984 Programming Languages courses in Epsom delivered Online

Welcome to 'Python Programming for Non Programmers Level 5,' a course specially designed for those new to the world of coding. This program starts with a comprehensive introduction to Python, a versatile programming language favored in numerous fields. Progressing to the second unit, participants will familiarize themselves with the initial steps of Python programming, setting a strong foundation for future learning. The course then advances to conditional branching in Python, an essential skill for logical problem-solving in coding. A highlight of this course is the practical project: building the game 'Rock Paper Scissors'. This engaging task not only consolidates learning but also adds a fun element to the process. The curriculum further includes critical topics like string operations, date and time functionalities, and the nuances of file handling in Python. Learners will navigate through the complexities of Python data structures-tuples, lists, and dictionaries-and learn to craft user functions, enhancing their coding capabilities. The course also covers email automation, ingenious import tactics, interfacing with operating systems, and handling exceptions with finesse. Furthermore, learners will get hands-on experience with package installation, scheduling tasks in Python, and managing databases using SQLite. The course wraps up with insights on running Python programs via command prompt and Jupyter Notebook, ensuring learners are well-equipped for real-world applications. Learning Outcomes Acquire foundational knowledge and setup skills in Python programming. Master conditional branching for effective problem-solving in code. Complete a practical coding project to solidify Python skills. Learn essential Python operations, including string handling and file management. Explore and apply advanced Python concepts for real-world applications. Why choose this Python Programming for Non Programmers Level 5 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 Python Programming for Non Programmers Level 5 course for? Beginners eager to learn Python from scratch. Non-technical professionals desiring to add coding skills to their portfolio. Educators keen to integrate Python into their teaching methodologies. Businesspersons interested in understanding coding fundamentals for tech-based solutions. Enthusiasts exploring programming as a new hobby or career path. Career path Entry-Level Python Programmer: £25,000 - £40,000 Python-Enabled Data Analyst: £28,000 - £45,000 Python Automation Engineer: £30,000 - £50,000 Technical Support Analyst with Python Skills: £22,000 - £35,000 Python Web Developer: £26,000 - £42,000 Quality Assurance Analyst with Python Expertise: £24,000 - £38,000 Prerequisites This Python Programming for Non Programmers Level 5 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Python Programming for Non Programmers Level 5 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 to Python Programming Section 01: Course Introduction 00:02:00 Unit 02: Getting Started with Python Section 01: Software Installation 00:02:00 Section 02: Hello World Program 00:06:00 Section 03: Input and Output 00:07:00 Section 04: Calculating Average of 5 Numbers 00:03:00 Unit 03: Conditional Branching with Python Section 01: If Loop In Python 00:06:00 Section 02: Program Using If Else part 1 00:03:00 Section 03: Program Using If Else part 2 00:08:00 Section 04: Program for Calculator 00:02:00 Section 05: Program Using For Loop 00:08:00 Section 06: For Table 00:05:00 Section 07: For loop and Mathematical Operator in Python 00:04:00 Section 08: Factorial of Number Using Python 00:06:00 Section 09: Program Using While 00:05:00 Section 10: While Loop Example 00:07:00 Section 11: Tasks for Practice 00:02:00 Unit 04: Importing external/internal library in python Section 01: Importing Library in Python 00:07:00 Unit 05: Project Rock Paper and Scissors Section 01: Rock Paper and Scissor Game 00:06:00 Unit 06: Strings Operation in Python Section 01: Program Using String part 1 00:05:00 Section 02: Program using String 2 00:06:00 Section 03: Program Using String 3 00:06:00 Section 04: Program Using String part 4 00:03:00 Unit 07: Date and time in Python Section 01: Use of Date and Time part 1 00:05:00 Section 02: Use of Date and Time part 2 00:05:00 Unit 08: File Handling, read and write using Python Section 01: File Handling Part 1 00:08:00 Section 02: File Handling Part 2 00:07:00 Unit 09: Data Storage Structures, Tuple, List and Dictionary Section 01: Tuple in Python Part 1 00:10:00 Section 02: Tuple in Python Part 2 00:07:00 Section 03: Using Lists part 1 00:07:00 Section 04: Using List part 2 00:12:00 Section 05: Using Lists part 3 00:06:00 Section 06: Using Lists part 4 00:08:00 Section 07: Using Lists part 5 00:02:00 Section 08: Use of Dictionary Part 1 00:04:00 Section 09: Use of Dictionary Part 2 00:05:00 Section 10: Use of Dictionary Part 3 00:08:00 