3803 Engineer courses in Reigate delivered Online

DNS training course description This three-day hands on DNS training course studies both the UNIX BIND and the Microsoft (MS DNS) implementations. The course starts with the big picture of how DNS works, then client configuration. Primary and secondary servers are then configured, progressing to DDNS, subdomains and security issues. Hands on sessions follow all sections ensuring that troubleshooting techniques are used throughout the course. Students choose whether to use Windows or UNIX for the hands on sessions. What will you learn Describe the architecture of DNS. Explain how DNS works. Install, configure, maintain and troubleshoot DNS DNS training course details Who will benefit: Technical staff wanting to learn DNS including: Network personnel System administrators. Prerequisites: UNIX Fundamentals (or Windows knowledge). TCP/IP foundation for engineers. Duration 3 days DNS training course contents What is DNS? Hostnames, Name resolution, host files, host file problems, What is DNS? The DNS namespace, TLDs, gTLDs, registering domains, Nameservers, how DNS works. Hands on Testing DNS servers on the Internet. DNS clients Ways to use DNS, dynamic and static configuration, multiple nameservers, domain name, searchlist, resolution issues, testing the configuration. Hands on Client configuration. DNS server software Implementations, Microsoft, BIND, daemons and services, installation, starting and stopping servers. Hands on Setting up a DNS server. DNS zone files What is a zone, Zone file overview, Forward zones, Reverse zones, Resource records, A records, PTR, CNAME, Root hints, local zone file. BIND and Microsoft configuration. Hands on Server configuration files. NS and applications MX records, Mail server load balancing, SPF, SRV records, VoIP and SRV, Microsoft and SRV, NAPTR. Hands on Testing records with dig and nslookup. DNS slaves and other servers DNS server types, Server resilience, Slaves, Zone transfers, SOA records, Serial numbers, recommendations, polling based zone transfers, NOTIFY, AD integration, DNS caching, Negative caching, TTL, Caching only servers. Hands on Masters, slaves and zone transfers. The DNS protocol The DNS stack, DNS port numbers, DNS queries, The DNS header, header section format, question format, other section format. Hands on Troubleshooting DNS with Wireshark. Dynamic DNS DHCP, DDNS, IXFR, WINS integration. Hands on Dynamic DNS. Subdomains Root servers, root server selection, Authority, delegation, NS records, subdomain with and without delegation, reverse delegation. Hands on Delegation, setting up a subdomain server. DNS security Restricting queries, DNS and firewalls, Split DNS, forwarders, internal root servers, the use of proxy servers, DNSSEC, TSIG. Hands on Hardening a DNS server. DNS and IPv6 What is IPv6, IPv6 addressing, IPv6 DNS issues, AAAA, IPv6 reverse delegation. Troubleshooting DNS Problem solving, DNS troubleshooting, Zone file checking, Some common errors, Log files, tools, nslookup, dig, host, DNS design, performance, load balancing. Hands on Putting it all together. Summary Useful books, Internet sites, RFCs. Appendix: ENUM What is ENUM, How ENUM works, NAPTR.

IPsec training course description This hands on course focuses on IPsec VPNs. Rather than focusing on one implementation this course concentrates on the technologies and protocols of IPsec. Starting with an overview of the complete IPsec architecture the course then moves onto ESP packet analysis along with encryption and authentication provided. IKEv1 and IKEv2 are both covered in detail. Having covered IPsec with pre shared keys the course then moves onto IPsec with certificates followed by IPsec issues. The course is vendor neutral with hands on with both Cisco and Microsoft implementations. What will you learn Explain how IPsec works. Explain the role of AH, ESP and IKE. Configure IPsec. Troubleshoot IPsec. IPsec training course details Who will benefit: Technical staff working with IPsec. Prerequisites: Definitive IP VPNs for engineers. Duration 3 days IPsec training course contents What is IPsec? How to spell IPsec, IPsec is IP security, confidentiality, integrity, authenticity, replay protection, what is a VPN? Network layer security, IPsec and IPv4, IPsec and IPv6, the suite of protocols, the standard, IPsec RFCs, IPsec history. Hands on Analysis of 'normal' IP packets. IPsec architecture The IPsec protocols, AH vs ESP, Why two headers? transport mode, tunnel mode, Remote access VPNs, site to site VPNs, security associations, SA database, Security Parameters Index, implementations: Host tack, Bump in the Stack, Bump in the Wire. Hands on Configuring IPsec. AH What AH does, the stack, The AH header, What is authenticated? Device authentication. AH in transport mode, AH in tunnel mode. Hands on AH packet analysis. ESP What ESP does, the ESP header, ESP in transport mode, ESP in tunnel mode, ESP and SA, ESP and SPI. Hands on ESP