and more.</p></td></tr><tr><td style='padding: 15px;'><p>13. Unsupervised Learning</p><p style='margin: 0'>This video explains unsupervised learning, Principal Components Analysis (PCA), and clustering.</p></td></tr><tr><td style='padding: 15px;'><p>14. Classification Metrics</p><p style='margin: 0'>This video explains classification metrics and will cover terminologies such as accuracy, specificity, sensitivity, and so on.</p></td></tr></tbody></table><br><h4>2. Labs</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Linear Regression</p><p style='margin: 0'>This video explains linear regression using an example of predicting fuel efficiency.</p></td></tr><tr><td style='padding: 15px;'><p>2. Logistic Regression</p><p style='margin: 0'>This video explains logistic regression with a little bit of mathematics behind it.</p></td></tr><tr><td style='padding: 15px;'><p>3. Ridge</p><p style='margin: 0'>This video explains a lab session on Ridge regression, which holds a unique position in statistical machine learning.</p></td></tr><tr><td style='padding: 15px;'><p>4. Decision Tree</p><p style='margin: 0'>This video explains a lab session on a decision tree, getting dependencies, and how to create mock data.</p></td></tr><tr><td style='padding: 15px;'><p>5. Random Forests</p><p style='margin: 0'>This video explains a lab session on random forests and a review of decision trees.</p></td></tr><tr><td style='padding: 15px;'><p>6. Support Vector Machine (SVM)</p><p style='margin: 0'>This video explains a lab session on Support Vector Machines or SVM.</p></td></tr><tr><td style='padding: 15px;'><p>7. Multilayer Perceptron (MLP)</p><p style='margin: 0'>This video explains a lab session on neural networks and Multilayer Perceptron (MLP) models.</p></td></tr><tr><td style='padding: 15px;'><p>8. CNN</p><p style='margin: 0'>This video continues the lab from neural networks and will have a look at convolutional neural networks.</p></td></tr><tr><td style='padding: 15px;'><p>9. PCA</p><p style='margin: 0'>This video explains a lab session on Eigenfaces using PCA.</p></td></tr><tr><td style='padding: 15px;'><p>10. ROCAUC</p><p style='margin: 0'>In this final lab, you will learn about ROC-AUC (Receiver Operating Characteristic Curve-Area Under Curve).</p></td></tr></tbody></table>

Packt

Data Science

Python

This is an introductory course on machine learning. The course covers a wide range of topics, from handling a dataset to model delivery. Some prior training in Python programming and basic calculus knowledge will help you get the best out of this course.

Fundamentals of Machine Learning

iStudy UK

Programming Fundamentals

Computer Programming

Python Programming: Beginner To Expert

Keras

TensorFlow

Deep Learning

You will learn Python-based deep learning and machine learning techniques through this course. With numerous real-world case studies, we will go over all the mathematics needed to master deep learning algorithms. We will study Backpropagation, Feed Forward Network, Artificial Neural Networks, CNN, RNN, Transfer Learning, and more.

Deep Learning with Real-World Projects

<div>
						<div>
				<div>
									<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
								<div>
				<p><span>Register on the Python For Beginners Part 1 today and build the experience, skills and knowledge you need to enhance your professional development and work towards your dream job. Study this course through online learning and take the first steps towards a long-term career.</span></p><p><span>The course consists of a number of easy to digest, in-depth modules, designed to provide you with a detailed, expert level of knowledge. Learn through a mixture of instructional video lessons and online study materials.</span></p><p><span>Receive online tutor support as you study the course, to ensure you are supported every step of the way. Get a digital certificate as a proof of your course completion.</span></p><p><span>The Python For Beginners Part 1 is incredibly great value and allows you to study at your own pace. Access the course modules from any internet-enabled device, including computers, tablet, and smartphones.</span></p><p><span>The course is designed to increase your employability and equip you with everything you need to be a success. Enrol on the now and start learning instantly!</span></p>					</div>
						</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
				<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
			<h2>What You Get With The Python For Beginners Part 1</h2>		</div>
				</div>
				<div>
				<div>
								<div>
				<ul><li><span>Receive an e-certificate upon successful completion of the course</span></li><li><span>Get taught by experienced, professional instructors</span></li><li><span>Study at a time and pace that suits your learning style</span></li><li><span>Get instant feedback on assessments </span></li><li><span>24/7 help and advice via email or live chat</span></li><li><span>Get full tutor support on weekdays (Monday to Friday)</span></li></ul>					</div>
						</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
				<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
					<div>
							
					<div></div>
											<div></div>
														
							
					<div></div>
											<div></div>
														
							
					<div></div>
											<div></div>
														
							
					<div></div>
											<div></div>
														
					</div>
			</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
				<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
			<h2>Certificate of Achievement </h2>		</div>
				</div>
				<div>
				<div>
								<div>
				<p><b>Endorsed Certificate of Achievement from the Quality Licence Scheme</b></p><p><span>Upon successful completion of the final assessment, you will be eligible to apply for the Quality Licence Scheme Endorsed Certificate of achievement. This certificate will be delivered to your doorstep through the post for £99. An extra £10 postage charge will be required for students leaving overseas. </span></p><p><b>CPD Accredited Certificate</b></p><p><span>After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.</span></p>					</div>
						</div>
				</div>
						</div>
					</div>
		</div>
				<div>
			<div>
							<div>
						<div>
				<div>
								<div>
																										</div>
						</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
				<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
			<h2>Who Is This Course For</h2>		</div>
				</div>
				<div>
				<div>
								<div>
				<p><span>The course is ideal for those who already work in this sector or are an aspiring professional. This course is designed to enhance your expertise and boost your CV. Learn key skills and gain a professional qualification to prove your newly-acquired knowledge.</span></p>					</div>
						</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
				<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
			<h2>Requirements</h2>		</div>
				</div>
				<div>
				<div>
								<div>
				<p><span>The online training is open to all students and has no formal entry requirements. To study the Python For Beginners Part 1, all your need is a passion for learning, a good understanding of English, numeracy, and IT skills. You must also be over the age of 16.</span></p>					</div>
						</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
									</div>
			</div>
					</div><div>
				<h3>Course Content</h3>

<div id="course_curriculum">
<table width="100%">				<tbody><tr>
					<td colspan="4">Module 01: Introduction to the Python for Beginners Course</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Introduction to the Python for Beginners Course</td>
					<td> </td>
					<td><span><i></i> 00:08:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 02: Getting Started with Python</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Getting Started with Python</td>
					<td> </td>
					<td><span><i></i> 00:53:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 03: Data Types and Operators</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Types and Operators</td>
					<td> </td>
					<td><span><i></i> 01:54:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 04: Data Structures</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Data Structures</td>
					<td> </td>
					<td><span><i></i> 01:59:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Module 05: Control Flow</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Control Flow</td>
					<td> </td>
					<td><span><i></i> 01:14:00</span></td>
				</tr>
								<tr>
					<td colspan="4">Order your Certificates &amp; Transcripts</td>
				</tr>
								<tr>
					<td><i></i></td>
					<td>Order your Certificates &amp; Transcripts</td>
					<td> </td>
					<td><span><i></i> 00:00:00</span></td>
				</tr>
				</tbody></table></div>

			</div>
			<h2>Frequently Asked Questions</h2>
                        <div>
                            <div>
                                <span>
                                    Are there any prerequisites for taking the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        There are no specific prerequisites for this course, nor
                                        are there any formal entry requirements. All you need is
                                        an internet connection, a good understanding of English
                                        and a passion for learning for this course.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Can I access the course at any time, or is there a set
                                    schedule?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        You have the flexibility to access the course at any time
                                        that suits your schedule. Our courses are self-paced,
                                        allowing you to study at your own pace and convenience.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    How long will I have access to the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        For this course, you will have access to the course
                                        materials for 1 year only. This means you can review the
                                        content as often as you like within the year, even after
                                        you've completed the course. However, if you buy Lifetime
                                        Access for the course, you will be able to access the
                                        course for a lifetime.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Is there a certificate of completion provided after
                                    completing the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        Yes, upon successfully completing the course, you will
                                        receive a certificate of completion. This certificate can
                                        be a valuable addition to your professional portfolio and
                                        can be shared on your various social networks.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    Can I switch courses or get a refund if I'm not satisfied
                                    with the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        We want you to have a positive learning experience. If
                                        you're not satisfied with the course, you can request a
                                        course transfer or refund within 14 days of the initial
                                        purchase.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    How do I track my progress in the course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        Our platform provides tracking tools and progress
                                        indicators for each course. You can monitor your progress,
                                        completed lessons, and assessments through your learner
                                        dashboard for the course.
                                    </p>
                                </div>
                            </div>
                        </div>
                        
                        <div>
                            <div>
                                <span>
                                    What if I have technical issues or difficulties with the
                                    course?
                                </span>
                                <div>
                                    <span></span>
                                </div>
                            </div>
                            <div>
                                <div>
                                    <p>
                                        If you encounter technical issues or content-related
                                        difficulties with the course, our support team is
                                        available to assist you. You can reach out to them for
                                        prompt resolution.
                                    </p>
                                </div>
                            </div>
                        </div>

