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Unlock the world of programming excellence with our 'Diploma in Python Programming' course. In this dynamic learning journey, you'll delve into the fundamental concepts of Python and emerge as a proficient Python programmer. Whether you're a novice or have some prior coding experience, this course caters to all levels of learners. You'll start with the basics, gradually working your way up to complex Python operations, data structures, and even creating a fun Rock, Paper, and Scissors project. By the end of this course, you'll have a strong grip on Python, be able to write user functions, handle exceptions, explore databases, and much more. Take your first step towards becoming a skilled Python programmer and discover the endless possibilities this versatile language offers. Learning Outcomes Master the foundational concepts of Python programming. Develop essential skills in working with strings, dates, and files using Python. Create user functions, handle exceptions, and install packages. Explore database management using SQLite and interact with the operating system. Gain the knowledge and confidence to run Python programs in different environments, including Jupyter Notebook. Why choose this Python Programming Diploma? 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 Diploma for? Aspiring programmers looking to kickstart their coding journey. Professionals seeking to expand their skill set and explore Python. Students aiming to excel in programming and computer science. Anyone curious about the power and versatility of Python as a programming language. Career path Python Programmer: £25,000 - £70,000 Data Analyst: £30,000 - £60,000 Web Developer: £25,000 - £50,000 Software Engineer: £35,000 - £80,000 Machine Learning Engineer: £40,000 - £90,000 Data Scientist: £40,000 - £70,000 Prerequisites This Diploma in Python Programming does not require you to have any prior qualifications or experience. You can just enrol and start learning. This Diploma in Python Programming 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 Module 01: Course Introduction 00:02:00 Unit 02: Getting Started with Python Module 01: Software Installation 00:02:00 Module 02: Hello World Program 00:06:00 Module 03: Input and Output 00:07:00 Module 04: Calculating Average of 5 Numbers 00:03:00 Unit 03: Conditional Branching with Python Module 01: If Loop In Python 00:06:00 Module 02: Program Using If Else part 1 00:03:00 Module 03: Program Using If Else part 2 00:08:00 Module 04: Program for Calculator 00:02:00 Module 05: Program Using For Loop 00:08:00 Module 06: For Table 00:05:00 Module 07: For loop and Mathematical Operator in Python 00:04:00 Module 08: Factorial of Number Using Python 00:06:00 Module 09: Program Using While 00:05:00 Module 10: While Loop Example 00:07:00 Module 11: Tasks for Practice 00:02:00 Unit 04: Importing external/internal library in python Module 01: Importing Library in Python 00:07:00 Unit 05: Project Rock Paper and Scissors Module 01: Rock Paper and Scissor Game 00:06:00 Unit 06: Strings Operation in Python Module 01: Program Using String part 1 00:05:00 Module 02: Program using String 2 00:06:00 Module 03: Program Using String 3 00:06:00 Module 04: Program Using String part 4 00:03:00 Unit 07: Date and time in Python Module 01: Use of Date and Time part 1 00:05:00 Module 02: Use of Date and Time part 2 00:05:00 Unit 08: File Handling, read and write using Python Module 01: File Handling Part 1 00:08:00 Module 02: File Handling Part 2 00:07:00 Unit 09: Data Storage Structures, Tuple, List and Dictionary Module 01: Tuple in Python Part 1 00:10:00 Module 02: Tuple in Python Part 2 00:07:00 Module 03: Using Lists part 1 00:07:00 Module 04: Using List part 2 00:12:00 Module 05: Using Lists part 3 00:06:00 Module 06: Using Lists part 4 00:08:00 Module 07: Using Lists part 5 00:02:00 Module 08: Use of Dictionary Part 1 00:04:00 Module 09: Use of Dictionary Part 2 00:05:00 Module 10: Use of Dictionary Part 3 00:08:00 Module 11: Use of Dictionary Part 4 00:07:00 Unit 10: Writing user functions in Python Module 01: Function in Python Part 1 00:06:00 Module 02: Function in Python Part 2 00:05:00 Module 03: Function in Python Part 3 00:04:00 Module 04: Function in Python Part 4 00:07:00 Module 05: Function in Python Part 5 00:08:00 Unit 11: Sending mail Module 01: Send Email 00:09:00 Unit 12: Import Tricks in Python Module 01: Import Study part 1 00:07:00 Module 02: Import Study part 2 00:03:00 Unit 13: Import Operating System and Platform Module 01: Importing OS 00:06:00 Module 02: Import Platform 00:05:00 Unit 14: Exceptions handling in python Module 01: Exception in Python part 1 00:11:00 Module 02: Exception in Python part 2 00:07:00 Module 03: Exception in Python part 3 00:05:00 Unit 15: Installing Packages and Scheduling In Python Module 01: Installing Packages using built in package manager 00:08:00 Module 02: Scheduler in Python 00:05:00 Unit 16: Data Base In Python using sqlite Module 01: Data Base 1 00:08:00 Module 02: Data Base 2 00:09:00 Module 03: Data Base 3 00:08:00 Module 04: Data base 4 00:07:00 Module 05: Data Base 5 00:06:00 Unit 17: Running Program from Command Prompt and jupyter Notebook Module 01: IDE_1 00:05:00 Module 02: IDE_2 00:07:00 Unit 18: Conclusion Module 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 05:14:00