packet analysis, policy configuration. IPsec encryption IPsec is a framework, standard algorithms, ESP keys, the role of IKE, key lifetimes, how IKE generates the keys, DES, 3DES, AES, cipher block chaining, counter mode, other encryption. Hands on Encryption configuration. IPsec authentication Authentication types, IPsec authentication, Authentication algorithms: MD5, keyed SHA-1, HMAC-MD5, HMAC-SHA-1, HMAC-RIPEMD, other authentication algorithms. Hands on Authentication configuration. IKE Internet Key Exchange, IKE and the SAD, the two phase negotiation, ISAKMP, ISAKMP header, pre shared keys, digital signatures, public key encryption, Diffie Hellman, proposals, counter proposals, nonces, identities, phase 1 negotiation: main mode, aggressive mode, base mode. Phase 2 negotiation: quick mode, new group mode. Hands on IKE packet analysis. More IKE PFS, IKE and dynamic addresses, XAUTH, hybrid authentication, CRACK, ULA, PIC. User level authentication. IKE renegotiation, heartbeats. Hands on Troubleshooting IPsec. IKEv2 The IKEv2 exchange, IKE_SA_INIT, IKE_AUTH, CREATE_CHILD_SA, IKEv2 packets, the informational exchange. Comparing IKev1 vs IKE v2. Hands on IKEv2 configuration and analysis. PKI What is PKI?, Digital certificates, Certificate authorities, CA servers, RA, VA, certificates, CA hierarchy, CRLs, certificate formats. Hands on installing and configuring certificate servers. IPsec issues NAT, IPsec overhead and fragmentation. Summary IPsec strengths and weaknesses. Where to get further information.

Gain n-depth knowledge about Docker technology and the confidence to help your company or your own project to apply the right Docker deployment workflow. Learn all about Docker, Docker REST API, and Docker continuous integration to build Docker images.

Total IP multicast training course description This training course provides an advanced three day hands on study of IP multicast technology focusing on architectures, applications and protocols. All aspects of IP multicasting are covered including PC, server and switch implementations. Design, configuration, support and troubleshooting are all covered in the course. Hands on sessions are used to reinforce the theory rather than teach specific implementations. What will you learn Design multicast networks. Explain how multicast networks work. Compare and contrast the different multicast routing protocols, such as DVMRP, PIM, MBGP and SSM. Configure PCs, servers, switches and routers for multicasting. Configure multicast routing protocols including: PIM Dense Mode. PIM Sparse Mode BGP SSM Troubleshoot multicast networks. Total IP multicast training course details Who will benefit: Technical staff working with IP multicasts. Prerequisites: TCP/IP Foundation for engineers Duration 3 days Total IP multicast training course contents Introduction What is multicasting? Why multicast? Why not multicast? Multicasting vs. multiple unicasts, Multicasting vs. broadcasts, multicasting applications, the use of unicast addressing for setting up multicast applications, multicast use within standard protocols such as OSPF. hands on Example multicast applications. Addressing Layer two multicast addresses, Class D addresses, mapping layer 3 addresses onto layer 2 multicast addresses. Multicast addresses on NBMAs, scoping multicast traffic, Multicast address blocks, GLOP, IPv6 and multicasting, anycasting. hands on Multicast addressing. Multicast architectures Where the different protocols are used, PC to router, router to router, how switches can get involved. hands on Analysing multicast packets. PC to router Configuring Class D addresses, IGMP, packet formats, queries, reports, maintaining groups, enhancements to IGMP (v2 and v3), Leaving a group, querier elections, hands on Analysing IGMP packets. Switches and multicasting Controlling multicast traffic with switches, VLANS, static bridge table entries, IGMP snooping, CGMP. hands on Configuring switches for multicast environments. Router to router MOSPF, DVMRP, PIM Sparse Mode, PIM Dense Mode, MBGP. hands on Simple router configuration for multicasting. Theory behind multicast routing protocols Distribution trees, source distribution trees, shared trees, core based trees. Reverse path forwarding, Multicast routing protocol types. PIM DM: Flooding, pruning, PIM designated routers, hands on configuring PIM DM. PIM Sparse mode Rendevous points, discovering RPs, hands on Configuring PIM SM, using different protocols for different groups. PIM SM with one RP, using multiple RPs, Auto RP. MBGP Multiprotocol routing, how does MBGP work? How MBGP carries multiple protocol information, MBGP and multicasts, MBGP and IPv6. hands on Configuring MBGP for multicasts. Internet multicasting The internet, ISPs, the MBone, tunnelling, Inter domain multicasting, the role of MBGP, Inter domain problem, MSDP, MSDP operation SSM, PIM-SM and shared trees, SSM, PIM-SSM operation, SSM benefits. hands on MSDP configuration. SSM configuration.