Section 11: Use of Dictionary Part 4 00:07:00 Unit 10: Writing user functions in Python Section 01: Function in Python Part 1 00:06:00 Section 02: Function in Python Part 2 00:05:00 Section 03: Function in Python Part 3 00:04:00 Section 04: Function in Python Part 4 00:07:00 Section 05: Function in Python Part 5 00:08:00 Unit 11: Sending mail Section 01: Send Email 00:09:00 Unit 12: Import Tricks in Python Section 01: Import Study part 1 00:07:00 Section 02: Import Study part 2 00:03:00 Unit 13: Import Operating System and Platform Section 01: Importing OS 00:06:00 Section 02: Import Platform 00:05:00 Unit 14: Exceptions handling in python Section 01: Exception in Python part 1 00:11:00 Section 02: Exception in Python part 2 00:07:00 Section 03: Exception in Python part 3 00:05:00 Unit 15: Installing Packages and Scheduling In Python Section 01: Installing Packages using built in package manager 00:08:00 Section 02: Scheduler in Python 00:05:00 Unit 16: Data Base In Python using sqlite Section 01: Data Base 1 00:08:00 Section 02: Data Base 2 00:09:00 Section 03: Data Base 3 00:08:00 Section 04: Data base 4 00:07:00 Section 05: Data Base 5 00:06:00 Unit 17: Running Program from Command Prompt and jupyter Notebook Section 01: IDE_1 00:05:00 Section 02: IDE_2 00:07:00 Unit 18: Conclusion Section 01: Conclusion 00:02:00 Resources Resources - Diploma in Python Programming 00:00:00 Assignment Assignment - Diploma in Python Programming 00:00:00 Recommended Materials Workbook - Diploma in Python Programming 00:00:00

Embark on a journey into the captivating realm of blockchain technology with our comprehensive course on Ethereum Blockchain DApp using Solidity. Dive into a world where innovation meets practicality, where the Ethereum ecosystem unfolds its potential, and where your skills take flight. Explore the dynamic landscape of Ethereum, from understanding its fundamental concepts to deploying and maintaining Ethereum apps with finesse. Stay ahead of the curve as you grasp the nuances of blockchain technology and harness its power to build decentralised applications that redefine possibilities. Unlock the secrets of Ethereum as you delve into its core, learning about smart contracts, Ethereum wallets, and the intricacies of blockchain development tools. Stay updated with the latest Ethereum news and predictions, understanding how Ethereum value influences global markets, including Ethereum price UK trends and Ethereum price predictions. Through hands-on exploration, navigate the Ethereum development lifecycle confidently, from conceptualisation to integration, testing to deployment. Witness the synergy between blockchain and non-blockchain applications, broadening your horizons and enhancing your skill set. Learning Outcomes: Grasp the fundamental concepts of what is blockchain technology and its applications, including Ethereum's role in revolutionising decentralised ecosystems. Develop proficiency in Solidity programming language and understand the Ethereum development lifecycle, from ideation to deployment. Gain practical experience in building Ethereum-based decentralised applications (DApps) and smart contracts. Acquire essential skills in testing, deploying, and maintaining Ethereum apps, ensuring their seamless integration into real-world scenarios. Stay informed about Ethereum news, price fluctuations, and market predictions, enabling informed decision-making in blockchain development ventures. Why buy this Ethereum Blockchain DApp using Solidity 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. Certification After studying the course materials of the Ethereum Blockchain DApp using Solidity there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this Ethereum Blockchain DApp using Solidity course for? Aspiring blockchain developers eager to master Ethereum and Solidity. Tech enthusiasts interested in exploring the dynamic world of decentralised applications. Students seeking to enhance their knowledge of blockchain technology for academic or career advancement. Entrepreneurs aiming to leverage blockchain for innovative business solutions. Professionals in IT, finance, or related fields looking to diversify their skill set with blockchain expertise. Prerequisites This Ethereum Blockchain DApp using Solidity does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Ethereum Blockchain DApp using Solidity 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. Career path Blockchain Developer: £40,000 - £80,000 per annum Ethereum Developer: £45,000 - £90,000 per annum Smart Contract Developer: £50,000 - £95,000 per annum Blockchain Analyst: £35,000 - £70,000 per annum Cryptocurrency Consultant: £45,000 - £85,000 per annum Blockchain Project Manager: £55,000 - £100,000 per annum Course Curriculum Section 01: What is Blockchain? Introduction to Building an Ethereum Blockchain App 00:02:00 The Beginning of Blockchain 00:05:00 Currency and Cryptocurrency 00:05:00 Why Use the Blockchain? 