Janets

Python For Beginners Part 1

<p>Get ready for an exceptional online learning experience with the <strong>Data Analysis, Data Science, Data Protection, Business Analysis, Python &amp; Excel </strong>bundle! This carefully curated collection of<strong> 20 premium courses</strong> is designed to cater to a variety of interests and disciplines. Dive into a sea of knowledge and skills, tailoring your learning journey to suit your unique aspirations.</p><p>The Data Analysis &amp; Data Protectionl is a dynamic package, blending the expertise of industry professionals with the flexibility of digital learning. It offers the perfect balance of foundational understanding and advanced insights. Whether you're looking to break into a new field or deepen your existing knowledge, theData Analysis &amp; Data Protection package has something for everyone.</p><p>As part of the Data Analysis, Data Science, Data Protection, Business Analysis, Python &amp; Excel package, you will receive complimentary PDF certificates for all courses in this bundle at no extra cost. Equip yourself with the Data Analysis &amp; Data Protection bundle to confidently navigate your career path or personal development journey. Enrol today and start your career growth!</p><p><strong>This Bundle Comprises the Following </strong><strong>Data Analysis, Data Science, Data Protection, Business Analysis, Python &amp; Excel </strong><strong>CPD-accredited courses:</strong></p><ul><li><strong>Course 01: </strong>Data Analytics</li><li><strong>Course 02: </strong>Diploma in Data Analytics with Tableau</li><li><strong>Course 03: </strong>Google Data Studio: Data Analytics</li><li><strong>Course 04: </strong>Business Intelligence Analyst</li><li><strong>Course 05: </strong>Diploma in Business Analysis</li><li><strong>Course 06: </strong>Data Science &amp; Machine Learning with Python</li><li><strong>Course 07: </strong>Spatial Data Visualization and Machine Learning in Python</li><li><strong>Course 08:</strong> Python Programming: Beginner To Expert</li><li><strong>Course 09: </strong>SQL For Data Analytics &amp; Database Development</li><li><strong>Course 10: </strong>Easy to Advanced Data Structures</li><li><strong>Course 11: </strong>R Programming for Data Science</li><li><strong>Course 12: </strong>Data Center Training Essentials: General Introduction</li><li><strong>Course 13: </strong>Data Analysis In Excel</li><li><strong>Course 14: </strong>Data Protection</li><li><strong>Course 15: </strong>Microsoft Excel Complete Course</li><li><strong>Course 16: </strong>Career Development Plan Fundamentals</li><li><strong>Course 17:</strong> CV Writing and Job Searching</li><li><strong>Course 18: </strong>Learn to Level Up Your Leadership</li><li><strong>Course 19: </strong>Networking Skills for Personal Success</li><li><strong>Course 20:</strong> Ace Your Presentations: Public Speaking Masterclass</li></ul><p><strong>What will make you stand out?</strong></p><p>Upon completion of this online Data Analysis, Data Science, Data Protection, Business Analysis, Python &amp; Excel bundle, you will gain the following:</p><ul><li>CPD QS Accredited Proficiency with this Data Analysis &amp; Data Protection bundle</li><li>After successfully completing the Data Analysis &amp; Data Protection bundle, you will receive a FREE PDF Certificate from REED as evidence of your newly acquired abilities.</li><li>Lifetime access to the whole collection of learning materials of this Data Analysis &amp; Data Protection bundle</li><li>The online test with immediate results</li><li>You can study and complete the Data Analysis &amp; Data Protection bundle at your own pace.</li><li>Study for the Data Analysis &amp; Data Protection bundle using any internet-connected device, such as a computer, tablet, or mobile device.</li></ul><p>Each course in this Data Analysis, Data Science, Data Protection, Business Analysis, Python &amp; Excel bundle holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This Data Analysis &amp; Data Protection bundle promises not just education but an evolving learning experience. Engage with this extraordinary collection, and prepare to enrich your personal and professional development.</p><p>Embrace the future of learning with Data Analysis, Data Science, Data Protection, Business Analysis, Python &amp; Excel, a rich anthology of 30 diverse courses. Our experts handpick each course in the Data Analysis &amp; Data Protection bundle to ensure a wide spectrum of learning opportunities. This Data Analysis &amp; Data Protection bundle will take you on a unique and enriching educational journey.</p><p>The Data Analysis, Data Science, Data Protection, Business Analysis, Python &amp; Excel bundle encapsulates our mission to provide quality, accessible education for all. Whether you are just starting your career, looking to switch industries, or hoping to enhance your professional skill set, the Data Analysis &amp; Data Protection bundle offers you the flexibility and convenience to learn at your own pace. Make the Data Analysis &amp; Data Protection package your trusted companion in your lifelong learning journey.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        200 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>The <strong>Data Analysis, Data Science, Data Protection, Business Analysis, Python &amp; Excel </strong>bundle is perfect for:</p><ul><li><strong>Start Your Data Journey: </strong>Ideal for those new to data analysis or looking to enhance their skills.</li><li><strong>Data-Driven Business: </strong>Perfect for business professionals who want to leverage data for better decisions.</li><li><strong>Aspiring Data Scientist: </strong>Excellent for those eager to learn advanced data science techniques.</li><li><strong>Data Compliance Expertise:</strong> Great for privacy and compliance officers needing data protection knowledge.</li><li><strong>Lifelong Data Learner:</strong> Beneficial for individuals who want to combine Python and Excel for data analysis.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You are warmly invited to register for this Data Analysis, Data Science, Data Protection, Business Analysis, Python &amp; Excel bundle. Please be aware that no formal entry requirements or qualifications are necessary. This curriculum has been crafted to be open to everyone, regardless of previous experience or educational attainment.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Upon <strong>Data Analysis, Data Science, Data Protection, Business Analysis, Python &amp; Excel </strong>course completion, you can expect to:</p><ul><li>Data Analyst</li><li>Data Scientist</li><li>Business Analyst</li><li>Data Protection Officer</li><li>Data Engineer</li><li>Machine Learning Engineer</li><li>Data Consultant</li><li>Operations Analyst</li><li>Marketing Analyst</li><li>Project Manager</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>20 CPD Quality Standard Pdf Certificates</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Compliance Central

Data Analysis, Data Science, Data Protection, Business Analysis, Python & Excel

<div>
						<div>
							<div>
							<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
			<h2>Overview
</h2>		</div>
				</div>
				<div>
				<div>
								<div>
					<p><span>This comprehensive course on <b>Machine Learning with Python</b> will deepen your understanding on this topic.</span></p><p><span>After successful completion of this course you can acquire the required skills in this sector. This <b>Machine Learning with Python</b> comes with accredited certification, which will enhance your CV and make you worthy in the job market.</span></p><p><span>So enrol in this course today to fast track your career ladder.</span></p>					</div>
						</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
				<section>
						<div>
							<div>
					<div>
			<div>
							<div>
								</div>
					</div>
		</div>
								</div>
					</div>
		</section>
				<section>
						<div>
							<div>
					<div>
			<div>
							<div>
						<div>
				<div>
			<h2>How will I get my certificate?</h2>		</div>
				</div>
				<div>
				<div>
								<div>
					<p>You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate.</p>					</div>
						</div>
				</div>
				<div>
				<div>
			<h2>Who is This course for?</h2>		</div>
				</div>
				<div>
				<div>
								<div>
					<p><span>There is no experience or previous qualifications required for enrolment on this <b>Machine Learning with Python</b>. It is available to all students, of all academic backgrounds.</span></p>					</div>
						</div>
				</div>
				<div>
				<div>
			<h2>Requirements</h2>		</div>
				</div>
				<div>
				<div>
								<div>
					<p><span>Our <b>Machine Learning with Python</b> is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G.</span></p><p><span>There is no time limit for completing this course, it can be studied in your own time at your own pace.</span></p>					</div>
						</div>
				</div>
				<div>
				<div>
			<h2>Career Path</h2>		</div>
				</div>
				<div>
				<div>
								<div>
					<p><span>Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business &amp; Management, Admin, Accountancy &amp; Finance, Secretarial &amp; PA, Teaching &amp; Mentoring etc.</span></p>					</div>
						</div>
				</div>
						</div>
					</div>
		</div>
								</div>
					</div>
		</section>
						</div>
						</div>
					</div> <h3>Course Curriculum</h3><div><p>4 sections • 21 lectures • 01:34:00 total length</p></div><div><div><div><div><div><div><div><p>•Introduction to types of ML algorithm: 00:02:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•SVM - Python Implementation: 00:06:00</p></div><div><div><p>•Introduction to types of ML algorithm: 00:02:00</p></div><div><div><p>•Importing a dataset in python: 00:02:00</p></div><div><div><p>•Resolving Missing Values: 00:06:00</p></div><div><div><p>•Managing Category Variables: 00:04:00</p></div><div><div><p>•Training and Testing Datasets: 00:07:00</p></div><div><div><p>•Normalizing Variables: 00:02:00</p></div><div><div><p>•Normalizing Variables - Python Code: 00:03:00</p></div><div><div><p>•Summary: 00:01:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•Simple Linear Regression - How it works?: 00:04:00</p></div><div><div><p>•Simple Linear Regreesion - Python Implementation: 00:07:00</p></div><div><div><p>•Multiple Linear Regression - How it works?: 00:01:00</p></div><div><div><p>•Multiple Linear Regression - Python Implementation: 00:09:00</p></div><div><div><p>•Decision Trees - How it works?: 00:05:00</p></div><div><div><p>•Random Forest - How it works?: 00:03:00</p></div><div><div><p>•Decision Trees and Random Forest - Python Implementation: 00:04:00</p></div></div></div></div></div><div><div><div><div><div><div><p>•kNN - How it works?: 00:02:00</p></div><div><div><p>•kNN - Python Implementation: 00:10:00</p></div><div><div><p>•Decision Tree Classifier and Random Forest Classifier in Python: 00:10:00</p></div><div><div><p>•SVM - How it works?: 00:04:00</p></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>

Apex Learning

Learning & Development

Managed Learning Programme (MLP)

Machine Learning (ML)

Learning To Learn

Azure Machine Learning

Machine Learning with Python

<p>Python is a powerful and versatile programming language that's widely used in the world of data science and machine learning. In this Python for Beginners course, you will learn the fundamentals of Python programming, including data types, data structures, control flow, and more. By the end of the course, you will have a solid foundation in Python that will enable you to tackle more complex projects in the future.</p><p><strong>Learning outcomes:</strong></p><ul><li>Understand the basic concepts of programming using Python</li><li>Know how to install and set up a Python development environment</li><li>Learn about data types and operators in Python</li><li>Understand the various data structures available in Python</li><li>Learn how to use control flow constructs in Python to make decisions and repeat actions</li><li>Gain the ability to write simple Python programs from scratch</li></ul><p>Python for Beginners Part 1 is a comprehensive course designed for anyone who wants to learn the basics of Python programming. The course is structured into five modules, each focusing on a specific area of Python programming. You will start by learning about the basics of programming and setting up a Python development environment. From there, you will move on to topics such as data types, data structures, and control flow.</p><p>Throughout the course, you will have access to interactive exercises and quizzes that will help you reinforce your learning. By the end of the course, you will have a solid understanding of Python programming and the ability to write your own simple programs.</p><p>If you're new to programming or just starting out with Python, this course is the perfect place to begin. With clear, concise explanations and plenty of examples, you'll be up and running with Python in no time.</p><p><strong>Certification</strong></p><p>Upon completion of the course, learners can obtain a certificate as proof of their achievement. You can receive a £4.99 PDF Certificate sent via email, a £9.99 Printed Hardcopy Certificate for delivery in the UK, or a £19.99 Printed Hardcopy Certificate for international delivery. Each option depends on individual preferences and locations.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        10 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div><h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <ul><li>Individuals who are new to programming</li><li>Professionals who want to learn Python for data science or machine learning</li><li>Students who want to gain a fundamental understanding of Python programming</li><li>Anyone who wants to add a valuable skill to their resume</li></ul>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Python Developer: £30,000 - £75,000 per year</li><li>Data Analyst: £24,000 - £46,000 per year</li><li>Machine Learning Engineer: £35,000 - £85,000 per year</li><li>Software Engineer: £24,000 - £70,000 per year</li><li>Full Stack Developer: £28,000 - £70,000 per year</li><li>Artificial Intelligence Developer: £35,000 - £85,000 per year</li></ul>
                        </div>

NextGen Learning

Learn Python Programming from Scratch

Skill Up

Online Course Creation

Career Development

IT Skills

Flat Discount: 52% OFF! QLS Endorsed| 40 Courses Diploma| 400 CPD Points| Free PDF+Transcript Certificate| Lifetime Access


Level 7 Data Science & Machine Learning (Python, R, SQL & Microsoft Azure) - - QLS Endorsed


Want to become an expert NLP engineer and a data scientist? Then this is the right course for you. In this course, we will be covering complex theory, algorithms, and coding libraries in a very simple way that can be easily grasped by any beginner as well.

Natural Language Processing with Real-World Projects

London

<article>
<div>
<h5>Java EVENINGS Course</h5>
</div>
<div></div>
<p>  						 
	</p><div>
	<ul>
		<p>
		<b>Python EVENINGS Course. </b>Basic Python syntax and principles of Object Orientated Programming. 
		<br />Most attendees are in-work IT Professional.
		<br />Private individuals are also very welcome. 
		<br />Evening courses also running.
		<br /><b>Our Style: </b>Hands-on, Practical  
		<br /><b>Location:  </b>Online, Instructor-led  
		<br /><b>Download:  </b>anaconda.com
		<br /><b>Duration:  </b>6 weeks, 1 evening per week, 6pm - 8pm
		<br /><b>Times: </b>arrange a time for your time zone
	    </p>
	</ul>	

<p></p>
</div></article>

<div>
	  <div>
		 <h5>Python Basics EVENINGS Course </h5>
	  </div>
	  <div></div>
	  <p> 
 
				This Python course London Evening covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom.
				This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language.
				These concepts are daily used by programmers and is your first step to working as a programmer.
				By the end, you'll be comfortable in programming Python code.
				You will have done small projects.
				This will serve for you as examples and samples that you can use to build larger projects.
				You can publish your code online to keep as a portfolio.

