Name: Data Analyst : Data Analyst (Data Analytics) - Level 5 Diploma Course
Price: 51 GBP
Availability: InStock

<p>Get ready for an exceptional online learning experience with the <strong>Big Data Analysis, Data Science, Fintech &amp; Python for Data Analyst </strong>bundle! This carefully curated collection of 20 premium courses 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 Big Data Analysis, Data Science, Fintech &amp; Python for Data Analyst is a dynamic package, that blends 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, the<strong> Data Analysis </strong>package has something for everyone.</p><p>As part of the Big Data Analysis, Data Science, Fintech &amp; Python for Data Analyst package, you will receive complimentary PDF certificates for all courses in this bundle at no extra cost. Equip yourself with the Data Analysis 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 courses:</strong></p><p><strong>CPD Quality Standards</strong><strong> Courses:</strong></p><ol><li><strong>Big Data Analytics with PySpark Power BI and MongoDB</strong></li><li><strong>Big Data Analytics with PySpark Tableau Desktop and MongoDB</strong></li><li><strong>Building Big Data Pipelines with PySpark MongoDB and Bokeh</strong></li><li><strong>Develop Big Data Pipelines with R &amp; Sparklyr &amp; Tableau</strong></li><li><strong>Develop Big Data Pipelines with R, Sparklyr &amp; Power BI</strong></li><li><strong>Learn Python, JavaScript, and Microsoft SQL for Data Science</strong></li><li><strong>SQL for Data Science, Data Analytics, and Data Visualization</strong></li><li><strong>Excel Data Analysis</strong></li><li><strong>Introduction to Data Analytics with Tableau</strong></li><li><strong>Business and Data Analytics for Beginners</strong></li><li><strong>Google Data Studio: Data Analytics </strong></li><li><strong>Basic Data Analysis</strong></li><li><strong>FinTech</strong></li></ol><p><strong>Learning Outcome:</strong></p><ul><li>Gain comprehensive insights into multiple fields.</li><li>Foster critical thinking and problem-solving skills across various disciplines.</li><li>Understand industry trends and best practices through the<strong> Data Analysis</strong> Bundle.</li><li>Develop practical skills applicable to real-world situations.</li><li>Enhance personal and professional growth with <strong>Data Analysis.</strong></li><li>Build a strong knowledge base in your chosen course via <strong>Data Analysis</strong>.</li><li>Benefit from the flexibility and convenience of online learning.</li><li>With the <strong>Data Analysis</strong> package, validate your learning with a CPD certificate.</li></ul><p>Each course in this bundle holds a prestigious CPD accreditation, symbolising exceptional quality. The materials, brimming with knowledge, are regularly updated, ensuring their relevance. This 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 the Big Data Analysis, Data Science, Fintech &amp; Python for Data Analyst, a rich anthology of 15 diverse courses. Each course in the <strong>Data Analysis</strong> bundle is handpicked by our experts to ensure a wide spectrum of learning opportunities. ThisBig Data Analysis, Data Science, Fintech &amp; Python for Data Analyst bundle will take you on a unique and enriching educational journey.</p><p>The 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 Big Data Analysis, Data Science, Fintech &amp; Python for Data Analyst bundle offers you the flexibility and convenience to learn at your own pace. Make the Data Analysis package your trusted companion in your lifelong learning journey.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        35 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>Big Data Analysis, Data Science, Fintech &amp; Python for Data Analyst</strong> bundle is perfect for:</p><ul><li>Lifelong learners looking to expand their knowledge and skills.</li><li>Professionals seeking to enhance their career with CPD certification.</li><li>Individuals wanting to explore new fields and disciplines.</li><li>Anyone who values flexible, self-paced learning from the comfort of home.</li></ul>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>Unleash your potential with the <strong>Big Data Analysis, Data Science, Fintech &amp; Python for Data Analyst </strong>bundle. Acquire versatile skills across multiple fields, foster problem-solving abilities, and stay ahead of industry trends. Ideal for those seeking career advancement, a new professional path, or personal growth. Embrace the journey with the <strong>Data Analysis </strong>bundle package.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate Of Completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Certificate Of Completion</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
            <div><p><strong>You will get a complimentary Hard Copy Certificate.</strong></p></div>

                        </div>

NextGen Learning

Business Analytics & Intelligence

Big Data Analytics

Data Science

Data Skills

Data Analyst

Continuous Professional Development (CPD)

Big Data Analysis, Data Science, Fintech & Python for Data Analyst

General Admission

<p>Recent developments in data analytics and statistics underscore the critical importance of understanding both data structure and analytics methodologies in today's data-driven world. With the exponential growth of data, businesses are increasingly relying on skilled professionals who can harness the power of data to drive informed decision-making. Our comprehensive <strong>Data Structure, Data Analytics with Statistics &amp; Data Science  QLS Endorsed Diploma </strong>bundle, endorsed by the Quality Licence Scheme (QLS) and accredited by the CPD Quality Standards (QS), offers a holistic approach to mastering data structure, data analytics, and statistical techniques.</p><p>In an era where data reigns supreme, organisations seek individuals who can navigate complex datasets with confidence and precision. This Data Structure, Data Analytics bundle equips learners with the essential skills and knowledge needed to excel in the field of data science and analytics. By delving into topics such as data manipulation, statistical analysis, and database management, participants gain a deep understanding of how to extract valuable insights from raw data. Moreover, our guided courses in career development and communication empower learners to effectively communicate their findings and advance their professional journey.</p><p><strong>Bundle Include includes:</strong></p><p><strong>QLS Endorsed Courses:</strong></p><ul><li><strong>Course 01:</strong> Certificate in Data Analytics with Tableau at QLS Level 3</li><li><strong>Course 02:</strong> Diploma in Data Structure at QLS Level 5</li><li><strong>Course 03:</strong> Advanced Diploma in Statistics &amp; Probability for Data Science &amp; Machine Learning at QLS Level 7</li></ul><p><strong>CPD QS Accredited Courses:</strong></p><ul><li><strong>Course 04:</strong> Business and Data Analytics for Beginners</li><li><strong>Course 05:</strong> Learn Financial Analytics and Statistical Tools</li><li><strong>Course 06: </strong>SQL For Data Analytics &amp; Database Development</li><li><strong>Course 07:</strong> Big Data Analytics with PySpark Power BI and MongoDB</li><li><strong>Course 08</strong>: Google Data Studio: Data Analytics </li><li><strong>Course 09: </strong>Business Intelligence Analyst</li><li><strong>Course 10</strong>: Spatial Data Visualization and Machine Learning in Python</li><li><strong>Course 11:</strong> Data Analysis In Excel</li></ul><p>Take your career to the next level with our Data Structure, Data Analytics bundle that includes technical courses and five guided courses focused on personal development and career growth.</p><ul><li><strong>Course 12:</strong> Career Development Plan Fundamentals</li><li><strong>Course 13</strong>: CV Writing and Job Searching</li><li><strong>Course 14:</strong> Networking Skills for Personal Success</li><li><strong>Course 15: </strong>Ace Your Presentations: Public Speaking Masterclass</li><li><strong>Course 16</strong>: Decision Making and Critical Thinking </li></ul><p>Seize this opportunity to elevate your career with our comprehensive Data Structure, Data Analytics bundle, endorsed by the prestigious QLS and accredited by CPD.Data Structure, Data Analytics with Statistics &amp; Data Science QLS Endorsed Diploma.</p><p><strong>Learning Outcomes:</strong></p><p>Upon completion of this Data Structure, Data Analytics bundle, participants will be able to:</p><ul><li>Demonstrate proficiency in data analytics tools such as Tableau, SQL, and Google Data Studio through Data Structure, Data Analytics courses.</li><li>Apply statistical techniques to analyse and interpret data for informed decision-making.</li><li>Design and implement data structures to efficiently store and retrieve information.</li><li>Utilise machine learning algorithms for predictive analysis and pattern recognition.</li><li>Develop effective communication and presentation skills to convey insights to stakeholders.</li><li>Navigate career development pathways in the field of data science and analytics.</li></ul><p>This Data Structure, Data Analytics course bundle provides a deep dive into the foundational principles of data structure, data analytics, and statistical methodologies. Participants will explore the fundamental concepts of data manipulation, including sorting, searching, and storing data efficiently. Through hands-on exercises and theoretical discussions, learners will gain a solid understanding of various data structures such as arrays, linked lists, trees, and graphs, along with their applications in real-world scenarios.</p><p>Moreover, the Data Structure, Data Analytics bundle encompasses a comprehensive exploration of data analytics techniques, equipping participants with the skills to extract actionable insights from complex datasets. From descriptive and inferential statistics to predictive modelling and machine learning algorithms, learners will discover how to uncover patterns, trends, and correlations within data, enabling informed decision-making and strategic planning. Throughout the Data Structure, Data Analytics course, emphasis is placed on practical applications and case studies, allowing participants to apply their knowledge to solve real-world problems in diverse domains.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        160 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>This Data Structure, Data Analytics course is perfect for:</p><ul><li>Aspiring data analysts seeking to enhance their analytical skills acrod Data Structure, Data Analytics courses. </li><li>Professionals transitioning into roles requiring proficiency in data analytics.</li><li>Students pursuing careers in data science, statistics, or related fields.</li><li>Business professionals looking to leverage data for strategic decision-making.</li><li>Individuals interested in advancing their career prospects in the field of data analytics.</li><li>Anyone seeking to gain a comprehensive understanding of data structure, analytics, and statistics.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You are warmly invited to register for this bundle. Please be aware that there are no formal entry requirements or qualifications 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 completion of the Data Structure, Data Analytics courses, you will be able to:</p><ul><li>Data Analyst</li><li>Business Intelligence Analyst</li><li>Data Scientist</li><li>Statistician</li><li>Database Administrator</li><li>Machine Learning Engineer</li><li>Data Engineer</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>13 CPD Quality Standard Certificates</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>3 QLS Endorsed Certificates</h4>
        <p>
            Hard copy certificate -
            Included
        </p>

                        </div>

Compliance Central

Data Structure, Data Analytics with Statistics & Data Science  QLS Endorsed Diploma

"Start your career as a Certified Python Programmer and earn up to £70,000 per Year."
Are you looking to make your mark in the ever-evolving world of Data Analyst? The demand for Python programmers has never been higher. Just in the UK, job postings for Analysts / Python programmers surged by an astounding 70% in 2022. This exponential growth trend signifies the soaring need for skilled Python programmers. Amid this vibrant job market, our Python Programmer online Training is your golden ticket to a prosperous career in programming or Data Analysis. Regardless of your level - beginner or expert - we ensure a comprehensive learning experience that will enhance your current skills and prepare you for the dynamic tech industry.
We envision being your reliable ally throughout your journey - from imparting quality Python training to ensuring your employability in the programming world.
Our Python Certification Program offers more than just technical know-how. We extend comprehensive career mentoring and support designed to mould you into an industry-ready professional. We'll assist you in creating an impressive resume, preparing for interviews, and landing your dream job. With a vast network of partner companies continually looking for Python programmers, we provide an opportunity to get your foot in the door of your desired companies.
Our mission is simple - to be your trusted partner every step of the way, from training to employment.
In addition to teaching you the technical skills you need, we will also provide you with career mentoring and support. We will help you build your resume, prepare for interviews, and land your dream job. We also have partnerships with many companies that are hiring Programmers, so we can help you get your foot in the door.
If you are not happy with our service, we also offer a 100% money-back guarantee. So what are you waiting for? Enrol in our Python Certification - IT Program today and start your journey to becoming a successful Python Programmer!
Why Choose Us?
So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Certified Python Programmers:
Personalised Guidance: We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Python experience, we will guide you towards honing your skills and developing a strong foundation in Python.
One-On-One Consultation: Gain invaluable insights and guidance from seasoned professionals who have thrived in the Python programming field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.
Extensive Job Opportunities: We have established partnerships with numerous companies actively seeking Certified Python Programmers. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.
Interview Preparation: No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.
Courses we will provide once you enrol in the program:
Course 01: Computer Science With Python
Course 02: Ultimate Python Training for Beginners
Course 03: Python Intermediate Training
Course 04: Python Advanced Training
Course 05: Deep Learning & Neural Networks Python - Keras
Course 06: Complete Python Machine Learning & Data Science Fundamentals
Course 06: Introduction to Data Analysis
Course 07: Business and Data Analytics for Beginners
Course 08: Data Analytics with Tableau
Course 09: Quick Data Science Approach from Scratch
Course 10: Learn MySQL from Scratch for Data Science and Analytics
Course 11: SQL for Data Science, Data Analytics and Data Visualization
Course 12: Statistics & Probability for Data Science & Machine Learning
Course 13: Basic Google Data Studio
Course 14: Machine Learning with Python Course
Course 15: Python Programming Bible | Networking, GUI, Email, XML, CGI
Course 16: Web Scraping and Mapping Dam Levels in Python and Leaflet
Course 17: Coding Essentials - Javascript, ASP. Net, C#
Course 19: Master JavaScript with Data Visualization
How Can We Offer Job Guarantees?
HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.
The Python Certification - IT Training is completed in 9 easy steps:
Step 1: Enrol in the Programme
Begin your exciting journey with us by enrolling in the Python Certification Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.
After you enrol in the Program, you will get lifetime access to 19 Premium Courses related to Python Programming. These courses will teach you the knowledge and skills required to become a successful Python Prgrammer. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!
Step 2: Initial One-On-One Counselling Session
Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.
Step 3 - Certification upon Course Completion
After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.
Step 4: CV Revamping
Our team of professionals will build you a compelling CV and LinkedIn profile. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the programming/development industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently.
Step 5: Building Network and Submitting CV
We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile.
Step 6: Interview Preparation
With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.
Step 7: Securing Job Interviews
Leveraging our partnerships with leading companies, we'll secure job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want.
Step 8: Post-Interview Support
Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.
Step 9: Celebrate Your New Job!
Once you've secured your dream job in Python Programming, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Python Programming begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
This Python Certification Course is suitable for:
Beginners with no prior programming experience who are looking to enter the world of coding.
Intermediate programmers who wish to expand their skills and explore Python's extensive usage.
IT professionals seeking to diversify their skill sets and stay relevant in today's tech-driven market.
Data analysts and scientists who want to leverage Python's powerful libraries for their data processing needs.
Students and recent graduates looking to enhance their employability in the thriving tech industry.
Entrepreneurs who wish to understand and utilise Python to automate tasks and analyse data for their businesses.
Anyone with a keen interest in Python programming and a desire to delve into its applications in diverse fields like web development, data science, machine learning, and more.
 Requirements 
No experience required. Just enrol & start learning python.
 Career path 
Upon completion of our Program, the potential career paths include:
Python Developer: £30,000 - £90,000 annually
Data Scientist: £40,000 - £100,000 annually
Machine Learning Engineer: £50,000 - £110,000 annually
Data Analyst: £35,000 - £85,000 annually
Software Engineer: £35,000 - £95,000 annually
Back-end Developer: £40,000 - £95,000 annually
Web Developer: £30,000 -£85,000 annually
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Academy for Health and Fitness

Programming Fundamentals

Career Development

IT Certifications

Become an IT professional with our Python Certification - IT Job Ready Program! Gain comprehensive skills in Python programming, data analysis, and automation. We offer a money-back guarantee if you don't secure a job within six months of completion. Enroll now and jumpstart your tech career!