00:06:00 Blockchain Data and Blocks 00:06:00 Blockchain Immutability 00:03:00 Blockchain Consensus 00:02:00 Building the Blockchain Story 00:03:00 Hashes 00:06:00 What is a Chain of Blocks? 00:04:00 Finding the Nonce 00:05:00 Blockchain Mining 00:03:00 Arriving at Consensus 00:05:00 Public vs. Private Blockchains 00:03:00 Distributed Processing and Blockchain Solutions 00:06:00 Section 02: What is Ethereum? Introduction to Ethereum 00:03:00 Ethereum in Financial Services 00:07:00 Ethereum in Digital Identity Management 00:05:00 Ethereum in Industry Applications 00:06:00 Ethereum in Government 00:03:00 Ethereum Smart Contracts 00:03:00 Ether and the Initial Coin Offering (ICO) 00:06:00 Decentralized Autonomous Organization (DAO) 00:03:00 The Ethereum Ecosystem 00:06:00 Building Blockchain Apps 00:05:00 Section 03: The Ethereum Ecosystem & the Development Lifecycle Parts of the Ethereum Blockchain 00:11:00 Smart Contracts 00:05:00 Smart Contract Languages 00:04:00 What are Virtual Machines? 00:06:00 The Ethereum Virtual Machine (EVM) 00:03:00 Fueling Your Code with Gas 00:05:00 Tools for Ethereum SDLC 00:03:00 Blockchain Client 00:03:00 Writing and Testing Your Code, Part 1 00:05:00 Writing and Testing Your Code, Part 2 00:07:00 Section 04: Ethereum Development Tools Your Ethereum Development Toolbox 00:04:00 Installing Geth Lab (CLI Blockchain Client) 00:04:00 Installing Ganache Lab (Test Blockchain) 00:06:00 Installing Truffle Lab (Development Environment and Testing Framework) 00:06:00 Installing Microsoft Visual Studio Code Lab (IDE) 00:05:00 Section 05: Your Ethereum Wallet What is an Ethereum Wallet? 00:02:00 Types of Ethereum Wallets 00:06:00 Web and Desktop Wallets 00:07:00 Mobile, Hardware, and Paper Wallets 00:09:00 Installing MetaMask 00:05:00 Section 06: Building Your First Ethereum App Preparing Your First Truffle Project 00:07:00 Writing a Simple Smart Contract 00:11:00 Compiling Your Simple Smart Contract 00:10:00 Deploying Code and Invoking Functions 00:09:00 Section 07: Learning about Smart Contracts Smart Contracts Review 00:03:00 What is Supply Chain? 00:07:00 Supply Chain Challenges and Blockchain Solutions 00:07:00 Blockchain Solution Examples 00:04:00 Ethereum Tokens 00:06:00 Your Supply Chain Project 00:08:00 Exploring Solidity 00:11:00 Defining Types of Data 00:05:00 Data Types Lab 00:09:00 Solidity Data Modifiers, Part 1 00:04:00 Solidity Data Modifiers, Part 2 00:06:00 Revisiting Gas 00:06:00 Controlling Flow 00:12:00 Handling Errors 00:05:00 Section 08: Your SuSection 08: Your Supply Chain Smart Contract dApppply Chain Smart Contract dApp Designing Your Supply Chain App 00:04:00 What are dApps? 00:06:00 Token Smart Contract Details 00:08:00 Supply Chain Smart Contract Details 00:06:00 Smart Contract Road Map 00:02:00 Token Smart Contract Data Lab, Part 1 00:07:00 Token Smart Contract Data Lab, Part 2 00:09:00 Supply Chain Smart Contract Functions Lab, Part 1 00:10:00 Supply Chain Smart Contract Functions Lab, Part 2 00:09:00 Token Smart Contract Functions Lab, Part 1 00:05:00 Token Smart Contract Functions Lab, Part 2 00:04:00 Supply Chain Smart Contract Functions Lab, Part 1 00:10:00 Supply Chain Smart Contract Functions Lab, Part 2 00:09:00 Using Events 00:07:00 Implementing Events 00:05:00 More on Ownership 00:08:00 Designing for Security 00:09:00 Implementing Minimal Functionality 00:06:00 Section 09: Testing Ethereum Apps Blockchain dApp Testing 00:10:00 Deploying Your dApp to a Test Blockchain Lab 00:08:00 Writing Tests for Ethereum dApps 00:06:00 Command-Line Testing Lab, Part 1 00:04:00 Command-Line Testing Lab, Part 2 00:11:00 Command-Line Testing Lab, Part 3 00:03:00 JavaScript Testing 00:08:00 Logging and Handling Errors 00:07:00 Logging Activity in Smart Contracts 00:05:00 Fixing Bugs in a dApp 00:05:00 Section 10: Deploying and Maintaining Ethereum Apps Test Blockchains 00:08:00 The Live Blockchain (Mainnet) 00:05:00 Connecting to Multiple Blockchains and Infura Lab 00:05:00 Configuring Truffle and Infura Lab 00:06:00 Funding Your Account Lab 00:04:00 Deploying to the Live Blockchain 00:08:00 Section 11: Integrating Non-Blockchain Apps with Ethereum Blockchain and Database Storage 00:11:00 Execution and Flow in dApps and Traditional Applications 00:05:00 Blockchain Incorporation Design Goals 00:06:00 Integration Considerations for Incorporating Blockchain 00:06:00 Interface Considerations for Incorporating Blockchain 00:04:00 Resources Resources - Ethereum Blockchain DApp using Solidity 00:00:00