Learning Outcomes After completing this course, learners will be able to: Learn Python for data analysis using NumPy and Pandas Acquire a clear understanding of data visualisation using Matplotlib, Seaborn and Pandas Deepen your knowledge of Python for interactive and geographical potting using Plotly and Cufflinks Understand Python for data science and machine learning Get acquainted with Recommender Systems with Python Enhance your understanding of Python for Natural Language Processing (NLP) Description Whether you are from an engineering background or not you still can efficiently work in the field of data science and the machine learning sector, if you have proficient knowledge of Python. Since Python is the easiest and most used programming language, you can start learning this language now to advance your career with the Data Science And Machine Learning Using Python : A Bootcamp course. This course will give you a thorough understanding of the Python programming language. Moreover, it will show how can you use Python for data analysis and machine learning. Alongside that, from this course, you will get to learn data visualisation, and interactive and geographical plotting by using Python. The course will also provide detailed information on Python for data analysis, Natural Language Processing (NLP) and much more. Upon successful completion of this course, get a CPD- certificate of achievement which will enhance your resume and career. Certificate of Achievement After the successful completion of the final assessment, you will receive a CPD-accredited certificate of achievement. The PDF certificate is for 9.99, and it will be sent to you immediately after through e-mail. You can get the hard copy for 15.99, which will reach your doorsteps by post.  Method of Assessment After completing this course, you will be provided with some assessment questions. To pass that assessment, you need to score at least 60%. Our experts will check your assessment and give you feedback accordingly. Career Path After completing this course, you can explore various career options such as Web Developer Software Engineer Data Scientist Machine Learning Engineer Data Analyst In the UK professionals usually get a salary of £25,000 - £30,000 per annum for these positions. Course Content Welcome, Course Introduction & overview, and Environment set-up Welcome & Course Overview 00:07:00 Set-up the Environment for the Course (lecture 1) 00:09:00 Set-up the Environment for the Course (lecture 2) 00:25:00 Two other options to setup environment 00:04:00 Python Essentials Python data types Part 1 00:21:00 Python Data Types Part 2 00:15:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 1) 00:16:00 Loops, List Comprehension, Functions, Lambda Expression, Map and Filter (Part 2) 00:20:00 Python Essentials Exercises Overview 00:02:00 Python Essentials Exercises Solutions 00:22:00 Python for Data Analysis using NumPy What is Numpy? A brief introduction and installation instructions. 00:03:00 NumPy Essentials - NumPy arrays, built-in methods, array methods and attributes. 00:28:00 NumPy Essentials - Indexing, slicing, broadcasting & boolean masking 00:26:00 NumPy Essentials - Arithmetic Operations & Universal Functions 00:07:00 NumPy Essentials Exercises Overview 00:02:00 NumPy Essentials Exercises Solutions 00:25:00 Python for Data Analysis using Pandas What is pandas? A brief introduction and installation instructions. 