Ready to land your dream job in tech? Our Python Certification - IT Job Ready Program equips you with essential Python programming, data analysis, and automation skills. Plus, we offer a money-back guarantee if you don't get hired within six months of completing the course. Don't miss out – enroll today and take the first step towards a successful IT career! 💻📊 #PythonCertification #TechTraining #CareerReady #MoneyBackGuarantee

Python Certification - IT Job Ready Program with Money Back Guarantee

<p><strong>** 13-in-1 Data Analysis Bundle **</strong></p><p><strong>Unleash Your Full Data Analysis Potential with Our Comprehensive Bundle!</strong></p><p>Are you ready to elevate your data analysis skills to a whole new level? Look no further! Our Data Analysis Bundle is the ultimate solution you've been searching for.</p><p>In today's data-driven world, being proficient in a single aspect of data analysis is just not enough. That's why we've carefully curated a bundle of courses that complement each other seamlessly, creating a holistic and powerful learning experience.</p><p><strong>The Data Analysis Bundle includes the following courses:</strong></p><ol><li>Diploma in Data Analytics with Tableau</li><li>Data Analytics</li><li>Google Data Studio: Data Analytics</li><li>Big Data Analytics with PySpark Power BI and MongoDB</li><li>Big Data Analytics with PySpark Tableau Desktop and MongoDB</li><li>Learn MySQL from Scratch for Data Science and Analytics</li><li>SQL for Data Science, Data Analytics and Data Visualization</li><li>Data Analysis In Excel</li><li>Diploma in Data Analysis Fundamentals</li><li>Business Data Analysis</li><li>Data Science &amp; Machine Learning with Python</li><li>R Programming for Data Science</li><li>Learn Python, JavaScript, and Microsoft SQL for Data science</li></ol><p><strong>Course Significant Points:</strong></p><ul><li>Quality Licence Scheme Endorsed</li><li>CPD Accredited Course</li><li>Unlimited Retake Exam &amp; Tutor Support</li><li>Easy Accessibility to the Course Materials</li><li>100% Learning Satisfaction Guarantee</li><li>Lifetime Access &amp; 24/7 Support</li><li>Self-paced online course Modules</li><li>Covers to Explore Multiple Job Positions</li></ul><p><strong>How is the course assessed?</strong></p><p>To assess your learning, you have to complete the assignment questions provided at the end of the course. You have to score at least 60% to pass the exam and to qualify for Quality Licence Scheme endorsed and CPD-accredited certificates. After passing the assignment exam, you will be able to apply for a certificate.</p><p><strong>Meet the Endorsement</strong></p><p>The Quality Licence Scheme has been designed specifically to recognise high-quality courses. In addition, the QLS certificate enriches your CV and recognises your quality study on the relevant subject.</p><p><strong>Meet the Accreditation</strong></p><p>CPD Quality Standards (CPD QS) accreditation assures the Data Analysis with Excel course training and learning activities are relevant, reliable, and up to date.</p><p><strong>**Enrol Today and Unleash Your Full Data Analysis Potential!** </strong></p><p>The Data Analysis Bundle is a comprehensive collection of courses designed to equip individuals with the skills and knowledge necessary for a successful career in data analysis. From foundational concepts to advanced techniques and tools, this bundle covers a wide range of topics in the field of data analysis. Whether you're a beginner looking to get started or a professional seeking to enhance your skills, these courses provide a well-rounded education in data analysis.</p><p><strong>**Diploma in Data Analytics with Tableau**</strong></p><ul><li>Introduction To The Course</li><li>Project 1: Discount Mart (Sales And Profit Analytics)</li><li>Project 2: Green Destinations (HR Analytics)</li><li>Project 3: Superstore (Sales Agent Tracker)</li><li>Northwind Trade (Shipping Analytics)</li><li>Project 5: Tesla (Stock Price Analytics)</li><li>Bonus: Introduction To Database Concepts</li><li>Tableau Stories</li></ul><p><strong>**Data Analytics**</strong></p><ul><li>Introduction To The World Of Data</li><li>Basics Of Data Analytics</li><li>Statistics For Data Analytics</li><li>Actions Taken In The Data Analysis Process</li><li>Gathering The Right Information</li><li>Storing Data</li><li>Data Mining</li><li>Excel For Data Analytics</li><li>Tools For Data Analytics</li><li>Data-Analytic Thinking</li><li>Data Visualisation That Clearly Describes Insights</li><li>Data Visualisation Tools</li></ul><p><strong>**Google Data Studio: Data Analytics**</strong></p><ul><li>Introduction</li><li>Google Sheets</li><li>Google Data Studio</li></ul><p><strong>**Big Data Analytics with PySpark Tableau Desktop and MongoDB**</strong></p><ul><li>Introduction</li><li>Setup And Installations</li><li>Data Processing With PySpark And MongoDB</li><li>Machine Learning With PySpark And MLlib</li><li>Creating The Data Pipeline Scripts</li><li>Tableau Data Visualization</li><li>Source Code</li></ul><p><strong>**Learn MySQL from Scratch for Data Science and Analytics**</strong></p><ul><li>Getting Started</li><li>SQL Server Setting Up</li><li>SQL Database Basics</li><li>SQL DML (Data Manipulation Language)</li><li>SQL DDL (Data Definition Language)</li><li>SQL DCL (Data Control Language)</li><li>SQL Statement Basic</li><li>Filtering Data Rows</li><li>Aggregate Functions For Data Analysis</li><li>SQL Data Analyticstatements</li><li>SQL Group By Statement</li><li>JOINS</li><li>SQL Constraints</li><li>Views</li><li>Advanced SQL Functions</li><li>SQL Stored Procedures</li><li>Import &amp; Export Data</li><li>Backup And Restore Database</li></ul><p><strong>**Data Analysis In Excel**</strong></p><ul><li>Modifying A Worksheet</li><li>Working With Lists</li><li>Analyzing Data</li><li>Visualizing Data With Charts</li><li>Using PivotTables And PivotCharts</li><li>Working With Multiple Worksheets And Workbooks</li><li>Using Lookup Functions And Formula Auditing</li><li>Automating Workbook Functionality</li><li>Creating Sparklines And Mapping Data</li><li>Forecasting Data</li></ul><p><strong>**Diploma in Data Analysis Fundamentals**</strong></p><ul><li>Introduction</li><li>Agenda And Principles Of Process Management</li><li>The Voice Of The Process</li><li>Working As One Team For Improvement</li><li>Exercise: The Voice Of The Customer</li><li>Tools For Data Analysis</li><li>The Pareto Chart</li><li>The Histogram</li><li>The Run Chart</li><li>Exercise: Presenting Performance Data</li><li>Understanding Variation</li><li>The Control Chart</li><li>Control Chart Example</li><li>Control Chart Special Cases</li><li>Interpreting The Control Chart</li><li>Control Chart Exercise</li><li>Strategies To Deal With Variation</li><li>Using Data To Drive Improvement</li><li>A Structure For Performance Measurement</li><li>Data Analysis Exercise</li><li>Course Project</li><li>Test Your Understanding</li></ul><p><strong>**Business Data Analysis**</strong></p><ul><li>Introduction To Business Analysis</li><li>Business Environment</li><li>Business Processes</li><li>Business Analysis Planning And Monitoring</li><li>Strategic Analysis And Product Scope</li><li>Solution Evaluation</li><li>Investigation Techniques</li><li>Ratio Analysis</li><li>Stakeholder Analysis And Management</li><li>Process Improvement With Gap Analysis</li><li>Documenting And Managing Requirements</li><li>Business Development And Succession Planning</li><li>Planning &amp; Forecasting Operations</li><li>Business Writing Skills</li></ul><p><strong>**Data Science &amp; Machine Learning with Python**</strong></p><ul><li>Course Overview &amp; Table Of Contents</li><li>Introduction To Machine Learning</li><li>System And Environment Preparation</li><li>Learn Basics Of Python - Assignment<br /><ul><li>Functions</li><li>Data Structures</li><li>NumPy Array</li><li>NumPy Data</li><li>NumPy Arithmetic</li><li>Learn Basics Of Matplotlib</li></ul></li><li>Learn Basics Of Pandas</li><li>Understanding The CSV Data File</li><li>Load And Read CSV Data File Using Python Standard Library<br /><ul><li>Using NumPy</li><li>Using Pandas</li></ul></li><li>Dataset Summary - Peek, Dimensions And Data Types<br /><ul><li>Class Distribution And Data Summary</li><li>Explaining Correlation</li><li>Explaining Skewness - Gaussian And Normal Curve</li></ul></li><li>Dataset Visualization - Using Histograms</li><li>Dataset Visualization - Using Density Plots</li><li>Dataset Visualization - Box And Whisker Plots</li><li>Multivariate Dataset Visualization - Correlation Plots</li><li>Multivariate Dataset Visualization - Scatter Plots</li><li>Data Preparation (Pre-Processing) - Introduction<br /><ul><li>Re-Scaling Data</li><li>Standardizing Data</li><li>Normalizing Data</li><li>Binarizing Data</li></ul></li><li>Feature Selection - Introduction<br /><ul><li>Uni-Variate Part</li><li>Recursive Feature Elimination</li><li>Principal Component Analysis (PCA)</li><li>Feature Importance</li></ul></li><li>Refresher Session - The Mechanism Of Re-Sampling, Training And Testing</li><li>Algorithm Evaluation Techniques - Introduction<br /><ul><li>Train And Test Set</li><li>K-Fold Cross Validation</li><li>Leave One Out Cross Validation</li><li>Repeated Random Test-Train Splits</li></ul></li><li>Algorithm Evaluation Metrics - Introduction<br /><ul><li>Classification Accuracy</li><li>Log Loss</li><li>Area Under ROC Curve</li><li>Confusion Matrix</li><li>Classification Report</li><li>Mean Absolute Error - Dataset Introduction</li><li>Mean Absolute Error</li><li>Mean Square Error</li><li>R Squared</li></ul></li><li>Classification Algorithm Spot Check - Logistic Regression<br /><ul><li>Linear Discriminant Analysis</li><li>K-Nearest Neighbors</li><li>Naive Bayes</li><li>CART</li><li>Support Vector Machines</li></ul></li><li>Regression Algorithm Spot Check - Linear Regression<br /><ul><li>Ridge Regression</li><li>Lasso Linear Regression</li><li>Elastic Net Regression</li><li>K-Nearest Neighbors</li><li>CART</li><li>Support Vector Machines (SVM)</li></ul></li><li>Compare Algorithms</li><li>Pipelines</li><li>Performance Improvement: Ensembles - Voting<br /><ul><li>Bagging</li><li>Boosting</li></ul></li><li>Performance Improvement: Parameter Tuning Using Grid Search</li><li>Performance Improvement: Parameter Tuning Using Random Search</li><li>Export, Save And Load Machine Learning Models : Pickle</li><li>Export, Save And Load Machine Learning Models : Joblib</li><li>Finalizing A Model - Introduction And Steps</li><li>Finalizing A Classification Model - The Pima Indian Diabetes Dataset</li><li>Quick Session: Imbalanced Data Set - Issue Overview And Steps</li><li>Iris Dataset : Finalizing Multi-Class Dataset</li><li>Finalizing A Regression Model - The Boston Housing Price Dataset</li><li>Real-Time Predictions: Using The Pima Indian Diabetes Classification Model</li><li>Real-Time Predictions: Using Iris Flowers Multi-Class Classification Dataset</li><li>Real-Time Predictions: Using The Boston Housing Regression Model</li></ul><p><strong>**R Programming for Data Science**</strong></p><ul><li>Data Science Overview</li><li>R And RStudio</li><li>Introduction To Basics</li><li>Vectors</li><li>Matrices</li><li>Factors</li><li>Data Frames</li><li>Lists</li><li>Relational Operators</li><li>Logical Operators</li><li>Conditional Statements</li><li>Loops</li><li>Functions</li><li>R Packages</li><li>The Apply Family - Lapply</li><li>The Apply Family - Sapply &amp; Vapply</li><li>Useful Functions</li><li>Regular Expressions</li><li>Dates And Times</li><li>Getting And Cleaning Data</li><li>Plotting Data In R</li><li>Data Manipulation With Dplyr</li></ul><p><strong>**Learn Python, JavaScript, and Microsoft SQL for Data science**</strong></p><ul><li>JavaScript Introduction</li><li>JavaScript Basics</li><li>JavaScript Operators</li><li>JavaScript Conditional Statements</li><li>JavaScript Control Flow Statements</li><li>JavaScript Functions</li><li>JavaScript Error Handling</li><li>JavaScript Client-Side Validations</li><li>Python Introduction</li><li>Python Basic</li><li>Python Strings</li><li>Python Operators</li><li>Python Data Structures</li><li>Python Conditional Statements</li><li>Python Control Flow Statements</li><li>Python Core Games</li><li>Python Functions</li><li>Python Args, KW Args For Data Science</li><li>Python Project</li><li>Python Object Oriented Programming [OOPs]</li><li>Python Methods</li><li>Python Class And Objects</li><li>Python Inheritance And Polymorphism</li><li>Python Encapsulation And Abstraction</li><li>Python OOPs Games</li><li>Python Modules And Packages</li><li>Python Error Handling</li><li>Microsoft SQL[MS] Introduction</li><li>MS SQL Statements</li><li>MS SQL Filtering Data</li><li>MS SQL Functions</li><li>MS SQL Joins</li><li>MS SQL Advanced Commands</li><li>MS SQL Structure And Keys</li><li>MS SQL Queries</li><li>MS SQL Structure Queries</li><li>MS SQL Constraints</li><li>MS SQL Backup And Restore</li></ul><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        270 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><strong>Data Analysis course is ideal for:</strong></p><ul><li>Professionals working in fields such as finance, business, and healthcare who need to analyse data and make decisions based on their findings.</li><li>Students and researchers who want to develop their skills in data analysis and visualisation using Excel.</li><li>Individuals who are looking to pursue a career in data analysis and want to gain a foundational understanding of Excel and its capabilities.</li><li>Business owners and entrepreneurs who want to learn how to use Excel to analyse and interpret data for their own businesses.</li><li>Anyone who wants to improve their data analysis skills for personal or professional purposes and gain proficiency in Excel as a tool for data analysis.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>There are no specific prerequisites to enrol in Data analysis course. <strong>Anyone and everyone</strong> can take this course.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>The course will assist you in establishing a solid understanding of data analysis. After the course, you will be able to explore career options such as:</p><ul><li><strong>Data Analyst </strong>(Average annual salary £35,000)</li><li><strong>Research Analyst</strong> (Average annual salary £28,552)</li><li><strong>Business Analyst</strong> (Average annual salary £42,618)</li><li><strong>Risk Analyst </strong>(Average annual salary £41,340)</li><li><strong>Financial Analyst</strong> (Average annual salary £50,300)</li></ul>
                        </div>