Ready to go beyond the basics? The JavaScript Advanced Training Course is tailored for learners who already understand the fundamentals and are eager to sharpen their scripting edge. This course dives into asynchronous programming, closures, higher-order functions, module patterns, and more – all laid out with clarity and purpose. Whether you're brushing up or building out your skills, you'll find this course paced to keep things flowing without ever feeling overwhelming. Think of it as levelling up without the drama. Expect engaging lessons designed to explain the deeper mechanisms behind how JavaScript truly operates in the browser. We’ll unravel common pitfalls, explore performance techniques, and demystify complex concepts in a straightforward way. It's ideal for developers who want to write cleaner, faster, and more efficient code – all while learning in a structured, accessible format. So, if you're looking to refine your scripting finesse and take control of your code, this course is made with you in mind. Learning outcomes: Understand the basics of JavaScript programming language Learn how to work with loops and operators Understand how to enable and place JavaScript on a web page Develop skills in creating multimedia and interactive features using JavaScript Learn how to use image maps and animations in web development The JavaScript Advanced Training course is designed for individuals who are interested in expanding their knowledge of JavaScript programming language. This course covers advanced topics such as loops, variables, and operators, and how to enable and place JavaScript on a web page. Students will also learn how to use JavaScript to create multimedia and interactive features, including image maps and animations. This course is ideal for those who have a basic understanding of JavaScript and are looking to take their skills to the next level. It is also suitable for web developers who want to enhance their skill set and create more interactive and engaging web pages. JavaScript Advanced Training Course Curriculum Section 01: Introduction Section 02: Loop Section 03: Example Section 04: Print and Animation Section 05: Image Map and Multimedia Section 06: JavaScript Enabling and Placement Section 07: JavaScript Variables and Operators Section 08: While Loop How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Individuals with a basic understanding of JavaScript who want to expand their knowledge Web developers who want to enhance their skill set Anyone interested in creating interactive and engaging web pages Students pursuing a career in web development Entrepreneurs and business owners who want to develop their own websites Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Web Developer Front-end Developer Full-stack Developer Software Engineer UI/UX Designer Salary range in the UK: £25,000 - £60,000 Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

AI is no longer a distant concept—it’s here, it’s evolving fast, and Python is the language fuelling much of its momentum. Whether you’re curious about machine learning, neural networks, or automation, this course offers a sharp and structured approach to understanding artificial intelligence using Python. From foundational concepts to intelligent algorithm design, you'll gain a clear insight into how machines simulate thought and decision-making. Ideal for those who want to stay ahead of the tech curve, this course unpacks Python-based AI with clarity and a touch of dry charm. You won’t need to decipher jargon or get tangled in theory-heavy lectures. Instead, you’ll find logic, code, and clever explanations that speak to learners who value smart learning over flashiness. AI with Python might sound complex, but once you've seen it broken down our way, it’ll feel like you’ve learned to speak the language of the future. Learning Outcomes: Develop an understanding of the principles and practices of Artificial Intelligence (AI) Learn effective strategies for detecting patterns and natural language processing Develop analytical skills for creating AI models and programs Understand Python programming language and its applications in AI Be able to make informed decisions and navigate the complex and dynamic world of AI The "Learn AI with Python" course is designed to provide a comprehensive understanding of the principles and practices that underpin successful AI programming. Through engaging modules and real-world case studies, learners will gain insights into the basics of AI, advanced techniques for detecting patterns and natural language processing, and effective strategies for creating AI models and programs using Python programming language. By the end of the course, learners will be equipped with the knowledge and skills to make informed decisions and navigate the complex and dynamic world of AI. Whether you're a beginner or an experienced programmer, this course is a must-have for anyone interested in the world of AI. Learn AI with Python Course Curriculum Section 01: Introduction Section 02: Class Imbalance and Grid Search Section 03: Adaboost Regressor Section 04: Detecting patterns with Unsupervised Learning Section 05: Affinity Propagation Model Section 06: Clustering Quality Section 07: Gaussian Mixture Model Section 08: Classifiers Section 09: Logic Programming Section 10: Heuristic Search Section 11: Natural Language Processing How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Programmers looking to enhance their AI skills Business professionals interested in AI applications Computer science students interested in AI Entrepreneurs looking to incorporate AI into their products or services Anyone interested in gaining a comprehensive understanding of AI and its applications Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path AI Programmer: £30,000 - £70,000 per year Data Scientist: £30,000 - £80,000 per year Machine Learning Engineer: £35,000 - £90,000 per year AI Researcher: £40,000 - £100,000 per year Software Developer: £25,000 - £70,000 per year Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