00:02:00 Pandas Introduction 00:02:00 Pandas Essentials - Pandas Data Structures - Series 00:20:00 Pandas Essentials - Pandas Data Structures - DataFrame 00:30:00 Pandas Essentials - Handling Missing Data 00:12:00 Pandas Essentials - Data Wrangling - Combining, merging, joining 00:20:00 Pandas Essentials - Groupby 00:10:00 Pandas Essentials - Useful Methods and Operations 00:26:00 Pandas Essentials - Project 1 (Overview) Customer Purchases Data 00:08:00 Pandas Essentials - Project 1 (Solutions) Customer Purchases Data 00:31:00 Pandas Essentials - Project 2 (Overview) Chicago Payroll Data 00:04:00 Pandas Essentials - Project 2 (Solutions Part 1) Chicago Payroll Data 00:18:00 Python for Data Visualization using matplotlib Matplotlib Essentials (Part 1) - Basic Plotting & Object Oriented Approach 00:13:00 Matplotlib Essentials (Part 2) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials (Part 3) - Basic Plotting & Object Oriented Approach 00:22:00 Matplotlib Essentials - Exercises Overview 00:06:00 Matplotlib Essentials - Exercises Solutions 00:21:00 Python for Data Visualization using Seaborn Seaborn - Introduction & Installation 00:04:00 Seaborn - Distribution Plots 00:25:00 Seaborn - Categorical Plots (Part 1) 00:21:00 Seaborn - Categorical Plots (Part 2) 00:16:00 Seborn-Axis Grids 00:25:00 Seaborn - Matrix Plots 00:13:00 Seaborn - Regression Plots 00:11:00 Seaborn - Controlling Figure Aesthetics 00:10:00 Seaborn - Exercises Overview 00:04:00 Seaborn - Exercise Solutions 00:19:00 Python for Data Visualization using pandas Pandas Built-in Data Visualization 00:34:00 Pandas Data Visualization Exercises Overview 00:03:00 Panda Data Visualization Exercises Solutions 00:13:00 Python for interactive & geographical plotting using Plotly and Cufflinks Plotly & Cufflinks - Interactive & Geographical Plotting (Part 1) 00:19:00 Plotly & Cufflinks - Interactive & Geographical Plotting (Part 2) 00:14:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Overview) 00:11:00 Plotly & Cufflinks - Interactive & Geographical Plotting Exercises (Solutions) 00:37:00 Capstone Project - Python for Data Analysis & Visualization Project 1 - Oil vs Banks Stock Price during recession (Overview) 00:15:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 1) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 2) 00:18:00 Project 1 - Oil vs Banks Stock Price during recession (Solutions Part 3) 00:17:00 Project 2 (Optional) - Emergency Calls from Montgomery County, PA (Overview) 00:03:00 Python for Machine Learning (ML) - scikit-learn - Linear Regression Model Introduction to ML - What, Why and Types.. 00:15:00 Theory Lecture on Linear Regression Model, No Free Lunch, Bias Variance Tradeoff 00:15:00 scikit-learn - Linear Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Linear Regression Model Hands-on (Part 2) 00:19:00 Good to know! How to save and load your trained Machine Learning Model! 00:01:00 scikit-learn - Linear Regression Model (Insurance Data Project Overview) 00:08:00 scikit-learn - Linear Regression Model (Insurance Data Project Solutions) 00:30:00 Python for Machine Learning - scikit-learn - Logistic Regression Model Theory: Logistic Regression, conf. mat., TP, TN, Accuracy, Specificityetc. 00:10:00 scikit-learn - Logistic Regression Model - Hands-on (Part 1) 00:17:00 scikit-learn - Logistic Regression Model - Hands-on (Part 2) 00:20:00 scikit-learn - Logistic Regression Model - Hands-on (Part 3) 00:11:00 scikit-learn - Logistic Regression Model - Hands-on (Project Overview) 00:05:00 scikit-learn - Logistic Regression Model - Hands-on (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn - K Nearest Neighbors Theory: K Nearest Neighbors, Curse of dimensionality . 00:08:00 scikit-learn - K Nearest Neighbors - Hands-on 00:25:00 scikt-learn - K Nearest Neighbors (Project Overview) 00:04:00 scikit-learn - K Nearest Neighbors (Project Solutions) 00:14:00 Python for Machine Learning - scikit-learn - Decision Tree and Random Forests Theory: D-Tree & Random Forests, splitting, Entropy, IG, Bootstrap, Bagging. 