One Education

Data Analyst : Data Analyst Course

<p>Tired of lost profits and missed opportunities? Imagine deciphering customer behaviour like a master codebreaker, predicting trends with laser accuracy, and turning data into a goldmine for your sales. Data Modelling empowers you to do just that.</p><p>UK retail alone saw a staggering £18 billion lost to poor data analysis in 2022. But the flip side? Companies embracing data-driven strategies saw a 6% average revenue boost. It's no longer a "nice-to-have" - it's the difference between thriving and surviving in today's dynamic market.</p><p>Stop guessing and start knowing. This Data Modelling course equips you with the skills to transform raw data into actionable insights. Learn to build powerful models, uncover hidden patterns, and forecast future sales with confidence. Take control of your sales destiny - enrol now and unlock the power of data.</p><p><strong>Learning Outcomes:</strong></p><ul><li>Execute robust Data Analysis using Excel for insightful decision-making.</li><li>Develop and administer MySQL databases for efficient data management.</li><li>Create impactful visualisations with Tableau for effective data communication.</li><li>Master Python and R for cutting-edge Data Science and Machine Learning.</li><li>Harness the power of Google BigQuery &amp; Cloud for scalable data engineering solutions.</li></ul><p>Embark on a transformative journey through the world of data, from fundamental analysis to advanced engineering. This diploma encompasses Data Analysis, Modelling, and Database Development, providing a holistic approach to data mastery. Dive into the intricacies of R Programming, Statistics, and Google Cloud, equipping yourself with skills that are highly sought after in today's data-driven landscape. Enroll now to stay ahead in the dynamic field of data!</p><p>This CPDQS Accredited Data Modelling Made Easy Bundle consists of these following 11 courses:</p><ul><li>Diploma in Data Analysis Fundamentals</li><li>Data Analysis In Excel</li><li>Data Entry Administrator Training</li><li>Diploma in Data Analytics with Tableau</li><li>MySQL Database Development</li><li>Data Science &amp; Machine Learning with Python</li><li>Business Data Analysis</li><li>Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li>R Programming for Data Science</li><li>Easy to Advanced Data Structures</li><li>Data Engineering with Google BigQuery &amp; Google Cloud</li></ul><p><strong>Certification</strong><br />Once you have finished the course, you will be eligible to apply for a CPD QS accredited certificate as proof of your new skills and your continued professional development. Certificates are available as PDF for £9, or you can request a hard copy to be sent in the post for £15.<br /></p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        35 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>Ideal for aspiring data analysts, professionals seeking career advancement, and tech enthusiasts.</p>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p> Open to all! No formal prerequisites. Embrace the world of data without barriers.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Analyst - £30,000 to £45,000</li><li>Database Developer - £35,000 to £50,000</li><li>Machine Learning Engineer - £45,000 to £70,000</li><li>Business Intelligence Analyst - £40,000 to £55,000</li><li>Data Engineer - £50,000 to £75,000</li></ul>
                        </div>

Data Modelling Made Easy - CPDQS Accredited Course

<p>Picture a world of endless possibilities; a realm where knowledge is power, and data reigns supreme. In today's digital age, the ability to decipher complex data sets and extract valuable insights has become an invaluable skill. With the Data Analysis with Data Science &amp; Machine Learning bundle, you're one step closer to harnessing the full potential of data and unlocking a brighter future.</p><p>The age of data is upon us, and the UK is no exception. As businesses and organisations increasingly rely on data to inform strategic decisions, professionals skilled in data analysis and machine learning are in high demand. By acquiring expertise in these fields, you'll not only enhance your career prospects but also contribute to the growth and success of the nation.</p><p>Don't miss out on this opportunity to take your career to the next level. Enrol in the Data Analysis with Data Science &amp; Machine Learning bundle today and unlock the power of data for your business.</p><p><strong>This Data Analysis with Data Science &amp; Machine Learning Bundle Consists of the following Premium courses: </strong></p><ul><li> Course 01: Introduction to Data Analysis</li><li> Course 02: Data Analytics with Tableau</li><li> Course 03: Complete Google Analytics Course</li><li> Course 04: Python for Data Analysis</li><li> Course 05: Quick Data Science Approach from Scratch</li><li> Course 06: R Programming for Data Science</li><li> Course 07: Learn MySQL from Scratch for Data Science and Analytics</li><li> Course 08: Master JavaScript with Data Visualization</li><li> Course 09: Excel Data Analysis</li><li> Course 10: Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li> Course 11: Root Cause Analysis</li><li> Course 12: Google Data Studio: Data Analytics</li><li> Course 13: Microsoft Excel: Automated Dashboard Using Advanced Formula, VBA, Power Query</li><li> Course 14: Business Intelligence and Data Mining Masterclass</li></ul><p>Learning Outcomes:</p><ul><li>Develop a solid understanding of data analysis techniques.</li><li>Learn how to collect, manage, and manipulate data effectively.</li><li>Gain knowledge in the programming languages commonly used in data analysis, such as Python and R.</li><li>Become proficient in data visualisation and presentation.</li><li>Develop an understanding of machine learning algorithms and their application in data analysis.</li><li>Learn how to use various data analysis software, including Tableau and Google Analytics.</li></ul><p>The Data Analysis with Data Science &amp; Machine Learning bundle includes a variety of courses aimed at providing theoretical knowledge in the field of data analysis. The bundle covers a wide range of topics, starting with the basics of data analysis such as data cleaning, exploration, and visualisation. With courses such as Introduction to Data Analysis, Data Analytics with Tableau, Complete Google Analytics Course, Python for Data Analysis, Quick Data Science Approach from Scratch, R Programming for Data Science, Learn MySQL from Scratch for Data Science and Analytics, and Master JavaScript with Data Visualization, learners can get a comprehensive understanding of data analysis concepts.</p><p>The course material is presented in a theoretical format to help learners gain a deep understanding of the topics. Learners can engage with the material at their own pace. The course content is presented in a way that is easy to understand, making it ideal for those who are new to the field of data analysis.</p><p><strong>Course Curriculum: Data Analysis with Data Science &amp; Machine Learning</strong></p><ul><li>Module 01: Introduction</li><li>Module 02: Agenda and Principles of Process Management</li><li>Module 03: The Voice of the Process</li><li>Module 04: Working as One Team for Improvement</li><li>Module 05: Exercise: The Voice of the Customer</li><li>Module 06: Tools for Data Analysis</li><li>Module 07: The Pareto Chart</li><li>Module 08: The Histogram</li><li>Module 09: The Run Chart</li><li>Module 10: Exercise: Presenting Performance Data</li><li>Module 11: Understanding Variation</li><li>Module 12: The Control Chart</li><li>Module 13: Control Chart Example</li><li>Module 14: Control Chart Special Cases</li><li>Module 15: Interpreting the Control Chart</li><li>Module 16: Control Chart Exercise</li><li>Module 17: Strategies to Deal with Variation</li><li>Module 18: Using Data to Drive Improvement</li><li>Module 19: A Structure for Performance Measurement</li><li>Module 20: Data Analysis Exercise</li><li>Module 21: Course Project</li><li>Module 22: Test your Understanding</li></ul><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        140 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>Professionals seeking to upskill and enhance their data analysis knowledge and abilities.</li><li>Individuals interested in pursuing a career in data analysis, data science or machine learning.</li><li>Business owners or entrepreneurs looking to gain insights into their data and make data-driven decisions.</li><li>Students or recent graduates seeking to gain valuable experience and knowledge in data analysis.</li><li>Anyone looking to expand their knowledge and understanding of data analysis and its useful applications.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>This Data Analysis with Data Science &amp; Machine Learning course has been designed to be fully compatible with tablets and smartphones.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Analyst: £24k-£42k per annum.</li><li>Business Intelligence Analyst: £25k-£60k per annum.</li><li>Data Scientist: £27k-£65k per annum.</li><li>Machine Learning Engineer: £28k-£80k per annum.</li><li>Business Analyst: £24k-£52k per annum.</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>Certificate of completion</h4>
        <p>
            Hard copy certificate -
            £10
        </p>
            <div> <p>You will get the Hard Copy certificate for the <strong>Data Analysis with Data Science &amp; Machine Learning</strong> course absolutely Free! Other Hard Copy certificates are available for £10 each.</p><p><strong>Please Note:</strong> The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.</p> </div>

                        </div>

Apex Learning

Data Analysis with Data Science & Machine Learning

<p>Feeling Stuck in Your Career? The Data Analyst (Data Analytics) Bundle is Your Skill-Building Solution. This exceptional collection of <strong>30 premium courses</strong> is designed to encourage growth and improve your career opportunities. Suited to meet different interests and goals, the Data Analyst-(Data Analytics) bundle provides an engaging learning experience, helping you learn skills across various disciplines.</p><p>With the Data Analyst (Data Analytics) Bundle, you'll have a personalised journey that aligns with your career goals and interests. This comprehensive package helps you confidently tackle new challenges, whether entering a new field or enhancing your existing knowledge. The Data Analyst-(Data Analytics) bundle is your gateway to expanding your career options, increasing job demand, and enhancing your skill set.</p><p>By enrolling in this bundle, you'll receive complimentary PDF certificates for all courses, adding value to your resume at no extra cost. Develop key skills and achieve important progress in your career and personal development. Start your journey today and experience the transformative impact of the Data Analyst-(Data Analytics) bundle on your job life and career growth!</p><p><strong>This Data Analyst (Data Analytics) </strong><strong>Bundle Comprises the Following CPD Accredited Courses:</strong></p><ul><li><strong>Course 01</strong>: Basic Data Analysis</li><li><strong>Course 02</strong>: Business Data Analysis</li><li><strong>Course 03</strong>: Introduction to Data Analytics with Tableau</li><li><strong>Course 04</strong>: Google Data Studio: Data Analytics</li><li><strong>Course 05</strong>: SQL Database Basics for Everyone</li><li><strong>Course 06</strong>: R Programming for Data Science</li><li><strong>Course 07</strong>: 2021 Data Science &amp; Machine Learning with R from A-Z</li><li><strong>Course 08</strong>: Learn Python, JavaScript, and Microsoft SQL for Data Science</li><li><strong>Course 09</strong>: Spatial Data Visualisation and Machine Learning in Python</li><li><strong>Course 10</strong>: Building Big Data Pipelines with PySpark MongoDB and Bokeh</li><li><strong>Course 11</strong>: Complete Python Machine Learning &amp; Data Science Fundamentals</li><li><strong>Course 12</strong>: Clinical Data Management with SAS Programming</li><li><strong>Course 13</strong>: Certificate in Data Entry and Management</li><li><strong>Course 14</strong>: Quick Data Science Approach from Scratch</li><li><strong>Course 15</strong>: Web Mapping and Data Visualizations</li><li><strong>Course 16</strong>: Programming AutoCAD with SQL Server Database Using C#</li><li><strong>Course 17</strong>: Big Data Analytics with PySpark Power BI and MongoDB</li><li><strong>Course 18</strong>: Develop Big Data Pipelines with R &amp; Sparklyr &amp; Tableau</li><li><strong>Course 19</strong>: Develop Big Data Pipelines with R, Sparklyr &amp; Power BI</li><li><strong>Course 20</strong>: Data Center Training Essentials: Power &amp; Electrical</li><li><strong>Course 21</strong>: Business Intelligence and Data Mining</li><li><strong>Course 22</strong>: Set Menu Prices for your restaurant using data</li><li><strong>Course 23</strong>: Data Analysis In Excel</li><li><strong>Course 24</strong>: Data Protection</li><li><strong>Course 25</strong>: Reporting and Data</li><li><strong>Course 26</strong>: Career Development Plan Fundamentals</li><li><strong>Course 27</strong>: CV Writing and Job Searching</li><li><strong>Course 28</strong>: Learn to Level Up Your Leadership</li><li><strong>Course 29</strong>: Networking Skills for Personal Success</li><li><strong>Course 30</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 Analyst (Data Analytics) Bundle, you will gain the following:</p><ul><li>CPD QS Accredited Proficiency with this Data Analyst-(Data Analytics) bundle</li><li>After successfully completing the Data Analyst-(Data Analytics) 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 Analyst-(Data Analytics) bundle</li><li>The online test with immediate results</li><li>You can study and complete the Data Analyst-(Data Analytics) bundle at your own pace.</li><li>Study for the Data Analyst-(Data Analytics) bundle using any internet-connected device, such as a computer, tablet, or mobile device.</li></ul><p>The Data Analyst (Data Analytics) bundle is a premier learning resource, with each course module holding respected CPD accreditation, symbolising exceptional quality. The content is packed with knowledge and is regularly updated to ensure it remains relevant. This bundle offers not just education but a constantly improving learning experience designed to enrich both your personal and professional development.</p><p>Advance the future of learning with the Data Analyst-(Data Analytics) <strong>bundle</strong>, a comprehensive, complete collection of 30 courses. Each course in the Data Analyst-(Data Analytics) bundle has been handpicked by our experts to provide a broad range of learning opportunities. Together, these modules form an important and well-rounded learning experience.</p><p>Our mission is to deliver high-quality, accessible education for everyone. Whether you are starting your career, switching industries, or enhancing your professional skills, the Data Analyst-(Data Analytics) bundle offers the flexibility and convenience to learn at your own pace. Make the Data Analyst-(Data Analytics) package your trusted partner in your lifelong learning journey.</p><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        300 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 Data Analyst (Data Analytics) bundle is perfect for:</p><ul><li>Expand your knowledge and skillset for a fulfilling career with the Data Analyst-(Data Analytics) bundle.</li><li>Become a more valuable professional by earning CPD certification and mastering in-demand skills with the Data Analyst-(Data Analytics) bundle.</li><li>Discover your passion or explore new career options with the diverse learning opportunities in the Data Analyst-(Data Analytics) bundle.</li><li>Learn on your schedule, in the comfort of your home - the Data Analyst-(Data Analytics) bundle offers ultimate flexibility for busy individuals.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>You are warmly invited to register for this 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>Gain a wide range of skills across various fields, improve your problem-solving capabilities, and keep current with industry trends. Perfect for those aiming for career advancement, exploring a new professional direction, or pursuing personal growth. Begin your journey with the Data Analyst (Data Analytics) bundle.</p>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

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

                        </div>

Data Analyst (Data Analytics) - 30 CPD Courses!