Delve into the world of data analysis with 'R Programming for Data Science,' a course designed to guide learners through the intricacies of R, a premier programming language in the data science domain. The course opens with a broad perspective on data science, illuminating the pivotal role of R in this field. Learners are then introduced to R and RStudio, equipping them with the foundational tools and interfaces essential for R programming. The curriculum progresses with an introduction to the basics of R, ensuring learners grasp the core principles that underpin more complex operations. A highlight of this course is its in-depth exploration of R's versatile data structures, including vectors, matrices, factors, and data frames. Each unit is crafted to provide learners with a comprehensive understanding of these structures, pivotal for effective data handling and manipulation. The course also emphasizes the importance of relational and logical operators in R, key elements for executing data operations. As the course advances, learners will engage with the nuances of conditional statements and loops, essential for writing efficient and dynamic R scripts. Moving into more advanced territories, the course delves into the creation and usage of functions, an integral part of R programming, and the exploration of various R packages that extend the language's capabilities. Learners will also gain expertise in the 'apply' family of functions, crucial for streamlined data processing. Further units cover regular expressions and effective strategies for managing dates and times in data sets. The course concludes with practical applications in data acquisition, cleaning, visualization, and manipulation, ensuring learners are well-prepared to tackle real-world data science challenges using R. Learning Outcomes Develop a foundational understanding of R's role in data science and proficiency in RStudio. Gain fluency in R programming basics, enabling the handling of complex data tasks. Acquire skills in managing various R data structures for efficient data analysis. Master relational and logical operations for advanced data manipulation in R. Learn to create functions and utilize R packages for expanded analytical capabilities. Why choose this R Programming for Data Science 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 R Programming for Data Science course for? Beginners in data science eager to learn R programming. Data analysts and scientists looking to enhance their skills in R. Researchers in various fields requiring advanced data analysis tools. Statisticians seeking to adopt R for more sophisticated data manipulations. Professionals in finance, healthcare, and other sectors needing data-driven insights. Career path Data Scientist (R Expertise): £30,000 - £70,000 Data Analyst (R Programming Skills): £27,000 - £55,000 Bioinformatics Scientist (R Proficiency): £35,000 - £60,000 Quantitative Analyst (R Knowledge): £40,000 - £80,000 Research Analyst (R Usage): £25,000 - £50,000 Business Intelligence Developer (R Familiarity): £32,000 - £65,000 Prerequisites This R Programming for Data Science does not require you to have any prior qualifications or experience. You can just enrol and start learning.This R Programming for Data Science 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: Data Science Overview Introduction to Data Science 00:01:00 Data Science: Career of the Future 00:04:00 What is Data Science? 00:02:00 Data Science as a Process 00:02:00 Data Science Toolbox 00:03:00 Data Science Process Explained 00:05:00 What's next? 00:02:00 Unit 02: R and RStudio Engine and coding environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A quick tour 00:04:00 Unit 03: Introduction to Basics Arithmetic with R 00:03:00 Variable assignment 00:04:00 Basic data types in R 00:03:00 Unit 04: Vectors Creating a vector 00:05:00 Naming a vector 00:04:00 Arithmetic calculations on vectors 00:07:00 Vector selection 00:06:00 Selection by comparison 00:04:00 Unit 05: Matrices What's a Matrix? 00:02:00 Analyzing Matrices 00:03:00 Naming a Matrix 00:05:00 Adding columns and rows to a matrix 00:06:00 Selection of matrix elements 00:03:00 Arithmetic with matrices 00:07:00 Additional Materials 00:00:00 Unit 06: Factors What's a Factor? 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Unit 07: Data Frames What's a Data Frame? 