<br />
This Python Programming course is hands-on and practical, to give you in-depth, practical experience of the topics covered.

	  </p>
	<div>
	<h5>Week 1: Basics</h5>
	</div>
	<div></div>
	<div> 
					<p>  <strong>Python Data Types and Variables:</strong>  
					<br />  Primitive types; Characters &amp; Strings; Boolean; Working with variables and its scope; Conversion and casting types in Python.	 
					<br /> <strong>Operators and Expressions: </strong>   
					<br />  Introduction of operators; Arithmetic operators; Relational operators; Assignment operator; Logical operators; Increment and decrement operators.
					</p> 
			 
				<p><strong> Decision Making:</strong>
				<br />If statement; If - else statement; If- elif - else statement; Nested if - else.
				</p><p><strong>Using Loops:</strong>
				<br />The while, while-else.
				<br />For loop;
				<br />Jump statements: break, continue;
				<br />Nesting loops.				
				</p>
			</div>
	<div>
	<h5>Week 2: Data Structures</h5>
	</div> <div></div>
	<div> 
				<p> Lists.
					<br />Tuples.
					<br />Sets.
					<br />Dictionary. Nested Dictionary.
					<br />Json Files.
				</p>
			</div>
	<div>
	<h5>Week 3: Python built-in functions</h5>
	</div> <div></div>
	<div> 
				<p>  
				<br />Using Built-in modules and functions:
				<br />Strings Functions.
				<br />Pattern matching with Regex.
				<br />Maths Functions.
				<br />Random Functions.
				<br />Python Date functions.
				</p>
			</div>
	<div>
	<h5>Week 4: OOP: Using Modules, functions, classes</h5>
	</div> <div></div>
	<div>
				<p>  Creating and using custom Functions.
					<br />Creating functions;
					<br />Using parameters and return values;
					<br />
					<br />Introduction to Classes and Objects:
					<br />Creating a Class; 
					<br />Creating an Object; Using an Object; 
					<br />Adding Instance variables; Controlling accessibility; Naming conventions for class members. 
					<br /> Class Constructors; Parameterized Constructors.
					<br />Inheritance. Overload.
				</p>
			</div>

	<div>
	<h5>Week 5: Pandas DataBase Basics</h5>
	</div> <div></div>
	<div>	 
		<p> <b>Connection details:</b>
				Connect to a database using access codes. 
				<br /><b>Select Queries:</b>
				Retrieving records and iterating results sets, using variables and parameters in queries. 
				<br />Working with DDL comands:
				Create a database, drop a database.
				Create a table, alter tables, drop a table. 
				<br />Working with DML Commands:
				Insert, delete, update records.
		</p>
	</div>
	
	 
	<div>
	<h5>Week 6: Pandas Dataframe Basics</h5>
	</div> <div></div>
	<div>	 
		<p> Getting data into a dataframe:
			<br />Dict to Dataframe, Dataframe to Dict.
			<br />Excel To Dict, Dict to Excel , working with Excel data, multiple Excel sheets.

			<br />Dataframe basics:
			<br />Slicing Dataframes,
			<br />Getting information about the dataframe,
			<br />Filter, sort and query a Dataframes,
			<br />Duplicate values,
			<br />Working with null-values,
			<br />Sampling,
			<br />Group by,
			<br />Join.

		</p>
	</div>
	  
</div>
 

<div>   

	   <div id="cincluded">
		  <div>
			 <h5>What is included</h5>
		  </div>

		  <article>
		  <div>
			 <ul>
				<li>PCWorkshops Course Certificate on completion  </li>
									   
				<li>Python Course Notes</li>
				<li>Python Code Examples</li>
				<li>Practical Python Course exercises and Code Samples</li>
				<li>After the course: 1-Hour personalised online revision session</li>
			 </ul>
		  </div>
		  </article>
	   </div>
				    
<div>
	                  <div>
	                     <h5 id="cincluded2">Book the Python  Course</h5>
	                  </div>
 
<div id="eventbrite-widget-container-60636103217"></div>




							 
</div>
				   <div id="caboutus">
	                  <div>
	                     <h5>About us</h5>
	                  </div> 
	                  	<article>
					    <div>
					    	<div>
					    		<div>
					    			
					    			<h5>Our experienced trainers are award winners. </h5> 
					    			<ul>
										<li>
											More about us
										</li>
										<li>
											FAQ's
										</li>
										<li>
											Client Comments  
										</li>
									 </ul>
					    		</div>
					    		<div>
					    			
					    				
					    			
					    		</div>
					    	</div>
	                     
					    </div>
					    </article>						
	               </div>
				   
				   
	        </div>

Python EVENINGS Course
Basic Python syntax and principles of object-oriented programming. 
Most attendees are in-work IT Professional. 
Private individuals are also very welcome. 
Evening courses also running. 

Details:
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 4 weeks, 1 evening per week, 6pm - 8pm 
Times: arrange a time for your time zone 
How to attend:  
Connection Link For the course: https://meet.goto.com/910697125
Once you have made the payment, use the above link on the date booked, to connect with the trainer. 
Python Basics EVENINGS Course
 This Python course London Evening covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom. This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language. These concepts are daily used by programmers and is your first step to working as a programmer. By the end, you'll be comfortable in programming Python code. You will have done small projects. This will serve for you as examples and samples that you can use to build larger projects. You can publish your code online to keep as a portfolio. 

This Python Programming course is hands-on and practical, to give you in-depth, practical experience of the topics covered. 
Week 1: Basics
 Python Data Types and Variables: 
Primitive Data types; Working with variables and its scope; Conversion and casting types in Python. 
 Operators and Expressions:  
 Introduction of operators; Arithmetic operators; Relational operators; Assignment operator; Logical operators; Increment and decrement operators. 
 Decision Making: 
If statement; If - else statement; If- elif - else statement; Nested if - else. 
Using Loops: 
The while, while-else. 
For loop; 
Jump statements: break, continue; 
Nesting loops. 
Week 2: Data Structures & Database
Lists.  
Tuples. 
Sets. 
Dictionary. Nested Dictionary. 
Json Files. 
Reading csv and text files
Connecting with a database and run SQL Queries. 
Week 3: Python built-in functions &  Pandas Dataframe Basics
 
Using built-in modules and functions: 
Strings Functions. 
Maths Functions. 
Random Functions. 
Data Frames; 
Getting data into a dataframe: 
Dict to Dataframe, Dataframe to Dict.  
Dataframe basics: 
Slicing Dataframes, 
Getting information about the dataframe, 
Filter and query a Dataframes, 
Working with null-values.
Week 4: OOP: Using Modules, functions, classes
 Creating and using custom Functions. 
Creating functions; 
Using parameters and return values; 
 
Introduction to Classes and Objects: 
Creating a Class; 
Creating an Object; Using an Object; 
Adding instance variables; controlling accessibility; and naming conventions for class members. 
 Class Constructors; Parameterized Constructors. 
Inheritance. Overload. 

What is included
PCWorkshops Course Certificate on completion
Python Course Notes
Python Code Examples
Practical Python Course exercises and Code Samples
After the course: 1-Hour personalised online revision session
  

PCWorkshops

Professional Skills Course (PSC)

Instructor

Basic Python syntax and principles of Object Orientated Programming. 
Most attendees are in-work IT Professional. 
Private individuals are also very welcome. 
Evening courses also running. 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 6 weeks, 1 evening per week, 6pm - 8pm 
Times: arrange a time for your time zone 