<p fr-original-style="" id="isPasted" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Data dashboards provide key information to stakeholders so that they can make informed decisions. While there are plenty of software solutions for building these essential data products, there is much less guidance on how to design dashboards to meet the diverse needs of users.&nbsp;</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">This course is for anyone who is building or implementing dashboards, and wants to know more about design principles and best practice. You could be using business intelligence software (such as Power BI or Tableau), or implementing bespoke solutions.&nbsp;</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">The course will give your team the ability to evaluate user needs and levels of understanding, make informed decisions about chart selections, and make effective use of interactivity dynamic data.&nbsp;</p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">We&rsquo;ll work with you before the course to ensure that we understand your organisation and what you&rsquo;re hoping to achieve.&nbsp;<br fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span fr-original-style="font-size: 18px;" style="font-size: 18px; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Sample learning content&nbsp;</strong></span></p><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;">Session 1: Data with a purpose</strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Understanding the different types of dashboard.</li><li fr-original-style="" style="box-sizing: border-box;">Information overload and other common dashboard pitfalls. &nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Assessing user needs and levels of data fluency.</li></ul><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;">Session 2: Planning a dashboard</strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Assessing diverse user needs and levels of data fluency.</li><li fr-original-style="" style="box-sizing: border-box;">Taking a User Experience (UX) approach to design and navigation.</li><li fr-original-style="" style="box-sizing: border-box;">Applying an interative and collaborative approach to onboarding.&nbsp;</li></ul><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;">Session 3: Graphs, charts and dials&nbsp;</strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Understanding how graphical perception informs chart choices.</li><li fr-original-style="" style="box-sizing: border-box;">Making intelligent design choices to help users explore.&nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Design principles for layout and navigation.&nbsp;</li></ul><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;">Session 4: Using interactivity&nbsp;</strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li fr-original-style="" style="box-sizing: border-box;">Making effective use of filters to slice and dice data sets.&nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Using layers of information to enable drilldown data exploration.&nbsp;</li><li fr-original-style="" style="box-sizing: border-box;">Complenting dashboards with automated alerts and queries.&nbsp;<br fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></li></ul><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span fr-original-style="font-size: 18px;" style="font-size: 18px; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Delivery</strong></span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">We deliver our courses over Zoom, to maximise flexibility. The training can be delivered in a single day, or across multiple sessions. All of our courses are live and interactive &ndash; every session includes a mix of formal tuition and hands-on exercises.&nbsp;<span fr-original-style="color: rgb(0, 0, 0);" id="isPasted" style="color: rgb(0, 0, 0); box-sizing: border-box;">To ensure this is possible, the number of attendees is capped at 16 people.&nbsp;<br fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span fr-original-style="font-size: 18px;" style="font-size: 18px; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Tutor</strong></span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Alan Rutter is the founder of Fire Plus Algebra. He is a specialist in communicating complex subjects through data visualisation, writing and design. He teaches for General Assembly and runs in-house training for public sector clients including the Home Office, the Department of Transport, the Biotechnology and Biological Sciences Research Council, the Health Foundation, and numerous local government and emergency services teams. He previously worked with Guardian Masterclasses on curating and delivering new course strands, including developing and teaching their B2B data visualisation courses. He oversaw the iPad edition launches of Wired, GQ, Vanity Fair and Vogue in the UK, and has worked with Cond&eacute; Nast International as product owner on a bespoke digital asset management system for their 11 global markets.<br fr-original-style="" style="box-sizing: border-box;"><br fr-original-style="" style="box-sizing: border-box;"></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><span fr-original-style="font-size: 18px;" style="font-size: 18px; box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Testimonial</strong></span></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">&ldquo;Alan was great to work with, he took us through the concepts behind data visualisation which means our team is now equipped for the future. He has a wide range of experience across the topic that is delivered in a clear, concise and friendly manner. We look forward to working with Alan again in the future.&rdquo;<br fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><em fr-original-style="" style="box-sizing: border-box;">John Masterson | Chief Product Officer | ImproveWell</em></strong></p>