00:03:00 Creating Data Frames 00:20:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Additional Materials 00:00:00 Unit 08: Lists Why would you need lists? 00:01:00 Creating a List 00:06:00 Selecting elements from a list 00:03:00 Adding more data to the list 00:02:00 Additional Materials 00:00:00 Unit 09: Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 Additional Materials 00:00:00 Unit 10: Logical Operators AND, OR, NOT Operators 00:04:00 Logical operators with vectors and matrices 00:04:00 Reverse the result: (!) 00:01:00 Relational and Logical Operators together 00:06:00 Additional Materials 00:00:00 Unit 11: Conditional Statements The IF statement 00:04:00 IFELSE 00:03:00 The ELSEIF statement 00:05:00 Full Exercise 00:03:00 Additional Materials 00:00:00 Unit 12: Loops Write a While loop 00:04:00 Looping with more conditions 00:04:00 Break: stop the While Loop 00:04:00 What's a For loop? 00:02:00 Loop over a vector 00:02:00 Loop over a list 00:03:00 Loop over a matrix 00:04:00 For loop with conditionals 00:01:00 Using Next and Break with For loop 00:03:00 Additional Materials 00:00:00 Unit 13: Functions What is a Function? 00:02:00 Arguments matching 00:03:00 Required and Optional Arguments 00:03:00 Nested functions 00:02:00 Writing own functions 00:03:00 Functions with no arguments 00:02:00 Defining default arguments in functions 00:04:00 Function scoping 00:02:00 Control flow in functions 00:03:00 Additional Materials 00:00:00 Unit 14: R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different ways to load a package 00:02:00 Additional Materials 00:00:00 Unit 15: The Apply Family - lapply What is lapply and when is used? 00:04:00 Use lapply with user-defined functions 00:03:00 lapply and anonymous functions 00:01:00 Use lapply with additional arguments 00:04:00 Additional Materials 00:00:00 Unit 16: The apply Family - sapply & vapply What is sapply? 00:02:00 How to use sapply 00:02:00 sapply with your own function 00:02:00 sapply with a function returning a vector 00:02:00 When can't sapply simplify? 00:02:00 What is vapply and why is it used? 00:04:00 Additional Materials 00:00:00 Unit 17: Useful Functions Mathematical functions 00:05:00 Data Utilities 00:08:00 Additional Materials 00:00:00 Unit 18: Regular Expressions grepl & grep 00:04:00 Metacharacters 00:05:00 sub & gsub 00:02:00 More metacharacters 00:04:00 Additional Materials 00:00:00 Unit 19: Dates and Times Today and Now 00:02:00 Create and format dates 00:06:00 Create and format times 00:03:00 Calculations with Dates 00:03:00 Calculations with Times 00:07:00 Additional Materials 00:00:00 Unit 20: Getting and Cleaning Data Get and set current directory 00:04:00 Get data from the web 00:04:00 Loading flat files 00:03:00 Loading Excel files 00:05:00 Additional Materials 00:00:00 Unit 21: Plotting Data in R Base plotting system 00:03:00 Base plots: Histograms 00:03:00 Base plots: Scatterplots 00:05:00 Base plots: Regression Line 00:03:00 Base plots: Boxplot 00:03:00 Unit 22: Data Manipulation with dplyr Introduction to dplyr package 00:04:00 Using the pipe operator (%>%) 00:02:00 Columns component: select() 00:05:00 Columns component: rename() and rename_with() 00:02:00 Columns component: mutate() 00:02:00 Columns component: relocate() 00:02:00 Rows component: filter() 00:01:00 Rows component: slice() 00:04:00 Rows component: arrange() 00:01:00 Rows component: rowwise() 00:02:00 Grouping of rows: summarise() 00:03:00 Grouping of rows: across() 00:02:00 COVID-19 Analysis Task 00:08:00 Additional Materials 00:00:00 Assignment Assignment - R Programming for Data Science 00:00:00

Dive into the fascinating world of deep learning with this expertly crafted course designed to unravel the mysteries of neural networks using R. This course guides you through the core principles of neural networks, illustrating how layers of algorithms mimic the human brain’s ability to identify patterns and make decisions. Whether you’re a data enthusiast or a professional seeking to enhance your analytical toolkit, this course offers a clear and engaging path to understanding deep learning concepts through the power of R programming. With a sharp focus on theory and application, you will explore how to build, train, and optimise neural networks effectively, while leveraging R’s rich ecosystem of libraries and tools. The course content is designed to maintain a perfect balance between depth and clarity, making complex topics accessible without oversimplification. By the end, you will be equipped with a strong conceptual foundation and the confidence to approach deep learning projects with R, all through an engaging online format that fits seamlessly into your schedule. Learning Outcomes: Understanding of single-layer and multi-layer neural networks Knowledge of R programming for neural network applications Implementation of neural networks in real-world projects Familiarity with agriculture and war datasets for neural network modelling Ability to evaluate neural