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

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

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.

This Diploma in Computer Science and Programming is designed to prepare you for a career as a computer programmer/programmer analyst. The course emphasises programming skills, program design techniques as well as database and systems analysis skills. You will learn the process of program design to solve real-world problems and the fundamental building blocks of a computer program. By the end of this course, you will be able to develop computer programs in a high-level computer programming language (such as Python). Why choose this course Earn an e-certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full Tutor Support on Weekdays Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of Video lessons Online study materials Certificate of Achievement Endorsed Certificate of Achievement from the Quality Licence Scheme Once the course has been completed and the assessment has been passed, all students are entitled to receive an endorsed certificate. This will provide proof that you have completed your training objectives, and each endorsed certificate can be ordered and delivered to your address for only £99. Please note that overseas students may be charged an additional £10 for postage. CPD Certificate from Janets Upon successful completion of the course, you will be able to obtain your course completion e-certificate. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Endorsement This course and/or training programme has been endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. This course and/or training programme is not regulated by Ofqual and is not an accredited qualification. Your training provider will be able to advise you on any further recognition, for example progression routes into further and/or higher education. For further information please visit the Learner FAQs on the Quality Licence Scheme website. Method of Assessment In order to ensure the Quality Licensing scheme endorsed and CPD acknowledged certificate, learners need to score at least 60% pass marks on the assessment process. After submitting assignments, our expert tutors will evaluate the assignments and give feedback based on the performance. After passing the assessment, one can apply for a certificate. Who is this course for? Diploma in Computer Science and Programming is suitable for anyone who wants to gain extensive knowledge, potential experience and expert skills in the related field. This is a great opportunity for all students from any academic backgrounds to learn more on this subject.

Unleash your data superpowers! Join our SQL Bootcamp: Database, Python & Javascript Training and go from zero to hero in record time. Did you know that SQL Training course are now among the top skills in demand worldwide? With the help of our SQL training course, you will learn how to write the same language as thousands of database experts. Enrol in this SQL course to learn how to handle huge datasets and evaluate actual data. This SQL training course is designed for students who want to become more proficient with SQL queries. You will learn about subjects including SQL fundamentals, environment setup, SQL analysis, building databases and tables, statements, and more with this package. What Courses You'll Get? Course 01: The Complete SQL from Scratch: Bootcamp Course 02: Python from Scratch Course 03: Javascript Programming for Beginners Learning Outcomes of SQL Training course Get introduced to the basics of SQL and environment setup. Learn how to create a database and table. Explore the statement basics and how to group them. Discover the most demanding programming language, Python, from scratch. Understand the fundamentals of Javascript. Key Highlights of the SQL Course: Lifetime Access to All SQL Learning Resources An Interactive, Online SQL Course Created By Experts in the SQL Field Self-Paced SQL courseand 24/7 Learning Support Free Certificate After SQL Course Completion SQL Bootcamp: Python, JavaScript, and Database Training Curriculum Breakdown: Course 01: The Complete SQL from Scratch: Bootcamp SQL Introduction Environment Setup Creating Database and Tables Statement Basics GROUP BY Statements JOINS Advanced Commands Databases and Tables Course 02: Python from Scratch Python Introduction Python Curriculum Overview Python Whats New Command line basics in python python installation Pycham-ce ide installation Setting up environment Running python code and more... Course 03: Javascript Programming for Beginners Introduction Project Files What is JavaScript? Running JS Code Variables Arithmetic Operators Conditional Statement and more... CPD 15 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This SQL course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in SQL. It is also great for professionals who are already working in SQL and want to get promoted at work. Career path Query Language Developer Server Database Manager SQL Database Administrator Python Developer Technical Consultant Project Implementation Manager Software Developer (SQL) Certificates 3 CDP Accerdited HARDCOPY Certificate Hard copy certificate - Included 3 CDP Accerdited HARDCOPY Certificate for Free. Delivery Charge: Inside the UK: £3.99 Outside UK: £9.99 3 CDP Accerdited PDF Certificate Digital certificate - Included 3 CDP Accerdited PDF Certificate for Free