Fire Plus Algebra

Data Visualization

Data Storytelling

Data Analysis

Dashboard design

<p><strong>Data analysis</strong> is a crucial skill in today's data-driven world, and the demand for skilled data analysts in the UK is on the rise. According to the Office for National Statistics (ONS), the UK's digital economy grew by <strong>7.9% in this year</strong>, creating numerous job opportunities in fields such as data analysis.</p><p>In Data Analysis in Excel with Analytics for Data Analysts course, you will get to learn the fundamentals of Excel data analysis. The highly informative modules will help you enhance your understanding of charts, pivot tables, pivot charts and more. You will acquire the expertise to work with multiple workbooks and worksheets. In this step-by-step learning process, you will get to grasp a better understanding of lookup functions. In addition, you will know the essentials of data forecasting, mapping data and formula auditing.</p><p>At the end of the data analysis course, you can receive QLS endorsed certificate of achievement. This certificate will allow you to enhance your resume and lift your employability. Enrol now!</p><p><strong>Dis Diploma Included Courses are: </strong></p><ul><li><strong>Course 01: Diploma in Data Analytics with Tableau<br /></strong></li><li><strong>Course 02: Data Analytics<br /></strong></li><li><strong>Course 03: Google Data Studio: Data Analytics</strong><strong><br /></strong></li><li><strong>Course 04: Big Data Analytics with PySpark Tableau Desktop and MongoDB<br /></strong></li><li><strong>Course 05: Learn MySQL from Scratch for Data Science and Analytics</strong><strong><br /></strong></li><li><strong>Course 06: Data Analysis In Excel<br /></strong></li><li><strong>Course 07: Diploma in Data Analysis Fundamentals<br /></strong></li><li><strong>Course 08: Business Data Analysis<br /></strong></li><li><strong>Course 09: Data Science &amp; Machine Learning with Python<br /></strong></li><li><strong>Course 10: R Programming for Data Science<br /></strong></li><li><strong>Course 11: Learn Python, JavaScript, and Microsoft SQL for Data science</strong></li></ul><p><strong>Key Learnings:</strong></p><ul><li>Ability to effectively modify and organize data within a worksheet using various formatting tools.</li><li>Proficiency in working with lists and using data analysis techniques such as sorting, filtering, and subtotalling.</li><li>Competency in analysing data through the use of functions, such as statistical and mathematical functions, to derive meaningful insights.</li><li>Proficiency in creating visually appealing charts and graphs to effectively communicate data insights.</li><li>Competency in using PivotTables and PivotCharts to efficiently summarize and analyse large sets of data.</li><li>Proficiency in automating data analysis tasks and functions through the use of macros and other automated workbook functionalities.</li></ul><p><strong>Course Significant Points:</strong></p><ul><li>Quality Licence Scheme Endorsed</li><li>CPD Accredited Course</li><li>Unlimited Retake Exam &amp; Tutor Support</li><li>Easy Accessibility to the Course Materials</li><li>100% Learning Satisfaction Guarantee</li><li>Lifetime Access &amp; 24/7 Support</li><li>Self-paced online course Modules</li><li>Covers to Explore Multiple Job Positions</li></ul><p><strong>How is the course assessed?</strong></p><p>To assess your learning, you have to complete the assignment questions provided at the end of the course. You have to score at least 60% to pass the exam and to qualify for Quality Licence Scheme endorsed and CPD-accredited certificates. After passing the assignment exam, you will be able to apply for a certificate.</p><p><strong>Meet the Endorsement</strong></p><p>The Quality Licence Scheme has been designed specifically to recognise high-quality courses. This Data Analysis with Excel course materials are recognised by Quality Licence Scheme (QLS). This ensures the deep research and quality resource allocation behind the development phase of the course. In addition, the QLS certificate enriches your CV and recognises your quality study on the relevant subject.</p><p><strong>How will QLS boost your worth?</strong></p><ul><li>Achieving <strong>Quality Licence Scheme</strong> endorsed certificates can provide you with valued and credible evidence of <strong>your skills and knowledge to potential employers. </strong></li><li>Quality Licence Scheme (QLS) endorsements are awarded to training programmes and courses that <strong>meet high quality standards</strong>, ensuring that your certificate represents <strong>a valuable achievement.</strong></li><li>The stringent assessment process involved in achieving Quality Licence Scheme Endorsed Certificates ensures that you have acquired the <strong>necessary skills and knowledge to excel in your chosen field.</strong></li></ul><p><strong>Meet the Accreditation</strong></p><p>CPD Quality Standards (CPD QS) accreditation assures the Data Analysis with Excel course training and learning activities are relevant, reliable, and up to date.</p><p><strong>How Will CPD Accredited Value You?</strong></p><ul><li>CPD accreditation ensures that the training programme or course you have completed has been <strong>independently reviewed</strong> and meets <strong>rigorous quality standards.</strong></li><li>By achieving CPD accredited certificates, you can <strong>enhance your career prospects</strong>, build your <strong>professional reputation</strong>, and stay competitive in <strong>today's job market.</strong></li></ul><p><strong>**Diploma in Data Analytics with Tableau**</strong></p><ul><li>Introduction To The Course</li><li>Project 1: Discount Mart (Sales And Profit Analytics)</li><li>Project 2: Green Destinations (HR Analytics)</li><li>Project 3: Superstore (Sales Agent Tracker)</li><li>Northwind Trade (Shipping Analytics)</li><li>Project 5: Tesla (Stock Price Analytics)</li><li>Bonus: Introduction To Database Concepts</li><li>Tableau Stories</li></ul><p><strong>**Data Analytics**</strong></p><ul><li>Introduction To The World Of Data</li><li>Basics Of Data Analytics</li><li>Statistics For Data Analytics</li><li>Actions Taken In The Data Analysis Process</li><li>Gathering The Right Information</li><li>Storing Data</li><li>Data Mining</li><li>Excel For Data Analytics</li><li>Tools For Data Analytics</li><li>Data-Analytic Thinking</li><li>Data Visualisation That Clearly Describes Insights</li><li>Data Visualisation Tools</li></ul><p><strong>**Google Data Studio: Data Analytics**</strong></p><ul><li>Introduction</li><li>Google Sheets</li><li>Google Data Studio</li></ul><p><strong>**Big Data Analytics with PySpark Tableau Desktop and MongoDB**</strong></p><ul><li>Introduction</li><li>Setup And Installations</li><li>Data Processing With PySpark And MongoDB</li><li>Machine Learning With PySpark And MLlib</li><li>Creating The Data Pipeline Scripts</li><li>Tableau Data Visualization</li><li>Source Code</li></ul><p><strong>**Learn MySQL from Scratch for Data Science and Analytics**</strong></p><ul><li>Getting Started</li><li>SQL Server Setting Up</li><li>SQL Database Basics</li><li>SQL DML (Data Manipulation Language)</li><li>SQL DDL (Data Definition Language)</li><li>SQL DCL (Data Control Language)</li><li>SQL Statement Basic</li><li>Filtering Data Rows</li><li>Aggregate Functions For Data Analysis</li><li>SQL Data Analyticstatements</li><li>SQL Group By Statement</li><li>JOINS</li><li>SQL Constraints</li><li>Views</li><li>Advanced SQL Functions</li><li>SQL Stored Procedures</li><li>Import &amp; Export Data</li><li>Backup And Restore Database</li></ul><p><strong>**Data Analysis In Excel**</strong></p><ul><li>Modifying A Worksheet</li><li>Working With Lists</li><li>Analyzing Data</li><li>Visualizing Data With Charts</li><li>Using PivotTables And PivotCharts</li><li>Working With Multiple Worksheets And Workbooks</li><li>Using Lookup Functions And Formula Auditing</li><li>Automating Workbook Functionality</li><li>Creating Sparklines And Mapping Data</li><li>Forecasting Data</li></ul><p><strong>**Diploma in Data Analysis Fundamentals**</strong></p><ul><li>Introduction</li><li>Agenda And Principles Of Process Management</li><li>The Voice Of The Process</li><li>Working As One Team For Improvement</li><li>Exercise: The Voice Of The Customer</li><li>Tools For Data Analysis</li><li>The Pareto Chart</li><li>The Histogram</li><li>The Run Chart</li><li>Exercise: Presenting Performance Data</li><li>Understanding Variation</li><li>The Control Chart</li><li>Control Chart Example</li><li>Control Chart Special Cases</li><li>Interpreting The Control Chart</li><li>Control Chart Exercise</li><li>Strategies To Deal With Variation</li><li>Using Data To Drive Improvement</li><li>A Structure For Performance Measurement</li><li>Data Analysis Exercise</li><li>Course Project</li><li>Test Your Understanding</li></ul><p><strong>**Business Data Analysis**</strong></p><ul><li>Introduction To Business Analysis</li><li>Business Environment</li><li>Business Processes</li><li>Business Analysis Planning And Monitoring</li><li>Strategic Analysis And Product Scope</li><li>Solution Evaluation</li><li>Investigation Techniques</li><li>Ratio Analysis</li><li>Stakeholder Analysis And Management</li><li>Process Improvement With Gap Analysis</li><li>Documenting And Managing Requirements</li><li>Business Development And Succession Planning</li><li>Planning &amp; Forecasting Operations</li><li>Business Writing Skills</li></ul><p><strong>**Data Science &amp; Machine Learning with Python**</strong></p><ul><li>Course Overview &amp; Table Of Contents</li><li>Introduction To Machine Learning</li><li>System And Environment Preparation</li><li>Learn Basics Of Python - Assignment</li><li>Learn Basics Of Python - Functions</li><li>Learn Basics Of Python - Data Structures</li><li>Learn Basics Of NumPy - NumPy Array</li><li>Learn Basics Of NumPy - NumPy Data</li><li>Learn Basics Of NumPy - NumPy Arithmetic</li><li>Learn Basics Of Matplotlib</li><li>Learn Basics Of Pandas</li><li>Understanding The CSV Data File</li><li>Load And Read CSV Data File Using Python Standard Library</li><li>Load And Read CSV Data File Using NumPy</li><li>Load And Read CSV Data File Using Pandas</li><li>Dataset Summary - Peek, Dimensions And Data Types</li><li>Dataset Summary - Class Distribution And Data Summary</li><li>Dataset Summary - Explaining Correlation</li><li>Dataset Summary - Explaining Skewness - Gaussian And Normal Curve</li><li>Dataset Visualization - Using Histograms</li><li>Dataset Visualization - Using Density Plots</li><li>Dataset Visualization - Box And Whisker Plots</li><li>Multivariate Dataset Visualization - Correlation Plots</li><li>Multivariate Dataset Visualization - Scatter Plots</li><li>Data Preparation (Pre-Processing) - Introduction<br /><ul><li>Re-Scaling Data</li><li>Standardizing Data</li><li>Normalizing Data</li><li>Binarizing Data</li></ul></li><li>Feature Selection - Introduction<br /><ul><li>Uni-Variate Part</li><li>Recursive Feature Elimination</li><li>Principal Component Analysis (PCA)</li><li>Feature Importance</li></ul></li><li>Refresher Session - The Mechanism Of Re-Sampling, Training And Testing</li><li>Algorithm Evaluation Techniques - Introduction<br /><ul><li>Train And Test Set</li><li>K-Fold Cross Validation</li><li>Leave One Out Cross Validation</li><li>Repeated Random Test-Train Splits</li></ul></li><li>Algorithm Evaluation Metrics - Introduction<br /><ul><li>Classification Accuracy</li><li>Log Loss</li><li>Area Under ROC Curve</li><li>Confusion Matrix</li><li>Classification Report</li><li>Mean Absolute Error - Dataset Introduction</li><li>Mean Absolute Error</li><li>Mean Square Error</li><li>R Squared</li></ul></li><li>Classification Algorithm Spot Check - Logistic Regression<br /><ul><li>Linear Discriminant Analysis</li><li>K-Nearest Neighbors</li><li>Naive Bayes</li><li>CART</li><li>Support Vector Machines</li></ul></li><li>Regression Algorithm Spot Check - Linear Regression<br /><ul><li>Ridge Regression</li><li>Lasso Linear Regression</li><li>Elastic Net Regression</li><li>K-Nearest Neighbors</li><li>CART</li><li>Support Vector Machines (SVM)</li></ul></li><li>Compare Algorithms</li><li>Pipelines</li><li>Performance Improvement: Ensembles - Voting<br /><ul><li>Bagging</li><li>Boosting</li></ul></li><li>Performance Improvement: Parameter Tuning Using Grid Search</li><li>Performance Improvement: Parameter Tuning Using Random Search</li><li>Export, Save And Load Machine Learning Models : Pickle</li><li>Export, Save And Load Machine Learning Models : Joblib</li><li>Finalizing A Model - Introduction And Steps</li><li>Finalizing A Classification Model - The Pima Indian Diabetes Dataset</li><li>Quick Session: Imbalanced Data Set - Issue Overview And Steps</li><li>Iris Dataset : Finalizing Multi-Class Dataset</li><li>Finalizing A Regression Model - The Boston Housing Price Dataset</li><li>Real-Time Predictions: Using The Pima Indian Diabetes Classification Model</li><li>Real-Time Predictions: Using Iris Flowers Multi-Class Classification Dataset</li><li>Real-Time Predictions: Using The Boston Housing Regression Model</li></ul><p><strong>**R Programming for Data Science**</strong></p><ul><li>Data Science Overview</li><li>R And RStudio</li><li>Introduction To Basics</li><li>Vectors</li><li>Matrices</li><li>Factors</li><li>Data Frames</li><li>Lists</li><li>Relational Operators</li><li>Logical Operators</li><li>Conditional Statements</li><li>Loops</li><li>Functions</li><li>R Packages</li><li>The Apply Family - Lapply</li><li>The Apply Family - Sapply &amp; Vapply</li><li>Useful Functions</li><li>Regular Expressions</li><li>Dates And Times</li><li>Getting And Cleaning Data</li><li>Plotting Data In R</li><li>Data Manipulation With Dplyr</li></ul><p><strong>**Learn Python, JavaScript, and Microsoft SQL for Data science**</strong></p><ul><li>JavaScript Introduction</li><li>JavaScript Basics</li><li>JavaScript Operators</li><li>JavaScript Conditional Statements</li><li>JavaScript Control Flow Statements</li><li>JavaScript Functions</li><li>JavaScript Error Handling</li><li>JavaScript Client-Side Validations</li><li>Python Introduction</li><li>Python Basic</li><li>Python Strings</li><li>Python Operators</li><li>Python Data Structures</li><li>Python Conditional Statements</li><li>Python Control Flow Statements</li><li>Python Core Games</li><li>Python Functions</li><li>Python Args, KW Args For Data Science</li><li>Python Project</li><li>Python Object Oriented Programming [OOPs]</li><li>Python Methods</li><li>Python Class And Objects</li><li>Python Inheritance And Polymorphism</li><li>Python Encapsulation And Abstraction</li><li>Python OOPs Games</li><li>Python Modules And Packages</li><li>Python Error Handling</li><li>Microsoft SQL[MS] Introduction</li><li>MS SQL Statements</li><li>MS SQL Filtering Data</li><li>MS SQL Functions</li><li>MS SQL Joins</li><li>MS SQL Advanced Commands</li><li>MS SQL Structure And Keys</li><li>MS SQL Queries</li><li>MS SQL Structure Queries</li><li>MS SQL Constraints</li><li>MS SQL Backup And Restore</li></ul><h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        570 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><strong>Data Analysis course is ideal for: </strong></p><ul><li>Professionals working in fields such as finance, business, and healthcare who need to analyse data and make decisions based on their findings.</li><li>Students and researchers who want to develop their skills in data analysis and visualisation using Excel.</li><li>Individuals who are looking to pursue a career in data analysis and want to gain a foundational understanding of Excel and its capabilities.</li><li>Business owners and entrepreneurs who want to learn how to use Excel to analyse and interpret data for their own businesses.</li><li>Anyone who wants to improve their data analysis skills for personal or professional purposes and gain proficiency in Excel as a tool for data analysis.</li></ul>
                        </div><h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>There are no specific prerequisites to enrol in Data analysis course. <strong> Anyone and everyone</strong> can take this course.</p>
                        </div><h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <p>The course will assist you in establishing a solid understanding of data analysis. After the course, you will be able to explore career options such as:</p><ul><li><strong>Data Analyst </strong>(Average annual salary £35,000)</li><li><strong>Research Analyst</strong> (Average annual salary £28,552)</li><li><strong>Business Analyst</strong> (Average annual salary £42,618)</li><li><strong>Risk Analyst </strong>(Average annual salary £41,340)</li><li><strong>Financial Analyst</strong> (Average annual salary £50,300)</li></ul>
                        </div><h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>Certificate of completion (PDF)</h4>
        <p>
            Digital certificate -
            £9
        </p>
            <div> <p><strong>CPD Accredited PDF Certificate.</strong><br />A PDF Certificate: £9</p> </div>
        <h4>Certificate of completion (Hardcopy)</h4>
        <p>
            Hard copy certificate -
            £15
        </p>
            <div> <p><strong>CPD Accredited Hard Copy Certificate. </strong><br />A Hardcopy Certificate (within the UK): £15<br />A Hardcopy Certificate (international): £15 + £10 (postal charge) = £25</p> </div>
        <h4>Endorsed Certificate of Achievement from the Quality Licence Scheme (Hardcopy)</h4>
        <p>
            Hard copy certificate -
            £109
        </p>
            <div> <p>Data Analysis In Excel (within the UK: £109, International: £119)</p> </div>

                        </div>

Data Analyst : Data Analyst (Data Analytics) - Level 5 Diploma Course

<h3><b>Overview</b></h3><p> </p><p><span>With the ever-increasing demand for Tableau in personal &amp; professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Tableau may be.</span></p><p> </p><p><span>Learning about Tableau or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Tableau. That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Tableau is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates.</span></p><p> </p><p><span>The self-paced online learning methodology by Compete High in this Diploma in Data Analytics In Tableau course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course!</span></p><p> </p><p><span>Instead of searching for hours, enrol right away on this Diploma in Data Analytics In Tableau course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run.</span></p><p> </p><h3><b>Who is this course for?</b></h3><p> </p><p><span>While we refrain from discouraging anyone wanting to do this Diploma in Data Analytics In Tableau course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it:</span></p><ol><li><span>Anyone looking for the basics of Tableau,</span></li><li><span>Jobseekers in the relevant domains,</span></li><li><span>Anyone with a ground knowledge/intermediate expertise in Tableau,</span></li><li><span>Anyone looking for a certificate of completion on doing an online training on this topic,</span></li><li><span>Students of Tableau, or anyone with an academic knowledge gap to bridge,</span></li><li><span>Anyone with a general interest/curiosity</span></li></ol><p> </p><h3><b>Career Path</b></h3><p> </p><p><span>This Diploma in Data Analytics In Tableau course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams. </span></p><p> </p><div><div><div><h3>
Course Curriculum</h3><div><div><h4>
Module 01_ Data Analytics</h4><div><div><ul><li><div>
<span></span><h5>
Data Analytics</h5></div><div>
<span>
00:00													</span>
<span></span></div></li></ul></div></div></div><div><h4>
Module 02_ Why Use Tableau for Data Analytics</h4><div><div><ul><li><div>
<span></span><h5>
Why Use Tableau for Data Analytics</h5></div><div>
<span>
00:00													</span>
<span></span></div></li></ul></div></div></div><div><h4>
Module 03_ Getting Started With Tableau</h4><div><div><ul><li><div>
<span></span><h5>
Getting Started With Tableau</h5></div><div>
<span>
00:00													</span>
<span></span></div></li></ul></div></div></div><div><h4>
Module 04_ Tableau Data Source (TDS)</h4><div><div><ul><li><div>
<span></span><h5>
Tableau Data Source (TDS)</h5></div><div>
<span>
00:00													</span>
<span></span></div></li></ul></div></div></div><div><h4>
Module 05_ Tableau Worksheets</h4><div><div><ul><li><div>
<span></span><h5>
Tableau Worksheets</h5></div><div>
<span>
00:00													</span>
<span></span></div></li></ul></div></div></div><div><h4>
Module 06_ Tableau Calculations</h4><div><div><ul><li><div>
<span></span><h5>
Tableau Calculations</h5></div><div>
<span>
00:00													</span>
<span></span></div></li></ul></div></div></div><div><h4>
Module 07_ Tableau Sort _ Filters</h4><div><div><ul><li><div>
<span></span><h5>
Tableau Sort _ Filters</h5></div><div>
<span>
00:00													</span>
<span></span></div></li></ul></div></div></div><div><h4>
Module 08_ Tableau Charts</h4><div><div><ul><li><div>
<span></span><h5>
Tableau Charts</h5></div><div>
<span>
00:00													</span>
<span></span></div></li></ul></div></div></div><div><h4>
Module 09_ Tableau Advanced</h4><div><div><ul><li><div>
<span></span><h5>
Tableau Advanced</h5></div><div>
<span>
00:00													</span>
<span></span></div></li></ul></div></div></div></div></div></div></div>

Overview
 
With the ever-increasing demand for Tableau in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Tableau may be.
 
Learning about Tableau or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Tableau. That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Tableau is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates.
 
The self-paced online learning methodology by Compete High in this Diploma in Data Analytics In Tableau course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course!
 
Instead of searching for hours, enrol right away on this Diploma in Data Analytics In Tableau course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run.
 
Who is this course for?
 
While we refrain from discouraging anyone wanting to do this Diploma in Data Analytics In Tableau course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it:
Anyone looking for the basics of Tableau,
Jobseekers in the relevant domains,
Anyone with a ground knowledge/intermediate expertise in Tableau,
Anyone looking for a certificate of completion on doing an online training on this topic,
Students of Tableau, or anyone with an academic knowledge gap to bridge,
Anyone with a general interest/curiosity
 
Career Path
 
This Diploma in Data Analytics In Tableau course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams. 
 