Python EVENINGS Course, Online Instructor-led

General admission

<div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This Python BootCamp is Instructor-led, Practical. In the12-week Python course, learn start to in-depth, leading to a good Python career.</strong></p></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></section></div></div></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></section></div></div></div><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">PYTHON BOOTCAMP:</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This 12-week Python Boot Camp is a practical, instructor-lead program, covering Python from start to in-depth. You will be fully fluent and confident as a Python programmer.</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">If you have more questions goto&nbsp;<a href="http://pcworkshopslondon.co.uk/contact.html" target="_blank" rel="nofollow noopener noreferrer" data-airgap-id="66" style="color: var(--eds-control,#3659e3); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: var(--eds-control,#3659e3);">https://pcworkshopslondon.co.uk/contact.html&nbsp;</a>,</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Or&nbsp;<a href="https://pcworkshopslondon.co.uk/" target="_blank" rel="nofollow noopener noreferrer" data-airgap-id="67" style="color: var(--eds-control,#3659e3); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: var(--eds-control,#3659e3);">contact us on training@pcworkshopslondon.co.uk</a></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><a href="https://pcworkshopslondon.co.uk/contact.htm" target="_blank" rel="nofollow noopener noreferrer" data-airgap-id="68" style="color: var(--eds-control,#3659e3); user-select: auto; font-size: var(--font-size); box-sizing: border-box; cursor: pointer; text-decoration: inherit;" fr-original-style=" color: var(--eds-control,#3659e3);">C﻿ustomise dates, course outline, arrange installments</a></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">This course will give you enough&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">practical experience and practical projects</strong>&nbsp;to code, to give you full confidence to enter into the coding profession. &nbsp;&nbsp;</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Duration:&nbsp;</strong>3 months:</p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">1 Python class per week,</li><li fr-original-style="" style="box-sizing: border-box;">Plus pratical work,</li><li fr-original-style="" style="box-sizing: border-box;">Plus personal trainer-mentor for 1-1 training,</li><li fr-original-style="" style="box-sizing: border-box;">Plus e-learning materials.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Final project :&nbsp;</strong>Practical to upload to&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">GitHub&nbsp;</strong>and show-case</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Date and times, choose:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Fridays in London or Online&nbsp;</strong>, 10am - 5pm,</li><li fr-original-style="" style="box-sizing: border-box;">or&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Saturdays in London or Online&nbsp;</strong>, 12noon-6pm,</li><li fr-original-style="" style="box-sizing: border-box;">o﻿r negotiate your date</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Study level:</strong> Start from beginners level to in-depth, ready to work professionally.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Virtual attendance: &nbsp;</strong>online instructor-led&nbsp;</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Download</strong>: Anaconda.com</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Pre-requisites:&nbsp;</strong>General computer literacy.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Oracle Qualification:&nbsp;</strong>PCWorkshops Python Programmer Certificate</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Payments:</strong>&nbsp; You may apply to pay in installments for this Python Training course</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">COURSE OUTLINE</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">W﻿eek 1 - 4: Essentials</strong></p><ol fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Python Coding Basics</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Object Oriented programming:&nbsp;</strong>Python Object Orientated programming (OOP)</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">UX Principles:&nbsp;</strong>UX Principles and applying it on Front-ends with TKinter</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Specialised topics:&nbsp;</strong>Dates, Localization, Strings, Maths Operation , Random Number,&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Lambdas</strong></li></ol><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">W﻿eek 5 - 10 : All about data</strong></p><ol fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Data Structures:</strong>&nbsp;Lists, Tuples, Sets,&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Exceptions</strong>, I/O Fundamentals , Reading and Writing file</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Database:&nbsp;</strong>Database principles and SQL.&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Database Project:&nbsp;</strong>Python database connections and creating a database driven project</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analytics:&nbsp;</strong>Numpy. Pandas for data analytics and data queries.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Analytics:&nbsp;</strong>Pandas data cleaning and restructuring, interacticting with Excel, Csv, Json,etc.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data visualisation:&nbsp;</strong>MatPlotLib</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Prediction:&nbsp;</strong>Machine Learning Basics</li></ol><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">W﻿eek 11 and 12: The final touch</strong></p><ol fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Concurrency and Multi-threading:</strong>&nbsp;Threads vs. Processes, Threading Module, Threading Event, Stop a Thread, Daemon Threads, Thread-safe Queue, Thread Pools, Locks</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Unit Testing</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">O﻿ptional&nbsp;</strong>: Replace Week 11 or 12 with Scraping using Python, ot Tkinter Front-ends</li></ol><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">I﻿NCLUDED:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">PCWorkshops Python Course Certificate on completion.</li><li fr-original-style="" style="box-sizing: border-box;">Python Course notes.</li><li fr-original-style="" style="box-sizing: border-box;">Practical Course exercises, Code Examples, Online Materials.</li><li fr-original-style="" style="box-sizing: border-box;">After the course, continuous assistance with practical and preparation for exams</li><li fr-original-style="" style="box-sizing: border-box;">Max group size on this is 4.</li><li fr-original-style="" style="box-sizing: border-box;">Portfolio: Post your Python project online.</li><li fr-original-style="" style="box-sizing: border-box;">Exam preparation and interview questions</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">MORE ABOUT THE ONLINE CLASSROOM</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Attend from your internet connection</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Instructor-led, get instant answers to your questions</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Fully interactive</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Work clearly explained with demonstrations and examples</li><li fr-original-style="" style="box-sizing: border-box;">&nbsp;Practical exercises to be tried out by delegate</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">WHAT YOU WILL GAIN:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Skills &amp; knowledge: Python coding knowledge and understanding with good practical application &nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Certification:&nbsp;Internal PCWorkshops Python certificate</li><li fr-original-style="" style="box-sizing: border-box;">Portfolio: You will have an online portfolio of Python projects&nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Experience:&nbsp;Our comprehensive practical makes you job ready</li></ul></div><div data-testid="image-content" style="color: rgb(57, 54, 79); box-sizing: border-box;" fr-original-style=" color: rgb(57, 54, 79);"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F444528299%2F44980801875%2F1%2Foriginal.20230212-111230?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=bc03bf9766e6c9ca0436ac60d0be83d6" alt="" data-airgap-id="88" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div><div data-testid="image-content" style="color: rgb(57, 54, 79); box-sizing: border-box;" fr-original-style=" color: rgb(57, 54, 79);"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F588336959%2F44980801875%2F1%2Foriginal.20230901-170557?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=e4036ff76e1af36cfba9452461b16c48" alt="" data-airgap-id="87" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div><div data-testid="image-content" style="color: rgb(57, 54, 79); box-sizing: border-box;" fr-original-style=" color: rgb(57, 54, 79);"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F588337149%2F44980801875%2F1%2Foriginal.20230901-170614?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=cdf1fcea5ad47abc354df67b458d5237" alt="" data-airgap-id="89" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div><div data-testid="image-content" style="color: rgb(57, 54, 79); box-sizing: border-box;" fr-original-style=" color: rgb(57, 54, 79);"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F588337349%2F44980801875%2F1%2Foriginal.20230901-170630?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=839d02fa3087d55ac858bcbb697972f5" alt="" data-airgap-id="86" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div></div><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><div style="color: rgb(30, 10, 60); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(30, 10, 60);"><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h2 fr-original-style="" style="box-sizing: border-box;">Refund Policy</h2></div><div style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">No Refunds</div>

This Python Data Analytics BootCamp is Instructor-led, Practical. In the12-week Python course, learn start to in-depth, leading to a good Python career.



PYTHON BOOTCAMP:
This 12-week Python Data Analytics Data Boot Camp is designed to give you a complete skill set required by data analysts .
You will be fully fluent and confident as a Python  data analyst, with full understanding of Python Programming.
From Data, databases, datasets, importing, cleaning, transforming, analysing to visualisation and creating awesome dashboards
The course is a practical, instructor-lead program.

If you have more questions goto https://pcworkshopslondon.co.uk/contact.html,
Or contact us on training@pcworkshopslondon.co.uk
C﻿ustomise dates, course outline, arrange installments
This course will give you enough practical experience and practical projects to code, to give you full confidence to enter into the coding profession. 
Duration: 3 months, 12 weeks:
1 Python class per week,
Plus practical work,
Plus personal trainer-mentor for 1-1 training,
Plus e-learning materials.
Final project : Practical to upload to GitHub and show-case
Date and times, choose:
Fridays in London or Online , 10am - 5pm,
or Saturdays in London or Online , 12noon-6pm,
o﻿r negotiate your date
Study level: Start from beginners level to in-depth, ready to work professionally.
Virtual attendance: online instructor-led 
Download: Anaconda.com
Pre-requisites: General computer literacy.
Oracle Qualification: PCWorkshops Python Programmer Certificate
Payments: You may apply to pay in installments for this Python Training course
COURSE OUTLINE
W﻿eek 1 - 4: Essentials
Python Coding Basics
Object Oriented programming: Python Object Orientated programming (OOP)
UX Principles: UX Principles and applying it on Front-ends with TKinter
Specialised topics: Dates, Localization, Strings, Maths Operation , Random Number, Lambdas
W﻿eek 5 - 10 : All about data
Python Data Structures: Lists, Tuples, Sets, Exceptions, I/O Fundamentals , Reading and Writing file
Database: Database principles and SQL. Database Project: Python database connections and creating a database driven project
Data Analytics: Numpy. Pandas for data analytics and data queries.
Data Analytics: Pandas data cleaning and restructuring, interacticting with Excel, Csv, Json,etc.
Data visualisation: MatPlotLib
Prediction: Machine Learning Basics
W﻿eek 11 and 12: The final touch
Python Concurrency and Multi-threading: Threads vs. Processes, Threading Module, Threading Event, Stop a Thread, Daemon Threads, Thread-safe Queue, Thread Pools, Locks
Python Unit Testing
O﻿ptional : Replace Week 11 or 12 with Scraping using Python, ot Tkinter Front-ends
I﻿NCLUDED:
PCWorkshops Python Course Certificate on completion.
Python Course notes.
Practical Course exercises, Code Examples, Online Materials.
After the course, continuous assistance with practical and preparation for exams
Max group size on this is 4.
Portfolio: Post your Python project online.
Exam preparation and interview questions
MORE ABOUT THE ONLINE CLASSROOM
Attend from your internet connection
Instructor-led, get instant answers to your questions
Fully interactive
Work clearly explained with demonstrations and examples
Practical exercises to be tried out by delegate
WHAT YOU WILL GAIN:
Skills & knowledge: Python coding knowledge and understanding with good practical application
Certification: Internal PCWorkshops Python certificate
Portfolio: You will have an online portfolio of Python projects
Experience: Our comprehensive practical makes you job ready






Refund Policy
No Refunds

PYTHON BOOTCAMP:



This 12-week Python Data Analytics Data Boot Camp is designed to give you a complete skill set required by data analysts .



You will be fully fluent and confident as a Python  data analyst, with full understanding of Python Programming.



From Data, databases, datasets, importing, cleaning, transforming, analysing to visualisation and creating awesome dashboards



The course is a practical, instructor-lead program.



Python Data Analytics BootCamp, 12-weeks, Online Instructor-led

Python Bootcamp Saturdays, Online

<article>
					<div>
						<h5>Python Beginners Course, 1-Day.</h5>
					</div>
					<div></div>
					<p>
						<span> </span>
						<br />This course covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom.
						<br />	This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language.
							<br />These concepts are daily used by programmers and is your first step to working as a programmer.
							<br />By the end, you'll be comfortable in programming Python code.
							<br />You will have done small projects.
							<br />This will serve for you as examples and samples that you can use to build larger projects.
						 
						<br /><b>Location: </b>Instructor-led, Online.
						<br /><b>Our Style: </b>Hands-on, Practical Course.
						<br /><b>Group Size: </b>Max 4 people per group.  
						<br /><b>Qualification: </b>PCWorkshops Beginners Certification
						<br /><b>Hours: </b>1 Day, 10am-5pm
						<br /><b>Download: </b>anaconda.com
						
				  	</p>
	    		</article> 
				
				<article>
					<div>
						<h5>Python Beginners Course, Course Outline.</h5>
					</div>
					<div></div>
					<p>
						<span> </span>
						<br />
						<b>Session 1: Basics</b>
 
						<br />Python Data Types and Variables:
						Working with variables and its scope; Conversion and casting types in Python.
						<br />Operators and Expressions.
						 

						<br />Decision Making: If statement; If - else statement; If- elif - else statement; Nested if - else. 
						
						<br />Using Loops: The while, while-else. For loop; Jump statements: break, continue; Nesting loops.
<br />
						<br /><b>Session 2: Data Structures</b>
						 
						<br />Lists.
						<br />Tuples.
						<br />Sets.
						<br />Dictionary. Nested Dictionary.
						<br />Json Files.
<br />
						<br /><b>Session 3: Python Built-in functions</b> 
						<br />Strings Functions. 
						<br />Maths Functions.
						<br />Random Functions.
						<br />Python Date functions.
<br />
						<br /><b>Session 4: OOP: Using Modules, functions, classes</b>
						 
						<br />Creating and using custom Functions.
						
						<br />Using parameters and return values.

						<br />Introduction to Classes and Objects:
						<br />Creating a Class. Creating and using Objects. 
						<br />Class Constructors.
						<br />Inheritance. Overload.
<br />
						<br /><b>Session 5: Access SQL Database Via Python</b>
						 
						<br /><b>Connection details:</b> Connect to a database using access codes.
						<br /><b>Select Queries:</b> Retrieving records and iterating results sets, using variables and parameters in queries.
						<br /><b>Working with DDL comands: </b>Create a database, drop a database. Create a table, alter tables, drop a table.
						<br /><b>Working with DML Commands: </b>Insert, delete, update records.

						<br /><br /><br /><b>Session 6: Pandas Dataframe Basics</b>
						 
						<br />Getting data into a dataframe:
						<br />Dict to Dataframe, Dataframe to Dict.
						<br />Excel To Dict, Dict to Excel , working with Excel data, multiple Excel sheets.
						<br />Dataframe basics:
						<br />Slicing Dataframes, Querying, filter and sort a dataframe,
						
						<br />Working with duplicates and null-values, Sampling, Group by, Join.
						