00:18:00 scikit-learn - Decision Tree and Random Forests - Hands-on (Part 1) 00:19:00 scikit-learn - Decision Tree and Random Forests (Project Overview) 00:05:00 scikit-learn - Decision Tree and Random Forests (Project Solutions) 00:15:00 Python for Machine Learning - scikit-learn -Support Vector Machines (SVMs) Support Vector Machines (SVMs) - (Theory Lecture) 00:07:00 scikit-learn - Support Vector Machines - Hands-on (SVMs) 00:30:00 scikit-learn - Support Vector Machines (Project 1 Overview) 00:07:00 scikit-learn - Support Vector Machines (Project 1 Solutions) 00:20:00 scikit-learn - Support Vector Machines (Optional Project 2 - Overview) 00:02:00 Python for Machine Learning - scikit-learn - K Means Clustering Theory: K Means Clustering, Elbow method .. 00:11:00 scikit-learn - K Means Clustering - Hands-on 00:23:00 scikit-learn - K Means Clustering (Project Overview) 00:07:00 scikit-learn - K Means Clustering (Project Solutions) 00:22:00 Python for Machine Learning - scikit-learn - Principal Component Analysis (PCA) Theory: Principal Component Analysis (PCA) 00:09:00 scikit-learn - Principal Component Analysis (PCA) - Hands-on 00:22:00 scikit-learn - Principal Component Analysis (PCA) - (Project Overview) 00:02:00 scikit-learn - Principal Component Analysis (PCA) - (Project Solutions) 00:17:00 Recommender Systems with Python - (Additional Topic) Theory: Recommender Systems their Types and Importance 00:06:00 Python for Recommender Systems - Hands-on (Part 1) 00:18:00 Python for Recommender Systems - - Hands-on (Part 2) 00:19:00 Python for Natural Language Processing (NLP) - NLTK - (Additional Topic) Natural Language Processing (NLP) - (Theory Lecture) 00:13:00 NLTK - NLP-Challenges, Data Sources, Data Processing .. 00:13:00 NLTK - Feature Engineering and Text Preprocessing in Natural Language Processing 00:19:00 NLTK - NLP - Tokenization, Text Normalization, Vectorization, BoW. 00:19:00 NLTK - BoW, TF-IDF, Machine Learning, Training & Evaluation, Naive Bayes 00:13:00 NLTK - NLP - Pipeline feature to assemble several steps for cross-validation 00:09:00 Resources Resources - Data Science and Machine Learning using Python : A Bootcamp 00:00:00 Order your Certificates & Transcripts Order your Certificates & Transcripts 00:00:00 Frequently Asked Questions Are there any prerequisites for taking the course? There are no specific prerequisites for this course, nor are there any formal entry requirements. All you need is an internet connection, a good understanding of English and a passion for learning for this course. Can I access the course at any time, or is there a set schedule? You have the flexibility to access the course at any time that suits your schedule. Our courses are self-paced, allowing you to study at your own pace and convenience. How long will I have access to the course? For this course, you will have access to the course materials for 1 year only. This means you can review the content as often as you like within the year, even after you've completed the course. However, if you buy Lifetime Access for the course, you will be able to access the course for a lifetime. Is there a certificate of completion provided after completing the course? Yes, upon successfully completing the course, you will receive a certificate of completion. This certificate can be a valuable addition to your professional portfolio and can be shared on your various social networks. Can I switch courses or get a refund if I'm not satisfied with the course? We want you to have a positive learning experience. If you're not satisfied with the course, you can request a course transfer or refund within 14 days of the initial purchase. How do I track my progress in the course? Our platform provides tracking tools and progress indicators for each course. You can monitor your progress, completed lessons, and assessments through your learner dashboard for the course. What if I have technical issues or difficulties with the course? If you encounter technical issues or content-related difficulties with the course, our support team is available to assist you. You can reach out to them for prompt resolution.