Course Curriculum
Module 01_ Data Analytics
Data Analytics

00:00
Module 02_ Why Use Tableau for Data Analytics
Why Use Tableau for Data Analytics

00:00
Module 03_ Getting Started With Tableau
Getting Started With Tableau

00:00
Module 04_ Tableau Data Source (TDS)
Tableau Data Source (TDS)

00:00
Module 05_ Tableau Worksheets
Tableau Worksheets

00:00
Module 06_ Tableau Calculations
Tableau Calculations

00:00
Module 07_ Tableau Sort _ Filters
Tableau Sort _ Filters

00:00
Module 08_ Tableau Charts
Tableau Charts

00:00
Module 09_ Tableau Advanced
Tableau Advanced

00:00

Compete High

Tableau Desktop Specialist

Data Engineering

Diploma in Education & Training (DET)

Tableau

Trainers Course

Diploma in Data Analytics In Tableau

<p><strong></strong><strong> Our Aim Is Your Satisfaction! Offer Ends Soon; Hurry Up!! </strong><strong></strong></p><p><strong>Are you looking to improve your current abilities or make a career move? Our unique</strong><strong> Data Analytics with Tableau</strong><strong> course might help you get there! Expand your expertise with high-quality training - study the</strong><strong> Data Analytics with Tableau </strong><strong>course and get an expertly designed, great-value training experience. Learn from industry professionals and quickly equip yourself with the specific knowledge and skills you need to excel in your chosen career through the</strong><strong>online training course.</strong></p><p>The Data Analytics with Tableau course is broken down into several in-depth modules to provide you with the most convenient and rich learning experience possible. Upon successful completion of the Data Analytics with Tableau course, an instant e-certificate will be exhibited in your profile that you can order as proof of your skills and knowledge. Add these amazing new skills to your resume and boost your employability by simply enrolling in this course.</p><p>This Data Analytics with Tableau training can help you to accomplish your ambitions and prepare you for a meaningful career. So, join us today and gear up for excellence!</p><p><strong>Why Prefer Us? </strong></p><ul><li>Opportunity to earn a certificate accredited by <strong>CPDQS.</strong></li><li><strong>Get a free student ID </strong>card!(£10 postal charge will be applicable for international delivery)</li><li>Innovative and Engaging Content.</li><li>Free Assessments</li><li>24/7 Tutor Support.</li></ul> <p>Take a step toward a brighter future!</p><p><strong>*** Course Curriculum ***</strong></p><p>Here is the curriculum breakdown of the Data Analytics with Tableau course:</p><p><strong> Data Analytics with Tableau <br /></strong></p><ul><li>Module 01: Introduction to the Course</li><li>Module 02: Project 1: Discount Mart (Sales and Profit Analytics)</li><li>Module 03: Project 2: Green Destinations (HR Analytics)</li><li>Module 04: Project 3: Superstore (Sales Agent Tracker)</li><li>Module 05: Northwind Trade (Shipping Analytics)</li><li>Module 06: Project 5: Tesla (Stock Price Analytics)</li><li>Module 07: Bonus: Introduction to Database Concepts</li><li>Module 08: Tableau Stories</li></ul><p><strong>Assessment Process</strong></p><p>Once you have completed all the modules in the Data Analytics with Tableau course, you can assess your skills and knowledge with an optional assignment.</p><p><strong>Certificate of Completion</strong></p><p>The learners have to complete the assessment of this Data Analytics with Tableau course to achieve the <strong>CPDQS accredited certificate</strong>.</p><ul><li><strong>Digital Certificate: £10</strong></li><li><strong>Hard Copy Certificate: £29 (Inside UK)</strong></li><li><strong>Hard Copy Certificate: £39 (for international students)</strong></li></ul> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        150 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 Data Analytics with Tableau 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>

 Our Aim Is Your Satisfaction! Offer Ends Soon; Hurry Up!! 
Are you looking to improve your current abilities or make a career move? Our unique Data Analytics with Tableau course might help you get there! Expand your expertise with high-quality training - study the Data Analytics with Tableau course and get an expertly designed, great-value training experience. Learn from industry professionals and quickly equip yourself with the specific knowledge and skills you need to excel in your chosen career through theonline training course.
The Data Analytics with Tableau course is broken down into several in-depth modules to provide you with the most convenient and rich learning experience possible. Upon successful completion of the Data Analytics with Tableau course, an instant e-certificate will be exhibited in your profile that you can order as proof of your skills and knowledge. Add these amazing new skills to your resume and boost your employability by simply enrolling in this course.
This Data Analytics with Tableau training can help you to accomplish your ambitions and prepare you for a meaningful career. So, join us today and gear up for excellence!
Why Prefer Us? 
Opportunity to earn a certificate accredited by CPDQS.
Get a free student ID card!(£10 postal charge will be applicable for international delivery)
Innovative and Engaging Content.
Free Assessments
24/7 Tutor Support.
Take a step toward a brighter future!
*** Course Curriculum ***
Here is the curriculum breakdown of the Data Analytics with Tableau course:
 Data Analytics with Tableau 

Module 01: Introduction to the Course
Module 02: Project 1: Discount Mart (Sales and Profit Analytics)
Module 03: Project 2: Green Destinations (HR Analytics)
Module 04: Project 3: Superstore (Sales Agent Tracker)
Module 05: Northwind Trade (Shipping Analytics)
Module 06: Project 5: Tesla (Stock Price Analytics)
Module 07: Bonus: Introduction to Database Concepts
Module 08: Tableau Stories
Assessment Process
Once you have completed all the modules in the Data Analytics with Tableau course, you can assess your skills and knowledge with an optional assignment.
Certificate of Completion
The learners have to complete the assessment of this Data Analytics with Tableau course to achieve the CPDQS accredited certificate.
Digital Certificate: £10
Hard Copy Certificate: £29 (Inside UK)
Hard Copy Certificate: £39 (for international students)
 CPD 
150 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 Data Analytics with Tableau course. This course is open to everybody.
 Requirements 
You will not need any prior background or expertise to enrol in this course.
 Career path 
After completing this course, you are to start your career or begin the next phase of your career.

Data Analytics with Tableau

<div id="course-pills-1">Duration<p>2 Days</p><p>12 CPD hours</p>Overview<p>Identify and configure basic functions of Tableau.     Connect to data sources, import data into Tableau, and save Tableau files     Create views and customize data in visualizations.     Manage, sort, and group data.     Save and share data sources and workbooks.     Filter data in views.     Customize visualizations with annotations, highlights, and advanced features.     Create and enhance dashboards in Tableau.     Create and enhance stories in Tableau</p><p></p><p>As technology progresses and becomes more interwoven with our businesses and lives, more and more data is collected about business and personal activities. This era of "big data" has exploded due to the rise of cloud computing, which provides an abundance of computational power and storage, allowing organizations of all sorts to capture and store data. Leveraging that data effectively can provide timely insights and competitive advantage.</p>  <p>The creation of data-backed visualizations is a key way data scientists, or any professional, can explore, analyze, and report insights and trends from data. TableauÂ© software is designed for this purpose. Tableau was built to connect to a wide range of data sources and allows users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Tableau's data connection capabilities and visualization features go far beyond those that can be found in spreadsheets, allowing users to create compelling and interactive worksheets, dashboards, and stories that bring data to life and turn data into thoughtful action.</p><p></p>Prerequisites<p>To ensure your success in this course, you should have experience managing data with MicrosoftÂ© ExcelÂ© or Google Sheets?.</p></div><div id="course-pills-2"><h3>Lesson 1: Tableau Fundamentals</h3><ul>     <li>Topic A: Overview of Tableau</li>    <li>Topic B: Navigate and Configure Tableau</li></ul>  <h3>Lesson 2: Connecting to and Preparing Data</h3><ul>    <li>Topic A: Connect to Data</li>    <li>Topic B: Build a Data Model</li>    <li>Topic C: Save Workbook Files</li>    <li>Topic D: Prepare Data for Analysis</li></ul>  <h3>Lesson 3: Exploring Data</h3><ul>    <li>Topic A: Create Views</li>    <li>Topic B: Customize Data in Visualizations</li></ul>  <h3>Lesson 4: Managing, Sorting, and Grouping Data</h3><ul>    <li>Topic A: Adjust Fields</li>    <li>Topic B: Sort Data</li>    <li>Topic C: Group Data</li></ul>  <h3>Lesson 5: Saving, Publishing, and Sharing Data</h3><ul>    <li>Topic A: Save Data Sources</li>    <li>Topic B: Publish Data Sources and Visualizations</li>    <li>Topic C: Share Workbooks for Collaboration</li></ul>  <h3>Lesson 6: Filtering Data</h3><ul>    <li>Topic A: Configure Worksheet Filters</li>    <li>Topic B: Apply Advanced Filter Options</li>    <li>Topic C: Create Interactive Filters</li></ul>  <h3>Lesson 7: Customizing Visualizations</h3><ul>    <li>Topic A: Format and Annotate Views</li>    <li>Topic B: Emphasize Data in Visualizations</li>    <li>Topic C: Create Animated Workbooks</li>    <li>Topic D: Best Practices for Visual Design</li></ul>  <h3>Lesson 8: Creating Dashboards in Tableau</h3><ul>    <li>Topic A: Create Dashboards</li>    <li>Topic B: Enhance Dashboards with Actions</li>    <li>Topic C: Create Mobile Dashboards</li></ul>  <h3>Lesson 9: Creating Stories in Tableau</h3><ul>    <li>Topic A: Create Stories</li>    <li>Topic B: Enhance Stories with Tooltips</li></ul></div>

Nexus Human

Excel Analytics

Data Studio

Tableau Desktop - Part 1

<strong>Do you want to learn Tableau and crack the Tableau Certified Data Analyst Exam? Then this course is for you!

This course is designed for absolute beginners, and it is well equipped with detailed video tutorials, exam notes PDF, tips and tricks, and full practice tests in exam format along with solutions.</strong>
        <p>This course is designed considering the fact that you are an absolute beginner, and you will be taught even the most basic concepts in Tableau from scratch so that after completing this course, you will be able to create rich visualizations easily and confidently.

It will help you prepare for and clear your Tableau Certified Data Analyst Exam. In this course, you will find practice tests designed keeping the current exam format in mind; you will find similar kinds of questions in the exam. We will also show you how to solve the questions in a faster way and all the detailed solutions are provided for the hands-on questions.

This course starts with the basic concepts of Tableau to refresh your knowledge. Then, you will look at field and chart types, and how to organize and simplify data. You will then move on to execute calculations, mapping, and analytics. After that, dashboards and data connections will be covered.

Finally, you will be looking at some practice tests to reinforce your learning. The data analyst topics covered include data connections, organizing and simplifying data, field and chart types, calculations, mapping, analytics, and dashboards.

By the end of this course, you will be able to create rich visualizations easily and confidently, and you will be ready to ace your Tableau Certified Data Analyst Exam.

All the resource files are uploaded on the GitHub repository at: https://github.com/PacktPublishing/Learn-Tableau-Certified-Data-Analyst-Exam</p>
        <h2>What You Will Learn</h2><p>Learn basic concepts of Tableau to refresh your knowledge<br>Look at field and chart types along with organizing and simplifying data<br>Execute calculations, mapping, and analytics<br>Use dashboards and data connection<br>Manipulate string, date and arithmetic calculations, logic statements<br>Connect to spatial files and look at forecasting, trend lines, and model</p>
        <h2>Audience</h2><p>This course is ideal for anyone who wants to learn Tableau and an experienced individual working on Tableau can benefit from this course in order to pass the Tableau Certified Data Analyst Exam.<br>An individual with an attitude of willingness to learn is the basic requirement. Working knowledge of Tableau is a plus but not mandatory.</p>
        <h2>Approach</h2><p>A comprehensive hands-on guide with real-time exam-oriented examples. The exam pattern and structure are mapped explicitly with the actual exam so that the customer is accustomed to the exam. Practice tests with their solutions are also added in the later part of the course.</p>
        <h2>Key Features</h2><p>Learn Tableau from scratch to ace the Tableau Certified Data Analyst Exam * Study guide PDF and quizzes provided to revise and reinforce the concepts learned * Discover a dedicated section for the practice tests and their solutions</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Learn-Tableau-Certified-Data-Analyst-Exam</p>
        <h2>About the Author</h2><h3>Vivek P.</h3><p>Vivek P. is a Tableau Certified Associate with more than 12 years of IT experience with different technologies. He is enthusiastic about working with technology and strongly believes in hands-on learning. His teaching methodology is also driven by this belief.</p>
        <h2>Course Outline</h2><h4>1. Getting started with Tableau</h4><p></p><br><h4>2. Field & Chart Types</h4><p></p><br><h4>3. Organizing & Simplifying Data</h4><p></p><br><h4>4. Calculations</h4><p></p><br><h4>5. Mapping</h4><p></p><br><h4>6. Analytics</h4><p></p><br><h4>7. Dashboards</h4><p></p><br><h4>8. Data Connections</h4><p></p><br><h4>9. Exam Tips and Tricks</h4><p></p><br><h4>10. Practice Test 1</h4><p></p>

Packt

Do you want to learn Tableau and crack the Tableau Certified Data Analyst Exam? Then this course is for you!

This course is designed for absolute beginners, and it is well equipped with detailed video tutorials, exam notes PDF, tips and tricks, and full practice tests in exam format along with solutions.

Learn Tableau and Ace the Tableau Certified Data Analyst Exam

<strong>This course is designed for absolute beginners and explains even the most basic concepts in Tableau from scratch. By completing this course, you will be able to create rich visualizations easily and confidently and have the knowledge required to crack the Tableau Desktop Specialist Exam.</strong>
        <p>Do you want to learn Tableau and crack the Tableau Desktop Specialist Exam? Then this course is for you.

This course is designed considering that you are an absolute beginner; you will learn even the most fundamental concepts in Tableau so that after completing this course, you can create rich visualizations easily and confidently.

It will help you prepare for and clear your Tableau Desktop Specialist exam. In this course, you will find practice tests that are designed by keeping the current exam format in mind; you will find similar kinds of questions in the exam. We will also show you how to solve the questions faster and all the detailed solutions are provided for the hands-on questions.

In this course, we will cover the following Specialist topic areas: the four exam domains-Connecting to and Preparing Data, Exploring and Analyzing Data, Sharing Insights, and Understanding Tableau Concepts.

By the end of this course, you will be well-prepared for your Tableau Desktop Specialist Exam. All the best!