						
						
				  	</p>
	    		</article> 

			    <div>  
				     
	     
	               <div id="cincluded">
	                  <div>
	                     <h5>Python Beginners Course Materials</h5>
	                  </div>

	                  <article>
	                  <div>
	                     <ul>
	                        <li>Python Beginners Certificate on completion  </li>
							                  
						    <li>Python Beginners Notes</li>
							<li>Python Code Examples</li>
	                        <li>Practical Python Beginners exercises</li>
	                        
	                     </ul>
	                  </div>
						   
	                  </article>
	               </div>
			
				    <article>
					<div>
						<h5>More about Python</h5>
					</div>
					<div></div>
					<p>
							Python is the Easiest Programming Language to Learn 
				 				Anybody can learn how to use it and  entry-level coders get access to the industry in a 
									fast-tacked manner and can from there migrate to other languages.
								 <br />
								 Learning to code  is now more important than ever, since a growing number of application and <br />
								  digital products require programmers. <br />

								 Additionally, as an interpreted coding language, Python allows you to run each line of code <br />
								 after writing it, rather 
								 than other compiled languages, such as C++. <br />
								 This is particularly useful for beginners, as they can test their work and 
								  gain instant feedback, <br />
								  to make amendments where required and continuously improve. A Python Course will
								explain to you how to do this<br />
								  <br />
								 Python is a Versatile Coding Language <br />
								 Use it for : <br /> 
								 Data mining ,  Data analytics , Data visualisation ,  AI and machine learning,  Building apps ,
								 Web development and web application development ,  Developing games,  Quantitative and qualitative analysis,
								 Data Engineering,  A Python Course is the start of all of the above.
								 <br /><br />
								 Learning Python will Improve Your Job Prospects <br />
								 As the fastest-growing computer programming language in the world, 
								 Python is also one of the most in-demand jobs. According to 2022 LinkedIn data,   
								Python is the second most in-demand programming language, after Java.  
								All of this makes a Python Course essential. 
				  	</p>
	    		</article> 
					  
				    
					
					
					
				   <div id="booking">
	                  <div>
	                     <h5>Book the Python Beginners Course</h5>
	                  </div>
							 
 							<div id="eventbrite-widget-container-48024956939"></div>

							

							
							 
	               </div>
				   <div id="cincluded">
	                  <div>
	                     <h5>About us</h5>
	                  </div> 
	                  	<article>
					    <div>
					    	<div>
					    		<div>
					    			
					    			<h5>Our experienced trainers are award winners. </h5> 
					    			<ul>
										<li>
											More about us
										</li>
										<li>
											FAQ's
										</li>
										<li>
											Client Comments  
										</li>
									 </ul>
					    		</div>
					    		<div>
					    			
					    				
					    			
					    		</div>
					    	</div>
	                     
					    </div>
					    </article>						
	               </div>
				   
				   
	            </div>

Python Beginners Course, 1-Day.
   
This course covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom. 
	This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language. 
These concepts are daily used by programmers and is your first step to working as a programmer. 
By the end, you'll be comfortable in programming Python code. 
You will have done small projects. 
This will serve for you as examples and samples that you can use to build larger projects. 

Location: Instructor-led, Online. 
Our Style: Hands-on, Practical Course. 
Group Size: Max 4 people per group. 
Qualification: PCWorkshops Beginners Certification 
Hours: 1 Day, 10am-5pm 
Download: anaconda.com 
Python Beginners Course, Course Outline.
  Session 1: Basics 
Python Data Types and Variables: Working with variables and its scope; Conversion and casting types in Python. 
Operators and Expressions. 
Decision Making: If statement; If - else statement; If- elif - else statement; Nested if - else. 
Using Loops: The while, while-else. For loop; Jump statements: break, continue; Nesting loops.

 
Session 2: Data Structures 
Lists. 
Tuples. 
Sets. 
Dictionary. Nested Dictionary. 
Json Files.

 
Session 3: Python Built-in functions 
Strings Functions. 
Maths Functions. 
Random Functions. 
Python Date functions.

 
Session 4: OOP: Using Modules, functions, classes 
Creating and using custom Functions. 
Using parameters and return values. 
Introduction to Classes and Objects: 
Creating a Class. Creating and using Objects. 
Class Constructors. 
Inheritance. Overload.

 
Session 5: Access SQL Database Via Python 
Connection details: Connect to a database using access codes. 
Select Queries: Retrieving records and iterating results sets, using variables and parameters in queries. 
Working with DDL comands: Create a database, drop a database. Create a table, alter tables, drop a table. 
Working with DML Commands: Insert, delete, update records. 


Session 6: Pandas Dataframe Basics 
Getting data into a dataframe: 
Dict to Dataframe, Dataframe to Dict. 
Excel To Dict, Dict to Excel , working with Excel data, multiple Excel sheets. 
Dataframe basics: 
Slicing Dataframes, Querying, filter and sort a dataframe, 
Working with duplicates and null-values, Sampling, Group by, Join. 
Python Beginners Course Materials
Python Beginners Certificate on completion
Python Beginners Notes
Python Code Examples
Practical Python Beginners exercises
More about Python
 Python is the Easiest Programming Language to Learn Anybody can learn how to use it and entry-level coders get access to the industry in a fast-tacked manner and can from there migrate to other languages. 
 Learning to code is now more important than ever, since a growing number of application and 
 digital products require programmers. 
 Additionally, as an interpreted coding language, Python allows you to run each line of code 
 after writing it, rather than other compiled languages, such as C++. 
 This is particularly useful for beginners, as they can test their work and gain instant feedback, 
 to make amendments where required and continuously improve. A Python Course will explain to you how to do this
 
 Python is a Versatile Coding Language 
 Use it for : 
 Data mining , Data analytics , Data visualisation , AI and machine learning, Building apps , Web development and web application development , Developing games, Quantitative and qualitative analysis, Data Engineering, A Python Course is the start of all of the above. 

 Learning Python will Improve Your Job Prospects 
 As the fastest-growing computer programming language in the world, Python is also one of the most in-demand jobs. According to 2022 LinkedIn data, Python is the second most in-demand programming language, after Java. All of this makes a Python Course essential. 
 

Programming Languages

Computer Skills

his course covers the essential Python Basics, in our interactive, instructor led Live Virtual Classroom. 
	This Python Basics course is a very good introduction to essential fundamental programming concepts using Python as programming language. 
These concepts are daily used by programmers and is your first step to working as a programmer. 
By the end, you'll be comfortable in programming Python code. 
You will have done small projects. 
This will serve for you as examples and samples that you can use to build larger projects. 

Python Beginners Course, 1-Day

<article>
<div>
<h5>Python Data Analytics Course</h5>
</div>
<div></div>
<p>  						 
	</p><div>
	<ul>
		
<div>
    <div id="widget-reviews"><div><h3>Python Beginners Course</h3><div><span></span><span></span><span></span><span></span><span></span><div>(4.6)</div></div><span></span><br /><div>Based on 5 reviews</div><div><div><div id="previous"><i></i></div><div id="currentReview"><div> Excellent course, led by a knowledg</div><div> Excellent course, led by a knowledgeable and engaging instructor. I attended ...</div><div> Helen S</div></div><div id="next"><i></i></div></div></div></div></div>
    <div id="widget-link">
        Powered by findcourses.co.uk
    </div>
</div>

		<p>
		<b>Python Data Course. </b>Data Analytics with Python using Numpy, Pandas, Dataframes. 
		<br />Most attendees are in-work Data Professional.
		<br />Private individuals are very welcome. 
		<br /><b>Our Style: </b>Hands-on, Practical  
		<br /><b>Location:  </b>Online, Instructor-led  
		<br /><b>Download:  </b>anaconda.com
		<br /><b>Duration:  </b>2 consecutive days, 10am - 5pm
		<br /><b>Times: </b>arrange a time for your time zone
	    </p>
	</ul>	

<p></p>
</div></article>

<div>
	  <div>
			<h5>Python Data Analytics Course </h5>
	  </div>
	  <div></div>
	  <p>  
	  <br /> 
	  </p>
	<div>
	<h5>Session 1: Database: </h5>
	</div>
	<div></div>
	<div> 
					<p>  <strong>SQLite3:</strong>  
					<br /> Linking with SQL Database.
					<br /> Create, Amend and Drop Tables.
					<br /> Insert, Update and delete records.
					<br /> Select queries.
					<br /> Traverse and display query results.
					<br /> Using parameters in queries.
					<br /> Get metadata about tables and columns. 
					</p> 
			</div>
	<div>
	<h5>Session 2: Data Structures</h5>
	</div> <div></div>
	<div> 
				<p> <strong>Data Structures:</strong>  
					<br />Tuples.
					<br />Sets.
					<br />Dictionary. Nested Dictionary.
					<br />Json Files.
				</p>
			</div>
	<div>
	<h5>Session 3: Python Numpy</h5>
	</div> <div></div>
	<div> 
				<p>  <strong>Numpy:</strong>  
				<br />The Python NumPy Module:
				<br />Working with arrays, create data using arrays.
				<br />Array manipulation.
				<br />String functions on arrays. 
				<br />Math, arithmetic and statistical functions.
				
				</p>
			</div>
	<div>
	<h5>Session 4: Python Pandas Dataframes and data importing</h5>
	</div> <div></div>
	<div>
		<p>  <strong>Python Dataframes</strong>  
		<br /> Data Series. Date/ Time Functionality. Time series.
		<br /> Creating Dataframes, Indexing. 
		<br />Dict to Dataframe, Dataframe to Dict.
		<br />Csv to Dataframe, Dataframe to csv.
		<br />Excel to Dataframe, Dataframe to Excel.
		</p>
	</div>

	<div>
	<h5>Session 5: Data Cleaning and preparation</h5>
	</div> <div></div>
	<div>	 
		<p> <strong>Data Cleaning and preparation</strong>  
		<br />Finding, replacing and filtering missing data.
		<br />Remove Duplicates.
		<br />Replacing values.
		<br />Renaming Axis Indexes.
		</p>
	</div>
	
	<div>
	<h5>Session 6: Pandas Data Wrangling</h5>
	</div> <div></div>
	<div>	 
		<p> <strong>Data Wrangling:</strong>   
		
		<br />Indexing, Re-indexing, 
		<br />Reorder, 
		<br />Sorting, Stastitics, 
			<br />Transforming data using  
		<br />Dataframe Joins, Merging, Concatenation, Overlap, Append, zip. 
		 
		</p>
	</div>
	
	<div>
	<h5>Week 6: Pandas Data Analysis</h5>
	</div> <div></div>
	<div>	 
		<p> <strong>Data Analysis:</strong>   
		<br /> Sorting. 
		<br /> Analysing and finding data using filter, slicing and dataframe queries. 
		<br /> Finding data by Iteration.
		<br /> Find statistics: Functions, Aggregate functions. 
		<br /> Unique values.
		<br />String objects, Regex. 
		</p>
	</div>
</div>
 

<div>   

	   <div id="cincluded">
		  <div>
			 <h5>Included with the Python Course</h5>
		  </div>

		  <article>
		  <div>
			 <ul>
				<li>PCWorkshops Course Certificate on completion  </li>
									   
				<li>Python Course Notes</li>
				<li>Python Code Examples</li>
				<li>Practical Python Course exercises and Code Samples</li>
				<li>After the course: 1-Hour personalised online revision session</li>
			 </ul>
		  </div>
		  </article>
	   </div>
				    
<div>
	                  <div>
	                     <h5 id="cincluded2">Book the Python Course</h5>
	                  </div>
 
	 
		<div id="eventbrite-widget-container-48025096356"></div>
		
		  		
					
					 
</div>
				   <div id="caboutus">
	                  <div>
	                     <h5>About us</h5>
	                  </div> 
	                  	<article>
					    <div>
					    	<div>
					    		<div>
					    			
					    			<h5>Our experienced trainers are award winners. </h5> 
					    			<ul>
										<li>
											More about us
										</li>
										<li>
											FAQ's
										</li>
										<li>
											Client Comments  
										</li>
									 </ul>
					    		</div>
					    		<div>
					    			
					    				
					    			
					    		</div>
					    	</div>
	                     
					    </div>
					    </article>						
	               </div>
				   
				   
	        </div>

Python Data Analytics Course

Python Data Analytics with Python using 
Numpy, 
Pandas, Dataframes. 