SMTP training course description A hands on course focusing on the workings of email systems and the standard protocols that they use. The course is not specific to any particular implementation, but some vendor specifics are noted. Linux and Microsoft machines are used in hands on sessions to reinforce the theory of major sessions. The course concentrates on troubleshooting and interworking using network sniffing and protocol inspection rather than "which buttons to push". What will you learn Describe and explain SMTP MIME POP3 IMAP PGP, GPG, S/MIME SPF, DKIM, DMARC Configure mail routing Secure email systems SMTP training course details Who will benefit: Technical staff responsible for email systems. Prerequisites: TCP/IP foundation for engineers. Duration 3 days SMTP training course contents SMTP architecture What is SMTP, email before SMTP, SMTP history, the different protocols, clients, servers. Email composition, transmission, delivering emails, storing and reading emails. MUAs, MTAs, POP3, IMAP, SMTP, DNS, webmail. Hands on Setting up MTAs and MUAs and sending a simple email using telnet. The SMTP protocol SMTP protocol stack, SMTP headers, HELO, SMTP mail, MAIL FROM, RCPT TO, DATA, SMTPUTF8, 8BITMIME, TURN, EHLO, ETRN, 3 digit replies. Hands on Analysing SMTP packets on a network. DNS and SMTP SMTP forwarding, SMTP relays, interoperation, how SMTP uses DNS, MX records. Hands on Setting up mail relays. SMTP headers IMF data, From, to, cc, bcc, sender and recipient headers, message Ids, received trails, in-reply-to, received-SPF, mail list headers. Hands on Using clients to analyse details from mail headers, including true originators and path of emails. MIME Email attachments, MIME versions, content type headers, encoding, base 64, binary data, multi part headers, troubleshooting attachments. Hands on Analysing MIME headers and attachments. POP3 What is POP3, where to use POP3, authorisation, transactions, POP3 commands: USER, PASS, STAT, LIST, RETR, DELE. Hands on Setting up a POP3 server, analysing POP3 packets on a network. IMAP and IMAPS What is IMAP, where to use IMAP, authorisation, mailbox structure, IMAP commands: LOGIN, AUTHENTICATE, LIST, CREATE, Examine (message flags), SELECT, STORE. Hands on Setting up an IMAP server and analysing IMAP packets on a network. Interoperation Mail gateways, addressing, Exchange, sendmail. Email security Basics, Transport level: STARTTLS. Content: PGP/GPG, mail signing and encryption, S/MIME, digital certificates, secure email submission. Hands on Setting up and using a PGP key, configure MTAs to use TLS. Email authentication and spam prevention Mail relays, grey listing, block list & RBL, DNSBL (Real-time Black hole List), White list, SPF, Domain Keys Identified Mail (DKIM), Author Domain Signing Practices (ADSP), Abuse Report Format (ARF), Domain-based Message Authentication, Reporting and Conformance (DMARC). Hands on Relay spamming and the blocking spamming.

Duration 5 Days 30 CPD hours This course is intended for The skills covered in this course converge on four areas-software development, IT operations, applied math and statistics, and business analysis. Target students for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems. So, the target student is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decisionmaking products that bring value to the business. A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification Overview In this course, you will develop AI solutions for business problems. You will: Solve a given business problem using AI and ML. Prepare data for use in machine learning. Train, evaluate, and tune a machine learning model. Build linear regression models. Build forecasting models. Build classification models using logistic regression and k -nearest neighbor. Build clustering models. Build classification and regression models using decision trees and random forests. Build classification and regression models using support-vector machines (SVMs). Build artificial neural networks for deep learning. Put machine learning models into operation using automated processes. Maintain machine learning pipelines and models while they are in production Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions. Solving Business Problems Using AI and ML Topic A: Identify AI and ML Solutions for Business Problems Topic B: Formulate a Machine Learning Problem Topic C: Select Approaches to Machine Learning Preparing Data Topic A: Collect Data Topic B: Transform Data Topic C: Engineer Features Topic D: Work with Unstructured Data Training, Evaluating, and Tuning a Machine Learning Model Topic A: Train a Machine Learning Model Topic B: Evaluate and Tune a Machine Learning Model Building Linear Regression Models Topic A: Build Regression Models Using Linear Algebra Topic B: Build Regularized Linear Regression Models Topic C: Build Iterative Linear Regression Models Building Forecasting Models Topic A: Build Univariate Time Series Models Topic B: Build Multivariate Time Series Models Building Classification Models Using Logistic Regression and k-Nearest Neighbor Topic A: Train Binary Classification Models Using Logistic Regression Topic B: Train Binary Classification Models Using k-Nearest Neighbor Topic C: Train Multi-Class Classification Models Topic D: Evaluate Classification Models Topic E: Tune Classification Models Building Clustering Models Topic A: Build k-Means Clustering Models Topic B: Build Hierarchical Clustering Models Building Decision Trees and Random Forests Topic A: Build Decision Tree Models Topic B: Build Random Forest Models Building Support-Vector Machines Topic A: Build SVM Models for Classification Topic B: Build SVM Models for Regression Building Artificial Neural Networks Topic A: Build Multi-Layer Perceptrons (MLP) Topic B: Build Convolutional Neural Networks (CNN) Topic C: Build Recurrent Neural Networks (RNN) Operationalizing Machine Learning Models Topic A: Deploy Machine Learning Models Topic B: Automate the Machine Learning Process with MLOps Topic C: Integrate Models into Machine Learning Systems Maintaining Machine Learning Operations Topic A: Secure Machine Learning Pipelines Topic B: Maintain Models in Production

Looking to build an AI application from scratch? Look no further than this compact course with ChatGPT! Using the OpenAI API and the latest web development technologies, including React, Next.js, JavaScript, Node, and CSS, you will gain hands-on experience building an AI-powered application that generates pet names for users.