SQL programming is the programming that manages data in the Relational Database Management System. The Mastering SQL Programming course aims to teach you how to optimise the accessibility and maintenance of data with the Structured Query Language SQL programming language, and gain a solid foundation for building, querying, and manipulating databases. This SQL Programming course will provide you the standard language, but also identifies deviations from the standard in two widely-used database products, Oracle and Microsoft SQL Server. You will understand SQL functions, join techniques, database objects and constraints, and will be able to write useful SELECT, INSERT, UPDATE and DELETE statements. Learn what SQL is and how to create, manipulate, and create reports from database tables from the best SQL courses. Important concepts associated with relational databases will be covered. You will run SQL commands to create database tables and define data element types. Enrol Now to start boosting your SQL skills! Key topics to be covered Stored Procedures Returning Data Testing and Debugging SQL CLR Code Dynamic SQL Column sets Learning Outcomes Know the tools for creating views with examples, columns and indexed views, creating stored procedures, testing and debugging. Learn how to create triggers, execute with result sets, use inline table valued functions, and use the multi statement function. Learn about transaction concepts, explicit transactions, and structured error handling. Understanding of different functions, data tools, database management, comparing database schemas, offline database management and much more. Master partitioning, managing partitions, querying partitions, complex querying, table expressions, efficient queries and complex queries. Why Choose this Course Earn a digital Certificate upon successful completion. Accessible, informative modules taught by expert instructors Study in your own time, at your own pace, through your computer tablet or mobile device Benefit from instant feedback through mock exams and multiple-choice assessments Get 24/7 help or advice from our email and live chat teams Full Tutor Support on Weekdays Course Design The course is delivered through our online learning platform, accessible through any internet-connected device. There are no formal deadlines or teaching schedules, meaning you are free to study the course at your own pace. You are taught through a combination of- Video lessons Online study supplies Mock tests Multiple-choice evaluation Assignment Certificate of Achievement Endorsed Certificate of Achievement from the Quality Licence Scheme Once the course has been completed and the assessment has been passed, all students are entitled to receive an endorsed certificate. This will provide proof that you have completed your training objectives, and each endorsed certificate can be ordered and delivered to your address for only £119. Please note that overseas students may be charged an additional £10 for postage. CPD Certificate of Achievement from Janets Upon successful completion of the course, you will be able to obtain your course completion e-certificate. Print copy by post is also available at an additional cost of £9.99 and PDF Certificate at £4.99. Endorsement This course and/or training programme has been endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. This course and/or training programme is not regulated by Ofqual and is not an accredited qualification. Your training provider will be able to advise you on any further recognition, for example progression routes into further and/or higher education. For further information please visit the Learner FAQs on the Quality Licence Scheme website. Method of Assessment To successfully complete the course, students will have to take an automated multiple-choice exam. This exam will be online and you will need to score 60% or above to pass the course. After successfully passing the exam, you will be able to apply for Quality Licence Scheme endorsed certificate of achievement. To verify your enhanced skills in the subject, we recommend that you also complete the assignment questions. These can be completed at any time which is convenient for yourself and will be assessed by our in-house specialised tutors. Full feedback will then be given on your current performance, along with any further advice or support. Who is this course for? Anyone who wants to gain extensive knowledge, potential experience and expert skills in SQL programming. Those who have an interest in production planning. Students from any academic backgrounds

The course covers data science and machine learning with R.

You will learn everything you need to know about JavaScript in this course.