All the resources and practice tests for this course are available at:  https://github.com/PacktPublishing/Learn-Tableau-and-Ace-the-Tableau-Desktop-Specialist-Exam</p>
        <h2>What You Will Learn</h2><p>Learn Tableau concepts, create basic charts and histograms in Tableau<br>Combine data from various sources using Join, Blend, and Union<br>Optimize the data you use with Extracts and live connections<br>Discover ways to group data using hierarchies, groups, and sets<br>Improve your visualizations by adding reference and trend lines<br>Filter, sort, and apply table calculations to data in Tableau</p>
        <h2>Audience</h2><p>This course acts as preparatory material for the Tableau Desktop Specialist exam. No prior knowledge of Tableau is required for this course. It is also helpful for anyone who wants to learn how to visualize data using Tableau.<br><br>The course is updated with content changes as per the V2020.3 Tableau Desktop Specialist Exam.</p>
        <h2>Approach</h2><p>This course provides you with all the material required to ace the Tableau Specialist exam. Everything in a single course-detailed video tutorials, exam notes PDF, tips and tricks, quizzes, practice tests in exam format along with solutions.<br><br>The course has a dedicated section for exam tips and tricks.</p>
        <h2>Key Features</h2><p>Create stunning visualizations and build dashboards that help you easily access and compare data * Showcase information by providing context and narratives using the story feature * Real exam-like questions for practice with a detailed explanation of hands-on questions</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Learn-Tableau-and-Ace-the-Tableau-Desktop-Specialist-Exam</p>
        <h2>About the Author</h2><h3>Vivek P.</h3><p>Vivek P. is a Tableau Certified Associate with more than 12 years of IT experience with different technologies. He is enthusiastic about working with technology and strongly believes in hands-on learning. His teaching methodology is also driven by this belief.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><br><h4>2. Understanding Tableau Concepts</h4><p></p><br><h4>3. Exploring and Analyzing data</h4><p></p><br><h4>4. Sharing Insights</h4><p></p><br><h4>5. Connecting to & Preparing Data</h4><p></p><br><h4>6. Hands-On Quiz to test the Tableau knowledge</h4><p></p>

This course is designed for absolute beginners and explains even the most basic concepts in Tableau from scratch. By completing this course, you will be able to create rich visualizations easily and confidently and have the knowledge required to crack the Tableau Desktop Specialist Exam.

Learn Tableau and Ace the Tableau Desktop Specialist Exam

<div id="course-pills-1">Duration<p>2 Days</p><p>12 CPD hours</p>This course is intended for<p>This course is designed for professionals in a variety of job roles who are currently using Tableau to perform numerical or general data analysis, visualization, and reporting. They need to provide data visualizations from multiple data sources, or combine data to show comparisons, manipulate data through calculations, create interactive visualizations, or create visualizations that showcase insights from statistical analysis. This course is also designed for students who plan to obtain Tableau Desktop Certified Associate certification, which requires candidates to pass the Tableau Desktop Certified Associate exam.</p>Overview<p>Blend data multiple sources.     Join data.     Access data in PDFs.     Refine visualizations with sets and parameters.     Analyze data with calculations.     Visualize data with advanced calculations.     Perform statistical analysis and forecasting.     Create geographic visualizations.     Get answers with Ask and Explain</p><p></p><p>The advent of cloud computing and storage has ushered in the era of "big data." With the abundance of computational power and storage, organizations and employees with many different roles and responsibilities can benefit from analyzing data to find timely insights and gain competitive advantage.</p>  <p>Data-backed visualizations allow anyone to explore, analyze, and report insights and trends from data. TableauÂ© software is designed for this purpose. Tableau was built to connect to a wide range of data sources and allows users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Beyond the fundamental capabilities of creating data driven visualizations, Tableau allows users to manipulate data with calculations to show insights, make visualizations interactive, and perform statistical analysis. This gives users the ability to create and share data driven insights with peers, executives, and clients.</p><p></p>Prerequisites<p>Tableau Desktop: Part 1</p></div><div id="course-pills-2"><h3>Lesson 1: Blending Data from Multiple Sources</h3><ul>  <li>Topic A: Blend Data</li>  <li>Topic B: Refine Blends to Visualize Key Information</li> </ul>  <h3>Lesson 2: Joining Data</h3><ul>  <li>Topic A: Create Joins</li>  <li>Topic B: Troubleshoot Joins</li>  <li>Topic C: Merge Data with Unions</li></ul>  <h3>Lesson 3: Accessing Data in PDFs</h3><ul>  <li>Topic A: Connect to PDFs</li>  <li>Topic B: Clean Up and Organize PDF Data</li> </ul>  <h3>Lesson 4: Refining Visualizations with Sets and Parameters</h3><ul>  <li>Topic A: Create Sets</li>  <li>Topic B: Analyze Data with Sets</li>  <li>Topic C: Apply Parameters to Refine Visualizations</li>  <li>Topic D: Create Advanced Visualizations</li> </ul>  <h3>Lesson 5: Analyzing Data with Calculations</h3><ul>  <li>Topic A: Create Calculated Fields to Analyze Data</li>  <li>Topic B: Manipulate Data with Functions</li>  <li>Topic C: Analyze Data with Table Calculations</li> </ul>  <h3>Lesson 6: Visualizing Data with Advanced Calculations</h3><ul>  <li>Topic A: Create Groups and Bins with Calculations</li>  <li>Topic B: Analyze Data with LOD Expressions</li> </ul>  <h3>Lesson 7: Performing Statistical Analysis and Forecasting</h3><ul>  <li>Topic A: Perform Statistical Analysis</li>  <li>Topic B: Forecast Data Trends</li> </ul>  <h3>Lesson 8: Creating Geographic Visualizations</h3><ul>  <li>Topic A: Create Maps</li>  <li>Topic B: Customize Mapped Data</li> </ul>  <h3>Lesson 9: Getting Answers with Ask and Explain</h3><ul>  <li>Topic A: Ask Data</li>  <li>Topic B: Explain Data</li> </ul></div><div id="course-pills-3"><h4>Additional course details:</h4><br /><p>Nexus Humans Tableau Desktop - Part 2 training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. </p><p></p> This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. <p></p>Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.  <p></p>While we feel this is the best course for the Tableau Desktop - Part 2 course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.  <p></p>Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.<p></p></div>

Tableau Desktop - Part 2

<div id="course-pills-1">Duration<p>1 Days</p><p>6 CPD hours</p>This course is intended for<p>This course is designed for professionals in a variety of job roles who receive Tableau data visualizations from data analysts or from data visualization engineers. These data report recipients want to take advantage of the many Tableau features and capabilities that enable them to explore the data behind the initial analysis, perform additional analysis to ask next-level questions of the data, and to customize visualizations and dashboards to share new insights and create compelling reports.</p>Overview<p>Explore Tableau reports. Analyze data to get answers and insights. Sort and group data for analysis and reporting. Filter views. Prepare reports. Troubleshoot, collaborate, and share views and analysis</p><p>As data acquisition, access, analysis, and reporting are interwoven with our businesses and lives, more and more data is collected about business and personal activities. This abundance of data and the computing power to analyze it has increased the use of data analysis and data visualization across a broad range of job roles. Decision makers of all types, including managers and executives, must interact with, interpret, and develop reports based on data and analysis provided to them. TableauÂ© software is designed for data analysis and the creation of visualizations. Data analysts prepare data, perform initial analysis, and create visualizations that are then passed on to business data-driven decision makers. These decision makers can use Tableau's tools to explore the data, perform further analysis to find new insights, make decisions, and create customized reports to share their findings.</p>Prerequisites<p>To ensure your success in this course, you should have experience managing data with MicrosoftÂ© ExcelÂ© or Google Sheets?</p></div><div id="course-pills-2"><h3> Lesson 1: Exploring Tableau Reports</h3><ul> <li>Topic A: Data Analysis Workflow with Tableau</li> <li>Topic B: Explore Views</li> <li>Topic C: Edit Workbooks</li></ul>  <h3> Lesson 2: Analyzing Data to Get Answers and Insights</h3><ul> <li>Topic A: Configure Marks with the Marks Card</li> <li>Topic B: Ask New Questions by Changing Aggregation</li> <li>Topic C: Find Answers with Calculations</li> <li>Topic D: Answer Questions with Table Calculations</li></ul>  <h3> Lesson 3: Sorting and Grouping Data for Analysis and Reporting</h3><ul> <li>Topic A: Sort Data</li> <li>Topic B: Group Data</li></ul>  <h3> Lesson 4: Filtering Views</h3><ul> <li>Topic A: Filter Data to Refine Analysis</li> <li>Topic B: Create Interactive Filters for Reports</li></ul>  <h3> Lesson 5: Preparing Reports</h3><ul> <li>Topic A: Format and Annotate Views to Tell Your Story</li> <li>Topic B: Emphasize Data in Reports</li> <li>Topic C: Animate Visualizations for Clarity</li></ul>  <h3>Lesson 6: Troubleshooting, Sharing, and Collaborating</h3><ul> <li>Topic A: Troubleshoot Data Issues</li> <li>Topic B: Collaborate in Tableau Online </li><li>Topic C: Collaborate with Non-Tableau Users</li></ul></div>

Tableau for Data-Driven Decision Makers

<strong>This course is designed for beginners who want to learn how to use Tableau Prep Builder for data preparation and data cleaning. We will start from scratch; no specific knowledge is required; you should only be familiar with Tableau.</strong>
        <p>Are you interested in data analytics and (self-service BI) business intelligence? Are you already using Tableau or plan to use it soon?

You might have already seen Tableau as a visual analytics tool in action. You might have created Tableau dashboards yourself. But as you know, the result of visualizing your data is only the tip of the iceberg. As data analysts spend a huge amount of their time cleaning and preparing data, this process is quite tedious. However, it is most important to get the data cleaned and in the right format.

Meet Tableau Prep Builder! A great tool that can help us in doing data preparation/data cleaning fast and efficiently.

In this Tableau Prep Builder course, you will learn all you need to know to use the power of Tableau Prep Builder for your own data cleaning tasks. The course is developed for beginners. Hence, no prior knowledge is required even though working with Tableau before would be an advantage.

This course will first explore the Tableau Prep Builder interface and then perform three case studies to understand how to use Tableau Prep Builder for data cleaning and data preparation. 

By the end of this course, you will be able to use the power of Tableau Prep Builder for data cleaning.

All the resources for this course are available at  https://github.com/PacktPublishing/Tableau-Prep-Builder-for-Beginners-Getting-Started</p>
        <h2>What You Will Learn</h2><p>Learn the fundamentals of Tableau Prep Builder<br>Learn how to get started with Tableau Prep Builder<br>Perform data cleaning with Tableau Prep Builder<br>Learn how to deal with multiple excel files<br>Work with multiple CSV files as a case study<br>Use transaction case study for data enrichment</p>
        <h2>Audience</h2><p>This course is for all Tableau users who need to do data cleaning. Aspiring data analysts or data scientists or report creators can also benefit from this course.<br><br>This course is a crash course for beginners; hence, we start from scratch so no specific knowledge is required but you should be familiar with Tableau. Tableau Prep builder 14-day Trial version could be used in case you do not have a license (yet).</p>
        <h2>Approach</h2><p>This is a practical course and consists of a case study where you can and should follow along to solve tasks.</p>
        <h2>Key Features</h2><p>Learn new ways to easily prepare data by only clicking or drag and drop with Tableau * Use different case studies to understand the power of Tableau Prep Builder * Perform data preparation and data cleaning with Tableau Prep Builder</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Tableau-Prep-Builder-for-beginners</p>
        <h2>About the Author</h2><h3>Dan We</h3><p>Daniel Weikert is a 33-year-old entrepreneur, data enthusiast, consultant, and trainer. He is a master's degree holder certified in Power BI, Tableau, Alteryx (Core and Advanced), and KNIME (L1-L3).
He is currently working in the business intelligence field and helps companies and individuals obtain vital insights from their data to deliver long-term strategic growth and outpace their competitors.

He has a passion for learning and teaching. He is committed to supporting other people by offering them educational services and helping them accomplish their goals, gain expertise in their profession, or explore new careers.</p>
        <h2>Course Outline</h2><h4>1. Tableau Prep Builder - let's get started</h4><p></p>

This course is designed for beginners who want to learn how to use Tableau Prep Builder for data preparation and data cleaning. We will start from scratch; no specific knowledge is required; you should only be familiar with Tableau.

Tableau Prep Builder for Beginners - Getting Started

Let's build sophisticated visualizations and dashboards using Sankey diagrams and geospatial, sunburst, and circular charts and animate your visualizations. We will also cover advanced Tableau topics, such as Tableau parameters and use cases and Level of Detail (LOD) expressions, spatial functions, advanced filters, and table calculations.

Ultimate Tableau Desktop Course - Beginner to Advanced Bundle

<strong>Learn how to combine the three most important tools in data science: Python, SQL, and Tableau</strong>
        <p>Python, SQL, and Tableau are three of the most widely used tools in the world of data science. Python is the leading programming language
SQL is the most widely used means for communication with database systems
Tableau is the preferred solution for data visualization;

The course starts off by introducing software integration as a concept. We discuss some important terms such as servers, clients, requests, and responses. Moreover, you will learn about data connectivity, APIs, and endpoints. Then we continue by introducing the real-life example exercise the course is centred around: the Absenteeism at Work dataset. The preprocessing part that follows will give you a taste of what BI and data science look like in real-life, on-the-job situations. Then we continue by applying some Machine Learning to our data. You will learn how to explore the problem at hand from a machine-learning perspective, how to create targets, what kind of statistical preprocessing is necessary for this part of the exercise, how to train a Machine Learning model, and how to test it-a truly comprehensive ML exercise. Connecting Python and SQL is not immediate; we show how that's done in an entire section of the course.

By the end of that section, you will be able to transfer data from Jupyter to Workbench. And finally, as promised, Tableau will allow us to visualize the data we have been working with. We will prepare several insightful charts and will interpret the results together.