Most attendees are in-work Data Professional.  Private individuals are very welcome. 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 1 consecutive day, 11am-5pm
Dates Times: You may let us know which dates your would prefer, or attend as scheduled

Python Data Analytics Course Description
  
Session 1: Database:
 SQLite3: 
 Linking with SQL Database. 
 Create, Amend and Drop Tables. 
 Insert, Update and delete records. 
 Select queries. 
 Traverse and display query results. 
 Using parameters in queries. 
 Get metadata about tables and columns. 
Session 2: Data Structures
 Data Structures: 
Tuples. 
Sets. 
Dictionary. Nested Dictionary. 
Json Files. 
Session 3: Python Numpy
 Numpy: 
The Python NumPy Module: 
Working with arrays, create data using arrays. 
Array manipulation. 
String functions on arrays. 
Math, arithmetic and statistical functions. 
Session 4: Python Pandas Dataframes and data importing
 Python Dataframes 
 Data Series. Date/ Time Functionality. Time series. 
 Creating Dataframes, Indexing. 
Dict to Dataframe, Dataframe to Dict. 
Csv to Dataframe, Dataframe to csv. 
Excel to Dataframe, Dataframe to Excel. 
Session 5: Data Cleaning and preparation
 Data Cleaning and preparation 
Finding, replacing and filtering missing data. 
Remove Duplicates. 
Replacing values. 
Renaming Axis Indexes. 
Session 6: Pandas Data Wrangling
 Data Wrangling: 
Indexing, Re-indexing, 
Reorder, 
Sorting, Stastitics, 
Transforming data using 
Dataframe Joins, Merging, Concatenation, Overlap, Append, zip. 
Week 6: Pandas Data Analysis
 Data Analysis: 
 Sorting. 
 Analysing and finding data using filter, slicing and dataframe queries. 
 Finding data by Iteration. 
 Find statistics: Functions, Aggregate functions. 
 Unique values. 
String objects, Regex. 
Included with the Python Course
PCWorkshops Course Certificate on completion
Python Course Notes
Python Code Examples
Practical Python Course exercises and Code Samples
After the course: 1-Hour personalised online revision session
 

Pandas

Python Data Analytics with Python using 



Numpy, 




Pandas, Dataframes. 





Most attendees are in-work Data Professional.  Private individuals are very welcome. 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 



Python Data Analytics Course

<article>
<div>
<h5>Java Machine Learning Course</h5>
</div>
<div></div>
<p>  						 
	</p><div>
	<ul>
		<p>
		<b>Python Machine Learning Course. </b>
		<br /><b>Prerequisites: </b>Basic knowledge of Python 
		<br /><b>Our Style: </b>Hands-on, Practical  
		<br /><b>Location:  </b>Online, Instructor-led  
		<br /><b>Download:  </b>anaconda.com
		<br /><b>Duration:  </b>2 consecutive days, the first of which shows as the booking date.
		<br /><b>Times: </b>10am - 5pm
	    </p>
	</ul>	

<p></p>
</div></article>

<div>
	  <div>
		 <h5>Python Machine Learning Course </h5>
	  </div>
	  <div></div>
		<p> Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business.
		<br />
		<br />Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data.
		<br />
		<br />Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms.
		<br />
		<br />Gain a good understanding of how to plan a Machine Learning project.
		We create, experiment and run example code to implement the Python Machine Learning algorithms.
	  </p>
<div>
<h5>Course Topics</h5>
</div>
<div></div>
<div>
	<ul>	  
			<li>Supervised Machine Learning:
			<strong>Classification Algorithms:</strong>  	 
					Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine
					<br /><strong>Regression Algorithms:</strong>  Linear, Polynomial
			</li> 
	
	
			<li> <strong>  Unsupervised Machine Learning: </strong> Clustering Algorithms: K-means clustering, Hierarchical Clustering

			<br /><strong>Dimension Reduction Algorithms: </strong>Principal Component Analysis Latent Dirichlet allocation (LDA)

			<br /><strong>Association Algorithms:</strong> Apriori, Euclat

			<br /><strong>Other machine learning Algorithms:</strong>
			Reinforcement learning Algorithms: Q-Learning
			</li>
	
			<li>
			<strong>Ensemble Methods Algorithms:</strong> Stacking, bagging, boosting.
			</li> 
			
			<li>
			<strong>Random </strong>Forest Random Forest, Gradient Boosting
			</li> 
	 
		<li><strong>Neural Networks and Deep Leaning Algorithms:</strong>
		Convolutional Network (CNN)
		</li> 
		
		<li><strong>Data Exploration and Preprocessing:</strong> The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. 
		</li>
	
		<li> Injecting domain knowledge in the process, attributes are extracted from the data and engineered into Machine Learning algorithms.
		</li> 
</ul>
</div>
		  
		
		 
</div>

Python Scikit-Learn Machine Learning Course


Prerequisites: Basic knowledge of Python 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 1 days
Times: 11am - 5pm 
How to attend: 
You can select your dates and use the link  https://meet.goto.com/910697125  to attend
Python Machine Learning Course Description
 Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business. 
 
Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data. 
 
Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms. 
 
Gain a good understanding of how to plan a Machine Learning project. We create, experiment, and run example code to implement the Python Machine Learning algorithms. 
Course Topics
Supervised Machine Learning: Classification Algorithms: Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine 
Regression Algorithms: Linear, Polynomial
Unsupervised Machine Learning: Clustering Algorithms: K-means clustering, Hierarchical Clustering 
Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) 
Association Algorithms: Apriori, Euclat 
Other machine learning Algorithms: Reinforcement learning Algorithms: Q-Learning
Ensemble Methods Algorithms: Stacking, bagging, boosting.
Random Forest Random Forest, Gradient Boosting
Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN)
Data Exploration and Preprocessing: The first part of a Machine Learning project understands the data and the problem at hand. Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy.
Injecting domain knowledge in the process, attributes are extracted from the data and engineered into Machine Learning algorithms.

Unsupervised Machine Learning

Python Machine Learning algorithms can derive trends (learn) from data and make predictions on data by extrapolating on existing trends. Companies can take advantage of this to gain insights and ultimately improve business. 
 
Using Python Machine Learning scikit-learn, practice how to use Python Machine Learning algorithms to perform predictions on data. 
 
Learn the below listed algorithms, a small collection of available Python Machine Learning algorithms. 

Python Machine Learning, online instructor-led 

<div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms.</strong></p></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"></section></div></div><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></strong></p><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Machine Learning 2-day Course</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Prerequisites:</strong></em></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Basic knowledge of Python coding is a pre-requisite.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who Should Attend?</strong></em></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Practical:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project</li><li fr-original-style="" style="box-sizing: border-box;">We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms.&nbsp;</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course Outline:</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Supervised Machine Learning:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine</li><li fr-original-style="" style="box-sizing: border-box;">Regression Algorithms: Linear, Polynomial</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Unsupervised Machine Learning:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Clustering Algorithms: K-means clustering, Hierarchical Clustering</li><li fr-original-style="" style="box-sizing: border-box;">Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA)</li><li fr-original-style="" style="box-sizing: border-box;">Association Machine Learning Algorithms: Apriori, Euclat</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Other machine learning Algorithms:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting</li><li fr-original-style="" style="box-sizing: border-box;">Reinforcement learning Algorithms: Q-Learning</li><li fr-original-style="" style="box-sizing: border-box;">Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN)</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Exploration and Preprocessing:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">The first part of a Machine Learning project understands the data and the problem at hand.</li><li fr-original-style="" style="box-sizing: border-box;">Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">What is included in this Python Machine Learning:</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Python Machine Learning Certificate on completion &nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Python Machine Learning notes</li><li fr-original-style="" style="box-sizing: border-box;">Practical Python Machine Learning exercises and code examples</li><li fr-original-style="" style="box-sizing: border-box;">After the course, 1 free, online session for questions or revision Python Machine Learning.</li><li fr-original-style="" style="box-sizing: border-box;">Max group size on this Python Machine Learning is 4.</li></ul></div><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><div style="color: rgb(30, 10, 60); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(30, 10, 60);"><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h2 fr-original-style="" style="box-sizing: border-box;">Refund Policy</h2></div><div style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">No Refunds</div>

This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms.





Python Machine Learning 2-day Course
Prerequisites:
Basic knowledge of Python coding is a pre-requisite.
Who Should Attend?
This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn.
Practical:
We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project
We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms.
Course Outline:
Supervised Machine Learning:
Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine
Regression Algorithms: Linear, Polynomial
Unsupervised Machine Learning:
Clustering Algorithms: K-means clustering, Hierarchical Clustering
Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA)
Association Machine Learning Algorithms: Apriori, Euclat
Other machine learning Algorithms:
Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting
Reinforcement learning Algorithms: Q-Learning
Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN)
Data Exploration and Preprocessing:
The first part of a Machine Learning project understands the data and the problem at hand.
Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy.


What is included in this Python Machine Learning:
Python Machine Learning Certificate on completion
Python Machine Learning notes
Practical Python Machine Learning exercises and code examples
After the course, 1 free, online session for questions or revision Python Machine Learning.
Max group size on this Python Machine Learning is 4.