network model accuracy and performance The Deep Learning Neural Network with R course is designed to provide learners with a comprehensive understanding of how to build and evaluate neural networks using R programming language. The course includes four modules that cover single-layer and multi-layer neural networks applied to agriculture and war datasets. Each module contains practical hands-on projects that allow learners to gain real-world experience in neural network development and evaluation. By the end of the course, learners will have a solid understanding of neural network concepts, R programming language, and practical experience with real-world datasets. Deep Learning Neural Network with R Course Curriculum Section 01: Single Layer Neural Networks Project - Agriculture (Part - 1) Section 02: Single Layer Neural Networks Project - Agriculture (Part - 2) Section 03: Multi-Layer Neural Networks Project - Deaths in wars (Part - 1) Section 04: Multi-Layer Neural Networks Project - Deaths in wars (Part - 2) How is the course assessed? Upon completing an online module, you will immediately be given access to a specifically crafted MCQ test. For each test, the pass mark will be set to 60%. Exam & Retakes: It is to inform our learners that the initial exam for this online course is provided at no additional cost. In the event of needing a retake, a nominal fee of £9.99 will be applicable. Certification Upon successful completion of the assessment procedure, learners can obtain their certification by placing an order and remitting a fee of __ GBP. £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Data analysts and scientists seeking to expand their knowledge of neural networks and R programming Professionals interested in applying neural networks to agriculture or war datasets Students and researchers interested in deep learning and machine learning techniques Anyone looking to enhance their skills in data analysis and modelling using neural networks and R programming Requirements There are no formal entry requirements for the course, with enrollment open to anyone! Career path Data Analyst Machine Learning Engineer Data Scientist Artificial Intelligence Developer Research Scientist Entry-level positions such as Data Analysts can expect to earn between £25,000 to £35,000 per annum, whereas senior-level positions such as Machine Learning Engineers can earn upwards of £70,000 per annum. Certificates Certificate of completion Digital certificate - £9 You can apply for a CPD Accredited PDF Certificate at the cost of £9. Certificate of completion Hard copy certificate - £15 Hard copy can be sent to you via post at the expense of £15.

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.

Discover the power of data science and machine learning with Python! Learn essential techniques, algorithms, and tools to analyze data, build predictive models, and unlock insights. Dive into hands-on projects, from data manipulation to advanced machine learning applications. Elevate your skills and unleash the potential of Python for data-driven decision-making.

Duration 5 Days 30 CPD hours This course is intended for This course is intended for IT Professionals who are already experienced in general Windows Server and Windows Client administration, and who want to learn more about using Windows PowerShell for administration. No prior experience with any version of Windows PowerShell, or any scripting language, is assumed. This course is also suitable for IT Professionals already experienced in server administration, including Exchange Server, SharePoint Server, SQL Server, System Center, and others. Overview After completing this course, students will be able to: Describe the functionality of Windows PowerShell and use it to run and find basic commands. Identify and run cmdlets for server administration. Work with Windows PowerShell pipeline. Describe the techniques Windows PowerShell pipeline uses. Use PSProviders and PSDrives to work with other forms of storage. Query system information by using WMI and CIM. Work with variables, arrays, and hash tables. Write basic scripts in Windows PowerShell. Write advanced scripts in Windows PowerShell. Administer remote computers. Use background jobs and scheduled jobs. Use advanced Windows PowerShell techniques. This course provides students with the fundamental knowledge and skills to use Windows PowerShell for administering and automating administration of Windows based servers. Getting Started with Windows PowerShell Overview and Background Understanding command syntax Finding commands Lab : Configuring Windows PowerShell Lab : Finding and Running Basic Commands Cmdlets for administration Active Directory administration cmdlets Network configuration cmdlets Other server administration cmdlets Lab : Windows Administration Working with the Windows PowerShell pipeline Understanding the Pipeline Selecting, Sorting, and Measuring Objects Filtering Objects Out of the Pipeline