Embark on a digital crafting odyssey, diving into the intricate world of web creation with our 'PHP Web Development with MySQL; GitHub & Heroku' course. Visualise your first step into this digital tapestry with the 'Introduction' unit, an inviting prelude that demystifies the realm of server-side scripting. As learners unfurl the sails of their developmental journey, they'll configure their coding environment, laying the robust groundwork for a future in web architecture. Advancing into the heart of PHP, our syllabus navigates through the crucial syntax and fundamentals that form the bedrock of dynamic website construction. Engage with the creation of interactive forms, delve into database manipulation using MySQL, and master user authentication processes. This course promises a transformative learning expedition, from first principles to deploying live web applications, all while ensuring each participant garners the confidence to stitch together the seams of secure, responsive online experiences. Learning Outcomes Comprehend PHP fundamentals and create robust web applications. Configure environments for PHP development with precision. Integrate MySQL databases for dynamic content management. Construct and handle secure PHP forms for data collection. Implement user authentication to safeguard web applications. Why choose this PHP Web Development with MySQL; GitHub & Heroku course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this PHP Web Development with MySQL; GitHub & Heroku course for? Novices embarking on web development careers. Technologists eager to learn server-side scripting. Data managers focusing on MySQL database integration. Coders looking to understand PHP in web applications. Developers aiming to utilise GitHub and Heroku for deployment. Career path Web Developer: £25,000 - £50,000 PHP Developer: £24,000 - £45,000 MySQL Database Administrator: £30,000 - £60,000 User Authentication Specialist: £35,000 - £55,000 Back-End Developer: £28,000 - £53,000 DevOps Engineer: £40,000 - £70,000 Prerequisites This PHP Web Development with MySQL; GitHub & Heroku does not require you to have any prior qualifications or experience. You can just enrol and start learning.This PHP Web Development with MySQL; GitHub & Heroku was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Unit 01: Introduction Introduction 00:06:00 Unit 02: Environment Configuration Module 01: Setup a PHP Environment using XAMPP 00:16:00 Module 02: Install Composer Package Manager 00:03:00 Module 03: Visual Studio Code - Web Development Add ons 00:12:00 Module 04: Create a GitHub Account 00:13:00 Module 05: Create a Heroku Account 00:08:00 Unit 03: PHP Basics and Syntax Module 01: How PHP Works 00:29:00 Module 02: IFELSE Statements 00:19:00 Module 03: Switch Statements 00:09:00 Module 04: FOR Loop 00:10:00 Module 05: WHILE AND DOWHILE Loops 00:14:00 Module 06: PHP Arrays and Manipulation 00:13:00 Module 07: String Manipulation Functions 00:28:00 Module 08: Date and Time Manipulation Functions 00:15:00 Module 09: User Defined Functions 00:22:00 Module 10: PHP Include and Require 00:22:00 Module 11: PHP Website Layout - With Bootstrap 00:23:00 Module 12: Add Project to Github 00:08:00 Module 13: Publish Website to Heroku 00:20:00 Unit 04: PHP Forms and MySQL and User Authentication Module 01: Project and Website Setup 00:21:00 Module 02: Create a Bootstrap 4 Form 00:28:00 Module 03: PHP Form - $_GET Action 00:23:00 Module 04: PHP Form - $_POST Action 00:11:00 Module 05: Design Database with phpMyAdmin 00:19:00 Module 06: Connect to Database using PHP PDO 00:18:00 Module 07: Save Records to Database 00:38:00 Module 08: View Database Records 00:36:00 Module 09: View One Record's Details 00:28:00 Module 10: Update Database Records 00:34:00 Module 11: Delete Database Records 00:11:00 Module 12: Final Touches: Form Validation, Error Messages, Success Messages 00:17:00 Module 13: Create Heroku App and Remote Database 00:21:00 Module 14: Setup Authentication Tables in Database 00:20:00 Module 15: Setup Login and Authentication 00:29:00 Module 16: Control User Access 00:08:00 Module 17: Sending Confirmation Emails 00:31:00 Module 18: Upload Profile Pictures 00:31:00 Module 19: Final Touches 00:14:00 Resources Resources - PHP Web Development w/ MySQL GitHub & Heroku 00:00:00 Assignment Assignment - PHP Web Development with MySQL; GitHub & Heroku 00:00:00