Refund Policy
No Refunds

Python Machine Learning Course, 1-Days, Online Attendance

Python Basics 1-days Online Instructor-Led

<div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python coding, interactive, instructor-led, hands-on, practical. From basics to working with professionals. Python Part Time. Python Coding.</strong></p></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></section></div></div></div><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Beginners Evenings Course</strong></strong></p><h2 style="color: rgb(30, 10, 60); box-sizing: border-box;" fr-original-style=" color: rgb(30, 10, 60);">Course summary</h2><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">This Python Programming course has become essential to all professional who would like to do code using Python. Learn evenings, work while studying. Work and study Python Part Time.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">It is a Python beginners course and teaches Python coding from scratch to intermediate.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Hands-on, practical. We code some real life examples in this course.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><em fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Duration:</strong></strong></em><em fr-original-style="" style="box-sizing: border-box;"><em fr-original-style="" style="box-sizing: border-box;">&nbsp;3 Evenings, once per week for 3 weeks 6pm-8pm, of which the first date only shows on the booking.</em></em></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Virtual Classroom:&nbsp;</strong></strong>You could attend in our classroom, or attend online via virtual classroom, by select the appropriate ticket.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who Should Attend?</strong></strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">This course is intended for beginner programmers who need to code in Python. Fast-paced, Quite intensive.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Course Outline:</strong></strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">1: Basics</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Data Types, Variables,</strong></strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Operators and Expressions:</strong></strong>&nbsp;Arithmetic operators; Relational operators; Assignment operator; Logical operators.</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Decision Making:</strong></strong>&nbsp;If statement; If - else statement; If- elif - else statement; Nested if - else;</li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Using Loops:</strong></strong>&nbsp;The while, while-else; do-while and the for loop; Enhanced for loop; Jump statements: break, continue; Nesting loops.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">2: Lists. Dictionaries, Json</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Python Data Structures: Lists. Data Structures: 2-d Lists, Tuples. Dictionary, Nested Disctionary.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">3: Built-in functions:</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Python Date Functions. Random. Math Functions. String Functions. Python Regex.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">4: Database:</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Connect to a database, create Database, create a table, insert, delete, update records, query a database and display results. Drop database, drop table.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">5: Files</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Exception Handling in Python<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">:&nbsp;</strong></strong>Fundamentals of exception handling; Exception types; Using try and except.</li><li fr-original-style="" style="box-sizing: border-box;">Files, streams: Create<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">,&nbsp;</strong></strong>Open, Traverse and Read Files: Csv, txt and Json Files.</li><li fr-original-style="" style="box-sizing: border-box;">API: Connecting to API&rsquo;s</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Session&nbsp;</strong></strong><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">6</strong></strong>:&nbsp;<strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">M ethods, Classes and Objects</strong></strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Creating and using Function, Working with parameters, Calling functions.</li><li fr-original-style="" style="box-sizing: border-box;">Object-Oriented Programming (OOP) principles. Modules and Classes, Creating an Object; Using an Object; Adding Instance variables; Controlling accessibility; Naming conventions for class member.s</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><br fr-original-style="" style="box-sizing: border-box;"></p><div data-testid="image-content" fr-original-style="" style="box-sizing: border-box;"><img src="https://img.evbuc.com/https%3A%2F%2Fcdn.evbuc.com%2Fimages%2F447713699%2F44980801875%2F1%2Foriginal.20230216-130657?h=2000&w=720&auto=format%2Ccompress&q=75&sharp=10&s=c331eac85ab8cd495a7a46a3aa8c2b7b" alt="" data-airgap-id="86" fr-original-style="" style="cursor: pointer; padding: 0px 1px; user-select: none; max-width: 100%; position: relative; box-sizing: border-box;" fr-original-class="fr-draggable"></div><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">FAQ</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Do I need Python on my Laptop?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Ideally spoken yes, but if not possible, you could use our online platform.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I pay by BACS?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I pay with PayPal?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, simply email us, a course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Do I get an invoice?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, on request.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I pay with a PO (Purchase Order Number)?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Do I get a certificate?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, a PCWorkshops Certificate</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I attend in classroom?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, on request, and it would incur an additional charge, depending on your location. We have offices in London, Manchester, Birmingham, Portmouth, Southend-on-Sea, Milton Keynes.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can beginners follow this course?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, this is a Python beginner friendly course. We offer Python courses with max 4 people, so we make sure each delegates fully understand the material covered</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Can I customise the course?</strong></p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Yes, all our Python courses are customisable. We can customise the dates, times, location. course outline.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"></p></div><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><div style="color: rgb(30, 10, 60); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(30, 10, 60);"><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h2 fr-original-style="" style="box-sizing: border-box;">Refund Policy</h2></div><div style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">No Refunds</div>

Python coding, interactive, instructor-led, hands-on, practical. From basics to working with professionals. Python Part Time. Python Coding.



Python Beginners Evenings Course
Course summary
This Python Programming course has become essential to all professional who would like to do code using Python. Learn evenings, work while studying. Work and study Python Part Time.
It is a Python beginners course and teaches Python coding from scratch to intermediate.
Hands-on, practical. We code some real life examples in this course.
Duration: 4 Evenings, once per week for 34weeks 6pm-8pm, of which the first date only shows on the booking.
Virtual Classroom: You could attend in our classroom, or attend online via virtual classroom, by select the appropriate ticket.
Who Should Attend?
This course is intended for beginner programmers who need to code in Python. Fast-paced, Quite intensive.
Course Outline:
Session 1: Basics
Python Data Types, Variables,
Operators and Expressions: Arithmetic operators; Relational operators; Assignment operator; Logical operators.
Decision Making: If statement; If - else statement; If- elif - else statement; Nested if - else;
Using Loops: The while, while-else; do-while and the for loop; Enhanced for loop; Jump statements: break, continue; Nesting loops.
Session 2: Lists. Dictionaries, Json
Python Data Structures: Lists. Data Structures: 2-d Lists, Tuples. Dictionary, Nested Disctionary. API's. Exceptions and CSV Files
Session 3: Built-in functions:
Python Random. Math Functions. String Functions.
Database:
Connect to a database, query a database and display results. 
Session 4: Methods, Classes and Objects
Creating and using Function, Working with parameters, Calling functions.
Object-Oriented Programming (OOP) principles. Modules and Classes, Creating an Object; Using an Object; Adding Instance variables; Controlling accessibility; Naming conventions for class member.s



FAQ
Do I need Python on my Laptop?
Ideally spoken yes, but if not possible, you could use our online platform.
Can I pay by BACS?
Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com
Can I pay with PayPal?
Yes, simply email us, a course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com
Do I get an invoice?
Yes, on request.
Can I pay with a PO (Purchase Order Number)?
Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com
Do I get a certificate?
Yes, a PCWorkshops Certificate
Can I attend in classroom?
Yes, on request, and it would incur an additional charge, depending on your location. We have offices in London, Manchester, Birmingham, Portmouth, Southend-on-Sea, Milton Keynes.
Can beginners follow this course?
Yes, this is a Python beginner friendly course. We offer Python courses with max 4 people, so we make sure each delegates fully understand the material covered
Can I customise the course?
Yes, all our Python courses are customisable. We can customise the dates, times, location. course outline.






Refund Policy
No Refunds

Course summary



This Python Programming course has become essential to all professional who would like to do code using Python. Learn evenings, work while studying. Work and study Python Part Time.



It is a Python beginners course and teaches Python coding from scratch to intermediate.



Hands-on, practical. We code some real life examples in this course.



Python Programming Beginners Evenings Course, Virtual Classroom.

Keep 020 7164 6359 for your contact on the day. Thanks for booking!

Python Evenings in Classroom, London

<p><strong> Boost Your Career By Enrolling On This Python Course To Get Through Challenging Moments!</strong></p><p><em><strong>Become a Python programmer and study one of the most in-demand talents for employers in the upcoming year!</strong></em></p><p>This is the most extensive, but simple, Python programming language course available! This programming language course is for you whether you've never coded before, know basic grammar, or want to learn about Python's advanced techniques. You will learn the Python programming language course the way that suits you best!</p><p>This course is accredited by <strong>CPD </strong>with <strong>10 CPD points</strong> for professional development. Students can expect to complete this course in around <strong>09 hours</strong>. You'll also get dedicated expert assistance from us to answer any queries you may have while studying our course.</p><p>Upon successful completion of the Python course, an instant e-certificate will be exhibited in your profile that you can order as proof of your new skills and knowledge. Add these amazing new skills to your resume and boost your employability by simply enrolling in this course.</p><p>You'll get a <strong>Free Student ID</strong> card by enrolling in this course. This ID card entitles you to discounts on bus tickets, movie tickets, and library cards.</p><p>This course can help you to accomplish your ambitions and prepare you for a meaningful career. So, join the course today - gear up with the essential skills to set yourself up for excellence!</p><p><strong>What you will learn from this Course?</strong></p><ul><li>Become a skilled Developer</li><li>How to use the basic structures: strings, lists, and dictionaries</li><li>How to use Object-Oriented Programming (OOP)</li><li>How to use core programming tools such as functions and loops</li><li>How to land your first job as a Developer</li><li>write Python scripts to perform automated actions</li><li>Start creating your Python programs from scratch</li><li>Learn to use variables to store, retrieve and calculate information</li></ul><p><strong>Why should you choose this course with Academy for Health &amp; Fitness?</strong></p><ul><li>Opportunity to earn a certificate accredited by <strong>CPD </strong>after completing this course</li><li><strong>Student ID</strong> card with amazing discounts - completely for <strong> FREE!</strong> (£10 postal charges will be applicable for international delivery)</li><li>Globally accepted standard structured lesson planning</li><li>Innovative and engaging content and activities</li><li>Assessments that measure higher-level thinking and skills</li><li>Complete the program in your own time, at your own pace</li><li>Each of our students gets full 24/7 tutor support</li></ul> <p>With this comprehensive course, you can achieve your dreams and train for your ideal career. The Python course provides students with an in-depth learning experience that they can work through at their own pace to enhance their professional development.</p><p>Start your learning journey straight away with this course and take a step toward a brighter future!</p><p><strong>*** Course Curriculum ***</strong></p><p><strong></strong><strong> Learn Programming with Python Course</strong><strong></strong></p><p><strong>Module 01:</strong></p><ul><li>An Installing Python</li><li>Documentation</li><li>Command-Line</li><li>Variables</li><li>Simple Python Syntax</li><li>Keywords</li><li>Import-Module</li></ul><p><strong>Module 02:</strong></p><ul><li>Additional Topics</li><li>If Elif Else</li><li>Iterable</li><li>For</li><li>Loops in Python</li><li>Execute</li><li>Exceptions</li></ul><p><strong>Module 03:</strong></p><ul><li>Data Types</li><li>Number Types</li><li>More Number Types</li><li>Strings</li><li>More Strings</li><li>Files</li><li>Lists</li><li>Dictionaries</li><li>Tuples</li><li>Sets</li></ul><p><strong>Module 04:</strong></p><ul><li>Comprehensions</li><li>Definitions</li><li>Functions</li><li>Default Arguments</li><li>Doc Strings</li><li>Variadic Functions</li><li>Factorial</li></ul><p><strong>Module 05:</strong></p><ul><li>Function Objects</li><li>Lambda</li><li>Generators</li><li>Object Initialization</li><li>Class Static Members</li><li>Classic Inheritance</li><li>Data Hiding</li></ul><p><strong>Assessment Process</strong></p><p>Once you have completed all the modules in the Python course, your skills and knowledge will be tested with an automated multiple-choice assessment. You will then receive instant results to let you know if you have successfully passed the course.</p><p><strong>Show off Your New Skills with a Certificate of Completion</strong></p><p>The learners have to successfully complete the assessment of this Course to achieve the <strong>CPD accredited certificate.</strong> Digital certificates can be ordered for only £10. The learner can purchase printed hard copies inside the UK for £29, and international students can purchase printed hard copies for £39.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        10 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <p>Anyone interested in learning more about the topic is advised to take this course. This course is open to everybody.</p>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You will not need any prior background or expertise to enrol in this course.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>After completing this course, you are to start your career or begin the next phase of your career.</p>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            £10
        </p>
        <h4>CPD Accredited Certificate </h4>
        <p>
            Hard copy certificate -
            £29
        </p>
            <div> <p>If you are an international student, then you have to pay an additional 10 GBP as an international delivery charge.</p> </div>

                        </div>

Boost Your Career By Enrolling On This Python Course To Get Through Challenging Moments!
Become a Python programmer and study one of the most in-demand talents for employers in the upcoming year!
This is the most extensive, but simple, Python programming language course available! This programming language course is for you whether you've never coded before, know basic grammar, or want to learn about Python's advanced techniques. You will learn the Python programming language course the way that suits you best!
This course is accredited by CPD with 10 CPD points for professional development. Students can expect to complete this course in around 09 hours. You'll also get dedicated expert assistance from us to answer any queries you may have while studying our course.
Upon successful completion of the Python course, an instant e-certificate will be exhibited in your profile that you can order as proof of your new skills and knowledge. Add these amazing new skills to your resume and boost your employability by simply enrolling in this course.
You'll get a Free Student ID card by enrolling in this course. This ID card entitles you to discounts on bus tickets, movie tickets, and library cards.
This course can help you to accomplish your ambitions and prepare you for a meaningful career. So, join the course today - gear up with the essential skills to set yourself up for excellence!
What you will learn from this Python Course?
Become a skilled Developer
How to use the basic structures: strings, lists, and dictionaries
How to use Object-Oriented Programming (OOP)
How to use core programming tools such as functions and loops
How to land your first job as a Developer
write Python scripts to perform automated actions
Start creating your Python programs from scratch
Learn to use variables to store, retrieve and calculate information
Why should you choose this course with Academy for Health & Fitness?
Opportunity to earn a certificate accredited by CPD after completing this course
Student ID card with amazing discounts - completely for FREE! (£10 postal charges will be applicable for international delivery)
Globally accepted standard structured lesson planning
Innovative and engaging content and activities
Assessments that measure higher-level thinking and skills
Complete the program in your own time, at your own pace
Each of our students gets full 24/7 tutor support
With this comprehensive course, you can achieve your dreams and train for your ideal career. The Python course provides students with an in-depth learning experience that they can work through at their own pace to enhance their professional development.