All the code files are placed at https://github.com/PacktPublishing/Python-SQL-Tableau-Integrating-Python-SQL-and-Tableau</p>
        <h2>What You Will Learn</h2><p>Create a module of the ML model for later use<br>Connect Python and SQL to transfer data from Jupyter to Workbench<br>Visualize data in Tableau<br>Analyze and interpret exercise outputs in Jupyter and Tableau</p>
        <h2>Audience</h2><p>This course is for anyone looking for a career in Business Intelligence and Data Science. Data scientists who are eagerly looking to break into the field and learn the necessary essentials of Data Science and software engineers who are interested in building intelligent applications driven by Python and Machine Learning will also benefit from this course.</p>
        <h2>Approach</h2><p>This course is designed so that each section covers a new scenario and uses a step-by-step approach to help you learn and understand each concept.</p>
        <h2>Key Features</h2><p>How to use Python, SQL, and Tableau together * Software integration * Data preprocessing techniques * Apply machine learning</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/python-sql-tableau-integrating-python-sql-and-tableau</p>
        <h2>About the Author</h2><h3>365 Careers Ltd.</h3><p>365 Careers' courses have been taken by more than 203,000 students in 204 countries. People working at world-class firms such as Apple, PayPal, and Citibank have completed 365 Careers trainings. By choosing 365 Careers, you make sure you will learn from proven experts who have a passion for teaching, and can take you from beginner to pro in the shortest possible amount of time.

If you want to become a financial analyst, a finance manager, an FP&A analyst, an investment banker, a business executive, an entrepreneur, a business intelligence analyst, a data analyst, or a data scientist, 365 Careers' courses are the perfect place to start.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p>This section will give you a brief introduction about the course.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. (Free Preview): What Does the Course Cover?</p><p style='margin: 0'>Introduction: What Does the Course Cover?</p></td></tr></tbody></table><br><h4>2. What is software integration?</h4><p>This section will help you to understand about software integration?.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. (Free Preview): Properties and Definitions: Data, Servers, Clients, Requests and Responses</p><p style='margin: 0'>What is software integration?: Properties and Definitions: Data, Servers, Clients, Requests and Responses</p></td></tr><tr><td style='padding: 15px;'><p>2. (Free Preview): Properties and Definitions: Data Connectivity, APIs, and Endpoints</p><p style='margin: 0'>What is software integration?: Properties and Definitions: Data Connectivity, APIs, and Endpoints</p></td></tr><tr><td style='padding: 15px;'><p>3. Further Details on APIs</p><p style='margin: 0'>What is software integration?: Further Details on APIs</p></td></tr><tr><td style='padding: 15px;'><p>4. (Free Preview): Text Files as Means of Communication</p><p style='margin: 0'>What is software integration?: Text Files as Means of Communication</p></td></tr><tr><td style='padding: 15px;'><p>5. Definitions and Applications</p><p style='margin: 0'>What is software integration?: Definitions and Applications</p></td></tr></tbody></table><br><h4>3. Setting up the working environment</h4><p>This section will help you set up the working environment.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Setting Up the Environment - An Introduction (Do Not Skip, Please)!</p><p style='margin: 0'>Setting up the working environment: Setting Up the Environment - An Introduction (Do Not Skip, Please)!</p></td></tr><tr><td style='padding: 15px;'><p>2. Why Python and why Jupyter?</p><p style='margin: 0'>Setting up the working environment: Why Python and why Jupyter?</p></td></tr><tr><td style='padding: 15px;'><p>3. Installing Anaconda</p><p style='margin: 0'>Setting up the working environment: Installing Anaconda</p></td></tr><tr><td style='padding: 15px;'><p>4. The Jupyter Dashboard - Part 1</p><p style='margin: 0'>Setting up the working environment: The Jupyter Dashboard - Part 1</p></td></tr><tr><td style='padding: 15px;'><p>5. The Jupyter Dashboard - Part 2</p><p style='margin: 0'>Setting up the working environment: The Jupyter Dashboard - Part 2</p></td></tr><tr><td style='padding: 15px;'><p>6. Installing sklearn</p><p style='margin: 0'>Setting up the working environment: Installing sklearn</p></td></tr></tbody></table><br><h4>4. What's next in the course?</h4><p>This section will help you understand what this course is all about.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Up Ahead</p><p style='margin: 0'>What's next in the course?: Up Ahead</p></td></tr><tr><td style='padding: 15px;'><p>2. Real-Life Example: Absenteeism at Work</p><p style='margin: 0'>What's next in the course?: Real-Life Example: Absenteeism at Work</p></td></tr><tr><td style='padding: 15px;'><p>3. Real-Life Example: The Dataset</p><p style='margin: 0'>What's next in the course?: Real-Life Example: The Dataset</p></td></tr></tbody></table><br><h4>5. Preprocessing</h4><p>In this section, we'll learn about Preprocessing.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Data Sets in Python</p><p style='margin: 0'>Preprocessing: Data Sets in Python</p></td></tr><tr><td style='padding: 15px;'><p>2. Data at a Glance</p><p style='margin: 0'>Preprocessing: Data at a Glance</p></td></tr><tr><td style='padding: 15px;'><p>3. A Note on Our Usage of Terms with Multiple Meanings</p><p style='margin: 0'>Preprocessing: A Note on Our Usage of Terms with Multiple Meanings</p></td></tr><tr><td style='padding: 15px;'><p>4. Picking the Appropriate Approach for the Task at Hand</p><p style='margin: 0'>Preprocessing: Picking the Appropriate Approach for the Task at Hand</p></td></tr><tr><td style='padding: 15px;'><p>5. Removing Irrelevant Data</p><p style='margin: 0'>Preprocessing: Removing Irrelevant Data</p></td></tr><tr><td style='padding: 15px;'><p>6. Examining the Reasons for Absence</p><p style='margin: 0'>Preprocessing: Examining the Reasons for Absence</p></td></tr><tr><td style='padding: 15px;'><p>7. Splitting a Column into Multiple Dummies</p><p style='margin: 0'>Preprocessing: Splitting a Column into Multiple Dummies</p></td></tr><tr><td style='padding: 15px;'><p>8. Dummy Variables and Their Statistical Importance</p><p style='margin: 0'>Preprocessing: Dummy Variables and Their Statistical Importance</p></td></tr><tr><td style='padding: 15px;'><p>9. Grouping - Transforming Dummy Variables into Categorical Variables</p><p style='margin: 0'>Preprocessing: Grouping - Transforming Dummy Variables into Categorical Variables</p></td></tr><tr><td style='padding: 15px;'><p>10. Concatenating Columns in Python</p><p style='margin: 0'>Preprocessing: Concatenating Columns in Python</p></td></tr><tr><td style='padding: 15px;'><p>11. Changing Column Order in Pandas DataFrame</p><p style='margin: 0'>Preprocessing: Changing Column Order in Pandas DataFrame</p></td></tr><tr><td style='padding: 15px;'><p>12. Implementing Checkpoints in Coding</p><p style='margin: 0'>Preprocessing: Implementing Checkpoints in Coding</p></td></tr><tr><td style='padding: 15px;'><p>13. Exploring the Initial "Date" Column</p><p style='margin: 0'>Preprocessing: Exploring the Initial "Date" Column</p></td></tr><tr><td style='padding: 15px;'><p>14. Using the "Date" Column to Extract the Appropriate Month Value</p><p style='margin: 0'>Preprocessing: Using the "Date" Column to Extract the Appropriate Month Value</p></td></tr><tr><td style='padding: 15px;'><p>15. Introducing "Day of the Week"</p><p style='margin: 0'>Preprocessing: Introducing "Day of the Week"</p></td></tr><tr><td style='padding: 15px;'><p>16. Further Analysis of the DataFrame: Next 5 Columns</p><p style='margin: 0'>Preprocessing: Further Analysis of the DataFrame: Next 5 Columns</p></td></tr><tr><td style='padding: 15px;'><p>17. Further Analysis of the DaraFrame: "Education", "Children", "Pets"</p><p style='margin: 0'>Preprocessing: Further Analysis of the DaraFrame: "Education", "Children", "Pets"</p></td></tr><tr><td style='padding: 15px;'><p>18. A Final Note on Preprocessing</p><p style='margin: 0'>Preprocessing: A Final Note on Preprocessing</p></td></tr></tbody></table><br><h4>6. Machine Learning</h4><p>In this section, we'll learn about Machine Learning.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. (Free Preview): Exploring the Problem from a Machine Learning Point of View</p><p style='margin: 0'>Machine Learning: Exploring the Problem from a Machine Learning Point of View</p></td></tr><tr><td style='padding: 15px;'><p>2. Creating the Targets for the Logistic Regression</p><p style='margin: 0'>Machine Learning: Creating the Targets for the Logistic Regression</p></td></tr><tr><td style='padding: 15px;'><p>3. Selecting the Inputs</p><p style='margin: 0'>Machine Learning: Selecting the Inputs</p></td></tr><tr><td style='padding: 15px;'><p>4. A Bit of Statistical Preprocessing</p><p style='margin: 0'>Machine Learning: A Bit of Statistical Preprocessing</p></td></tr><tr><td style='padding: 15px;'><p>5. Train-test Split of the Data</p><p style='margin: 0'>Machine Learning: Train-test Split of the Data</p></td></tr><tr><td style='padding: 15px;'><p>6. Training the Model and Assessing its Accuracy</p><p style='margin: 0'>Machine Learning: Training the Model and Assessing its Accuracy</p></td></tr><tr><td style='padding: 15px;'><p>7. Extracting the Intercept and Coefficients from a Logistic Regression</p><p style='margin: 0'>Machine Learning: Extracting the Intercept and Coefficients from a Logistic Regression</p></td></tr><tr><td style='padding: 15px;'><p>8. Interpreting the Logistic Regression Coefficients</p><p style='margin: 0'>Machine Learning: Interpreting the Logistic Regression Coefficients</p></td></tr><tr><td style='padding: 15px;'><p>9. Omitting the dummy variables from the Standardization</p><p style='margin: 0'>Machine Learning: Omitting the dummy variables from the Standardization</p></td></tr><tr><td style='padding: 15px;'><p>10. Interpreting the Important Predictors</p><p style='margin: 0'>Machine Learning: Interpreting the Important Predictors</p></td></tr><tr><td style='padding: 15px;'><p>11. Simplifying the Model (Backward Elimination)</p><p style='margin: 0'>Machine Learning: Simplifying the Model (Backward Elimination)</p></td></tr><tr><td style='padding: 15px;'><p>12. Testing the Machine Learning Model</p><p style='margin: 0'>Machine Learning: Testing the Machine Learning Model</p></td></tr><tr><td style='padding: 15px;'><p>13. How to Save the Machine Learning Model and Prepare it for Future Deployment</p><p style='margin: 0'>Machine Learning: How to Save the Machine Learning Model and Prepare it for Future Deployment</p></td></tr><tr><td style='padding: 15px;'><p>14. Creating a Module for Later Use of the Model</p><p style='margin: 0'>Machine Learning: Creating a Module for Later Use of the Model</p></td></tr></tbody></table><br><h4>7. Installing MySQL and Getting Acquainted with the Interface</h4><p>In this section, we'll Install MySQL and get Acquainted with the Interface.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Installing MySQL</p><p style='margin: 0'>Installing MySQL and Getting Acquainted with the Interface: Installing MySQL</p></td></tr><tr><td style='padding: 15px;'><p>2. Setting Up a Connection</p><p style='margin: 0'>Installing MySQL and Getting Acquainted with the Interface: Setting Up a Connection</p></td></tr><tr><td style='padding: 15px;'><p>3. Introduction to the MySQL Interface</p><p style='margin: 0'>Installing MySQL and Getting Acquainted with the Interface: Introduction to the MySQL Interface</p></td></tr></tbody></table><br><h4>8. Connecting Python and SQL</h4><p>This section will help you to connect Python and SQL.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Implementing the 'absenteeism_module' - Part I</p><p style='margin: 0'>Connecting Python and SQL: Implementing the 'absenteeism_module' - Part I</p></td></tr><tr><td style='padding: 15px;'><p>2. Implementing the 'absenteeism_module' - Part II</p><p style='margin: 0'>Connecting Python and SQL: Implementing the 'absenteeism_module' - Part II</p></td></tr><tr><td style='padding: 15px;'><p>3. Creating a Database in MySQL</p><p style='margin: 0'>Connecting Python and SQL: Creating a Database in MySQL</p></td></tr><tr><td style='padding: 15px;'><p>4. Importing and Installing 'pymysql'</p><p style='margin: 0'>Connecting Python and SQL: Importing and Installing 'pymysql'</p></td></tr><tr><td style='padding: 15px;'><p>5. Creating a Connection and Cursor</p><p style='margin: 0'>Connecting Python and SQL: Creating a Connection and Cursor</p></td></tr><tr><td style='padding: 15px;'><p>6. Creating the 'predicted_outputs' table in MySQL</p><p style='margin: 0'>Connecting Python and SQL: Creating the 'predicted_outputs' table in MySQL</p></td></tr><tr><td style='padding: 15px;'><p>7. Running an SQL SELECT Statement from Python</p><p style='margin: 0'>Connecting Python and SQL: Running an SQL SELECT Statement from Python</p></td></tr><tr><td style='padding: 15px;'><p>8. Transferring Data from Jupyter to Workbench - Part I</p><p style='margin: 0'>Connecting Python and SQL: Transferring Data from Jupyter to Workbench - Part I</p></td></tr><tr><td style='padding: 15px;'><p>9. Transferring Data from Jupyter to Workbench - Part II</p><p style='margin: 0'>Connecting Python and SQL: Transferring Data from Jupyter to Workbench - Part II</p></td></tr><tr><td style='padding: 15px;'><p>10. Transferring Data from Jupyter to Workbench - Part III</p><p style='margin: 0'>Connecting Python and SQL: Transferring Data from Jupyter to Workbench - Part III</p></td></tr></tbody></table><br><h4>9. Analyzing the Obtained data in Tableau</h4><p>In this section, we'll analyze the Obtained data.</p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Analysis in Tableau: Age vs Probability</p><p style='margin: 0'>Analyzing the Obtained data in Tableau: Analysis in Tableau: Age vs Probability</p></td></tr><tr><td style='padding: 15px;'><p>2. Analysis in Tableau: Reasons vs Probability</p><p style='margin: 0'>Analyzing the Obtained data in Tableau: Analysis in Tableau: Reasons vs Probability</p></td></tr><tr><td style='padding: 15px;'><p>3. Analysis in Tableau: Transportation Expense vs Probability</p><p style='margin: 0'>Analyzing the Obtained data in Tableau: Analysis in Tableau: Transportation Expense vs Probability</p></td></tr></tbody></table>

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