Welcome to the exciting world of C# (C-Sharp)! This course is your gateway to mastering one of the most versatile and in-demand programming languages in the world. As technology continues to advance, C# remains at the forefront, offering endless opportunities for those who can harness its power. In this course, we will take you on a journey that begins with the fundamentals and leads you to become a proficient C# developer. In the first section, 'Introduction,' you'll gain insight into the world of C# and understand its significance in the modern software development landscape. We'll guide you through the process of setting up your development environment, ensuring you're ready to dive into coding with confidence. The course progresses to cover essential topics such as C# console programming, Winforms applications, database operations, user management, and source control. By the end, you'll have a deep understanding of C# and the practical skills needed to develop robust software applications. Join us on this exhilarating journey, and let's unlock the incredible potential of web development together. Learning Outcomes of C# (C-Sharp): Develop a solid foundation in C# programming, including mastery of basic control structures and more advanced concepts. Create Windows forms applications and understand the basics of Multi-Document Interface (MDI) for efficient user interface development. Manage databases effectively, covering CRUD (Create, Read, Update, Delete) operations and database changes. Implement user management and login functionality to enhance the security and usability of your applications. Learn the importance of source control and acquire the skills to add your projects to source control repositories. Why buy this C# (C-Sharp) course? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments are designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the C# (C-Sharp) Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Who is this C# (C-Sharp) course for? Aspiring software developers looking to build a strong foundation in programming. Computer science students seeking practical knowledge and skills for real-world application development. IT professionals aiming to expand their expertise and career opportunities in software development. Individuals interested in creating Windows applications with user-friendly interfaces. Anyone eager to understand source control and its role in collaborative software development. Career path Junior Developer: £25,000 - £40,000 Per Annum Software Engineer: £40,000 - £60,000 Per Annum Database Developer with C#: £35,000 - £55,000 Per Annum Senior C# Developer: £55,000 - £80,000 Per Annum Software Development Team Lead (C#): £70,000 - £100,000 Per Annum C# Solutions Architect: £90,000 - £130,000 Per Annum Prerequisites This C# (C-Sharp) does not require you to have any prior qualifications or experience. You can just enrol and start learning.This C# (C-Sharp) was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Certification After studying the course materials, there will be a written assignment test which you can take at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99 Original Hard Copy certificates need to be ordered at an additional cost of £8. Course Curriculum Introduction Introduction 00:03:00 Development Environment Setup Install Visual Studio 2019 Community Edition 00:04:00 Install .Net Core SDK 00:02:00 Tour Of Visual Studio 00:11:00 C# Console Programming - Basic Control Structures Write a Simple Hello World Program 00:15:00 Input and Output Programs 00:18:00 C# Data Types and Conversion 00:22:00 Operators in C# 00:17:00 Condition Statements 00:32:00 Repetition Statements 00:28:00 Methods and Return Types 00:27:00 C# Console Programming - More Advanced Concepts String Manipulation Functions 00:21:00 Handling Exceptions 00:13:00 Classes and Objects 00:37:00 Arrays, Lists and Other Collections 00:35:00 Winforms Applications - The Basics Create a Simple Winforms Application (Car Rental Application) 00:26:00 Understand Winforms Controls, Properties and Events 00:21:00 Form Validation and Exception Handling 00:34:00 Create Database in SQL Server 00:10:00 Create Database Model with ADO.NET 00:13:00 Select Data from the Database Using LINQ 00:15:00 Submit to Database from Form 00:17:00 Multi Document Interface (MDI) and More Database Operations Creating Additional Forms and Windows 00:14:00 Create an MDI Application 00:17:00 Managing Database Changes and CRUD Operations View Data In A Grid 00:29:00 Managing Database Changes 00:18:00 Create and Edit Records (Using one form) 00:48:00 Vehicle Data Validations and Exception Handling 00:07:00 Manage Car Rental Records 00:45:00 Enhancing Application Flow and User Experience 00:28:00 User Management and Login Functionality Simple Login Form 00:39:00 Control Features Based on User Roles 00:35:00 User Password and Active Status Reset 00:21:00 Add New Users and Password Reset 00:45:00 Add To Source Control Add Project to GitHub 00:19:00 Assignment Assignment - C# (C-Sharp) 00:00:00