Start your learning journey straight away with this Python course and take a step toward a brighter future!
*** Course Curriculum ***
Learn Programming with Python Course
Module 01:
An Installing Python
Documentation
Command-Line
Variables
Simple Python Syntax
Keywords
Import-Module
Module 02:
Additional Topics
If Elif Else
Iterable
For
Loops in Python
Execute
Exceptions
Module 03:
Data Types
Number Types
More Number Types
Strings
More Strings
Files
Lists
Dictionaries
Tuples
Sets
Module 04:
Comprehensions
Definitions
Functions
Default Arguments
Doc Strings
Variadic Functions
Factorial
Module 05:
Function Objects
Lambda
Generators
Object Initialization
Class Static Members
Classic Inheritance
Data Hiding
Assessment Process
Once you have completed all the modules in the Python course, your skills and knowledge will be tested with an automated multiple-choice assessment. You will then receive instant results to let you know if you have successfully passed the course.
Show off Your New Skills with a Certificate of Completion
The learners have to successfully complete the assessment of this Course to achieve the CPD accredited certificate. Digital certificates can be ordered for only £10. The learner can purchase printed hard copies inside the UK for £29, and international students can purchase printed hard copies for £39.
CPD 
10 CPD hours / points  Accredited by CPD Quality Standards



Who is this course for? 
Anyone interested in learning more about the topic is advised to take this Python course. This course is open to everybody.



Requirements 
You will not need any prior background or expertise to enrol in this Python course.



Career path
After completing this Python course, you are to start your career or begin the next phase of your career.



Certificates 
Certificate of completion
Digital certificate - £10 
CPD Accredited Certificate
Hard copy certificate - £29 
If you are an international student, then you have to pay an additional 10 GBP as an international delivery charge.

Academy for Health and Fitness

Assessment Practising Certificate (APC)

Trainers Course

Continuous Professional Development (CPD)

Python - CPD Accredited

<article>
<div>
<h5>Java Course 1 hour. Code the Hangman</h5>
</div>
<div></div>
<p>  						 
	</p><div>
	<ul>
		<p>
		<b>Python Course, code the Hangman. </b>Basic Python Course covers in one hour the coding of an interesting app. 
		<br />Any one very welcome.  
		<br /><b>Our Style: </b>Hands-on, Practical  
		<br /><b>Location:  </b>Online, Instructor-led  
		<br /><b>Download:  </b>anaconda.com
		<br /><b>Duration:  </b>1 Hour
		<br /><b>Times: </b>arrange a time for your time zone
	    </p>
	</ul>	

<p></p>
</div></article>

<div>
	  <div>
		 <h5>Python Basics Course Description</h5>
	  </div>
	  <div></div>
	  <p> Learn to code the Hangman Game in 1 hour. 
		<br /> Essentials of Python programming, explaining Python technology. 
		<br /> Practical Python lessons and Python exercises. 
		<br /> Great Tutors. 
		<br /> Online. 
		<br /> Learn plenty in one day: Code The Hangman Game in Python
	  </p>
	<div>
	<h5>Code the Hangman Game</h5>
	</div>
	<div></div>
	<div> 
		<p>  <strong>Python Course 1 Hour:</strong>  
		<br />  	STEP 1: Using variables. Arithmetic operations. Strings. String Functions
		<br />  	STEP 2: Getting user input from console. Decision Making (If-else).
		<br />  	STEP 3: For and While Loops. Repeat code by using loops.
		<br />  	STEP 4: Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values.
		<br />  	STEP 5: Object Oriented Programming: Functions. Classes.  
		<br />  	STEP 6: Create the Hangman Game.			
		</p>
	</div>
 
</div>
 

<div>   

	   <div id="cincluded">
		  <div>
			 <h5>What is included with The Python Course 1 Hour</h5>
		  </div>

		  <article>
		  <div>
			 <ul>
				<li>PCWorkshops Python Course Certificate on completion  </li> 
				<li>Python Course Notes</li>
				<li>Python Code Examples</li>
				<li>Practical Python Course exercises and Code Samples</li>
				<li>After the course: 1-Hour personalised online revision session</li>
			 </ul>
		  </div>
		  </article>
	   </div>
				    
<div>
	                  <div>
	                     <h5 id="cincluded2">Book the Python Course 1 hour</h5>
	                  </div>
 
	 
 <div id="eventbrite-widget-container-69413456517"></div>




									
					
					 
</div>
				   <div id="caboutus">
	                  <div>
	                     <h5>About us</h5>
	                  </div> 
	                  	<article>
					    <div>
					    	<div>
					    		<div>
					    			
					    			<h5>Our experienced trainers are award winners. </h5> 
					    			<ul>
										<li>
											More about us
										</li>
										<li>
											FAQ's
										</li>
										<li>
											Client Comments  
										</li>
									 </ul>
					    		</div>
					    		<div>
					    			
					    				
					    			
					    		</div>
					    	</div>
	                     
					    </div>
					    </article>						
	               </div>
				   
				   
	        </div>

Java Course 1 hour. Code the Hangman
Online, Instructor-led
 
 Python Course, code the Hangman. Basic Python Course covers in one hour the coding of an interesting app. 
Any one very welcome. 
Our Style: Hands-on, Practical 

Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 1 Hour 
Times: arrange a time for your time zone 
Python Basics Course Description
 Learn to code the Hangman Game in 1 hour. 
 Essentials of Python programming, explaining Python technology. 
 Practical Python lessons and Python exercises. 
 Great Tutors. 
 Online. 
 Learn plenty in one day: Code The Hangman Game in Python 
Code the Hangman Game
 Python Course 1 Hour: 
 STEP 1: Using variables. Arithmetic operations. Strings. String Functions 
 STEP 2: Getting user input from console. Decision Making (If-else). 
 STEP 3: For and While Loops. Repeat code by using loops. 
 STEP 4: Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values. 
 STEP 5: Object Oriented Programming: Functions. Classes. 
 STEP 6: Create the Hangman Game. 
What is included with The Python Course 1 Hour
PCWorkshops Python Course Certificate on completion
Python Course Notes
Python Code Examples
Practical Python Course exercises and Code Samples
After the course: 1-Hour personalised online revision session
Book the Python Course 1 hour
About us
Our experienced trainers are award winners.
More about us
FAQ's
Client Comments

Application Software

Computing & Software Development Tools

Coding For Kids

Remote Desktop Software

Software Development

Python Course, code the Hangman. Basic Python Course covers in one hour the coding of an interesting app. 
Any one very welcome. 
Our Style: Hands-on, Practical 
Location: Online, Instructor-led 
Download: anaconda.com 
Duration: 1 Hour 
Times: arrange a time for your time zone 

Python Taster, Code the Hangman, Online Instrcutor-led 

<div style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><div data-testid="summary" id="isPasted" fr-original-style="" style="box-sizing: border-box;"><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online.</strong></p></div><div data-testid="organizerBrief" fr-original-style="" style="box-sizing: border-box;"><div data-testid="creator-signal-main-section" fr-original-style="" style="box-sizing: border-box;"><section fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></section></div></div></div><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h1 style="color: rgb(57, 54, 79); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(57, 54, 79);">Learn to code a Password Validator in 1 hour.&nbsp;</h1><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">Basics made simple! &nbsp;Learn plenty in one day: Code A Password Validator</p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Essentials of Python programming.</li><li fr-original-style="" style="box-sizing: border-box;">Practical lessons and exercises.</li><li fr-original-style="" style="box-sizing: border-box;">Great Tutors.&nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Online.</li><li fr-original-style="" style="box-sizing: border-box;">You may Request a Central London Location, per email</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Who will the Course Benefit?</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">This is a fantastic course for beginners</li><li fr-original-style="" style="box-sizing: border-box;">Or for coders, simply fast-track crossing over to Python.</li></ul><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Teaching Style:&nbsp;</strong>Practical, Interactive, Personalised. Useful examples.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">What is included?</strong></p><ul style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><li fr-original-style="" style="box-sizing: border-box;">Course notes, exercises and examples.</li><li fr-original-style="" style="box-sizing: border-box;">Course certificate.</li></ul><h2 style="color: rgb(30, 10, 60); box-sizing: border-box;" fr-original-style=" color: rgb(30, 10, 60);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Learn Python by coding a Password Validator</strong></h2><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 1:&nbsp;</strong>Using variables. Arithmetic operations. Strings. String Functions</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 2:&nbsp;</strong>Getting user input from console. Decision Making(If-else)</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 3:&nbsp;</strong>For and While Loops. Repeat code by using loops.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 4:&nbsp;</strong>Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 5:&nbsp;</strong>Object Oriented Programming. Functions. Classes.</p><p style="color: rgb(111, 114, 135); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">STEP 6:&nbsp;</strong>Create the Password Validator</p></div><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><div style="color: rgb(30, 10, 60); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(30, 10, 60);"><hr fr-original-style="" style="border-color: var(--border-muted); border-style: solid; clear: both; break-after: page; user-select: none; box-sizing: border-box;"><h2 fr-original-style="" style="box-sizing: border-box;">Refund Policy</h2></div><div style="color: rgb(111, 114, 135); box-sizing: border-box;" fr-original-style=" color: rgb(111, 114, 135);">No Refunds</div>

Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online.



Learn to code a Password Validator in 1 hour. 
Basics made simple! Learn plenty in one day: Code A Password Validator
Essentials of Python programming.
Practical lessons and exercises.
Great Tutors.
Online.
You may Request a Central London Location, per email
Who will the Course Benefit?
This is a fantastic course for beginners
Or for coders, simply fast-track crossing over to Python.
Teaching Style: Practical, Interactive, Personalised. Useful examples.
What is included?
Course notes, exercises and examples.
Course certificate.
Learn Python by coding a Password Validator
STEP 1: Using variables. Arithmetic operations. Strings. String Functions
STEP 2: Getting user input from console. Decision Making(If-else)
STEP 3: For and While Loops. Repeat code by using loops.
STEP 4: Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values.
STEP 5: Object Oriented Programming. Functions. Classes.
STEP 6: Create the Password Validator





Refund Policy
No Refunds

Online Course Marketing

Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online.
Learn to code a Password Validator in 1 hour. 



1040 Courses delivered Online

Network management technologies

By Systems & Network Training

Fundamentals of Machine Learning

By Packt

Python Programming: Beginner To Expert

By iStudy UK

Deep Learning with Real-World Projects

By Packt

Python For Beginners Part 1

By Janets

Data Analysis, Data Science, Data Protection, Business Analysis, Python & Excel

By Compliance Central

Machine Learning with Python

By Apex Learning

Learn Python Programming from Scratch

By NextGen Learning

Level 7 Data Science & Machine Learning (Python, R, SQL & Microsoft Azure) - - QLS Endorsed

By Skill Up

Natural Language Processing with Real-World Projects

By Packt