Enumerating Objects in the Pipeline Sending pipeline data as output Lab : Using the Pipeline Lab : Filtering Objects Lab : Enumerating Objects Lab : Sending output to a file Understanding How the Pipeline Works Passing the pipeline data Advanced considerations for pipeline data Lab : Working with Pipeline Parameter Binding Using PSProviders and PSDrives Using PSProviders Using PSDrives Lab : Using PSProviders and PSDrives Querying Management Information by Using WMI and CIM Understanding WMI and CIM Querying Data with WMI and CIM Making changes with WMI/CIM Lab : Working with WMI and CIM Working with variables, arrays, and hash tables Using variables Manipulating variables Manipulating arrays and hash tables Lab : Working with variables Basic scripting Introduction to scripting Scripting constructs Importing data from files Lab : Basic scripting Advanced scripting Accepting user input Overview of script documentation Troubleshooting and error handling Functions and modules Lab : Accepting data from users Lab : Implementing functions and modules Administering Remote Computers Using basic Windows PowerShell remoting Using advanced Windows PowerShell remoting techniques Using PSSessions Lab : Using basic remoting Lab : Using PSSessions Using Background Jobs and Scheduled Jobs Using Background Jobs Using Scheduled Jobs Lab : Using Background Jobs and Scheduled Jobs Using advanced Windows PowerShell techniques Creating profile scripts Using advanced techniques Lab : Practicing advanced techniques Lab : Practicing script development (optional)

Duration 5 Days 30 CPD hours This course is intended for This course is intended for IT Professionals who are already experienced in general Windows Server and Windows Client administration, and who want to learn more about using Windows PowerShell for administration. No prior experience with any version of Windows PowerShell, or any scripting language, is assumed. This course is also suitable for IT Professionals already experienced in server administration, including Exchange Server, SharePoint Server, SQL Server, System Center, and others. Overview After completing this course, students will be able to:Describe the functionality of Windows PowerShell and use it to run and find basic commands.Identify and run cmdlets for server administration.Work with Windows PowerShell pipeline.Describe the techniques Windows PowerShell pipeline uses.Use PSProviders and PSDrives to work with other forms of storage.Query system information by using WMI and CIM.Work with variables, arrays, and hash tables.Write basic scripts in Windows PowerShell.Write advanced scripts in Windows PowerShell.Administer remote computers.Use background jobs and scheduled jobs.Use advanced Windows PowerShell techniques. This course provides students with the fundamental knowledge and skills to use Windows PowerShell for administering and automating administration of Windows based servers. Getting Started with Windows PowerShell Overview and Background Understanding command syntax Finding commands Lab : Configuring Windows PowerShell Lab : Finding and Running Basic Commands Cmdlets for administration Active Directory administration cmdlets Network configuration cmdlets Other server administration cmdlets Lab : Windows Administration Working with the Windows PowerShell pipeline Understanding the Pipeline Selecting, Sorting, and Measuring Objects Filtering Objects Out of the Pipeline Enumerating Objects in the Pipeline Sending pipeline data as output Lab : Using the Pipeline Lab : Filtering Objects Lab : Enumerating Objects Lab : Sending output to a file Understanding How the Pipeline Works Passing the pipeline data Advanced considerations for pipeline data Lab : Working with Pipeline Parameter Binding Using PSProviders and PSDrives Using PSProviders Using PSDrives Lab : Using PSProviders and PSDrives Querying Management Information by Using WMI and CIM Understanding WMI and CIM Querying Data with WMI and CIM Making changes with WMI/CIM Lab : Working with WMI and CIM Working with variables, arrays, and hash tables Using variables Manipulating variables Manipulating arrays and hash tables Lab : Working with variables Basic scripting Introduction to scripting Scripting constructs Importing data from files Lab : Basic scripting Advanced scripting Accepting user input Overview of script documentation Troubleshooting and error handling Functions and modules Lab : Accepting data from users Lab : Implementing functions and modules Administering Remote Computers Using basic Windows PowerShell remoting Using advanced Windows PowerShell remoting techniques Using PSSessions Lab : Using basic remoting Lab : Using PSSessions Using Background Jobs and Scheduled Jobs Using Background Jobs Using Scheduled Jobs Lab : Using Background Jobs and Scheduled Jobs Using advanced Windows PowerShell techniques Creating profile scripts Using advanced techniques Lab : Practicing advanced techniques Lab : Practicing script development (optional)