1094 Courses in Cardiff delivered On Demand

This is a beginner-friendly video course that teaches you how to build a 2D game from scratch using Unity and C#. You will learn how to implement 2D lighting, use particle systems, program a player controller, and more. No prior experience is necessary!

This course offers an immersive experience in data analysis, guiding you from initial setup with Python and Pandas, through series and DataFrame manipulation, to advanced data visualization techniques. Perfect for enhancing your data handling and analysis skills.

A comprehensive, simple, visual guide and a super-easy course using SAS with no installation on your computer necessary. This course uses the latest SAS Studio offered through SAS OnDemand and it's completely free. 12+ hours of knowledge-packed lectures, videos, quiz questions, followed by two practical and hands-on guided exercises and projects.

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

Overview This comprehensive course on R Programming for Data Science will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This R Programming for Data Science comes with accredited certification from CPD, which will enhance your CV and make you worthy in the job market. So enrol in this course today to fast track your career ladder. How will I get my certificate? You may have to take a quiz or a written test online during or after the course. After successfully completing the course, you will be eligible for the certificate. Who is This course for? There is no experience or previous qualifications required for enrolment on this R Programming for Data Science. It is available to all students, of all academic backgrounds. Requirements Our R Programming for Data Science is fully compatible with PC's, Mac's, Laptop, Tablet and Smartphone devices. This course has been designed to be fully compatible with tablets and smartphones so you can access your course on Wi-Fi, 3G or 4G. There is no time limit for completing this course, it can be studied in your own time at your own pace. Career Path Having these various qualifications will increase the value in your CV and open you up to multiple sectors such as Business & Management, Admin, Accountancy & Finance, Secretarial & PA, Teaching & Mentoring etc. Course Curriculum 23 sections • 129 lectures • 06:25:00 total length •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?: 00:01:00 •Engine and coding environment: 00:03:00 •Installing R and RStudio: 00:04:00 •RStudio: A quick tour: 00:04:00 •Arithmetic with R: 00:03:00 •Variable assignment: 00:04:00 •Basic data types in R: 00:03:00 •Creating a vector: 00:05:00 •Naming a vector: 00:04:00 •Vector selection: 00:06:00 •Selection by comparison: 00:04:00 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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 •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 •Mathematical functions: 00:05:00 •Data Utilities: 00:08:00 •Additional Materials: 00:00:00 •grepl & grep: 00:04:00 •Metacharacters: 00:05:00 •sub & gsub: 00:02:00 •More metacharacters: 00:04:00 •Additional Materials: 00:00:00 •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 •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 •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 •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 - R Programming for Data Science: 00:00:00

The Complete AutoLISP Programming Online Course teaches you how to use AutoLISP to customise AutoCAD. It breaks down the rules, commands, and logic needed to write smart scripts and automate tasks in AutoCAD. You’ll learn through clear lessons and hands-on projects, making the process easy even if you’re new to programming. By the end, you’ll be able to write your own AutoLISP programs and speed up your design workflow. Course Curriculum ✓ Unit 01: Introduction ✓ Unit 02: Quick Win Demo ✓ Unit 03: AutoLISP Rules ✓ Unit 04: AutoLISP Variables ✓ Unit 05: AutoLISP Math Functions ✓ Unit 06: AutoLISP's List Functions ✓ Unit 07: AutoLISP's User Input Functions ✓ Unit 08: Object Handling Functions ✓ Unit 09: AutoLISP's Selection Sets ✓ Unit 10: Conditionals and Equality Functions ✓ Unit 11: AutoCAD Objects - Data Model ✓ Unit 12: Symbol Table and Dictionary Handling Functions ✓ Unit 13: Hands-On Projects ✓ Unit 14: Conclusion Learning Outcomes Understand how AutoLISP works in AutoCAD. Use variables and functions in AutoLISP. Perform maths operations using AutoLISP. Work with lists to handle multiple values. Get and process user input through code. Handle objects and selection sets in drawings. Use conditionals to add logic to your code. Access and edit AutoCAD data models. Use symbol tables and dictionaries. Build and test real-world AutoLISP projects. Who is this course for? This course is for AutoCAD users, drafters, and design professionals who want to automate tasks and save time. It's also great for students and engineers who want to add coding to their skillset in a simple and direct way. Eligibility Requirements You should have basic AutoCAD knowledge. No coding experience is needed—this course teaches everything step by step. Career Path After completing this course, you can work as a CAD Programmer, AutoCAD Customisation Specialist, CAD Technician, or Technical Drafter. These roles often need people who can build scripts and tools to boost design productivity. (Learn more about this online course)

Build modern responsive websites and UIs with Sass, and get started with exploring Flex and CSS Grid

Learning Objectives Introduction , Interviewing Pitfalls , Before the Interview , During the Interview , After the Interview , Conclusion   Pre-Requisites There are no prerequisites for this course.   Description One of the most important decisions a company can make is hiring new employees. Good hiring decisions can make or break teams and can have a direct impact on a company's bottom line. Additionally, increasing diversity in hiring is about more than simple fair hiring practices. Research shows diverse teams make faster decisions and are more innovative. This class is designed to assist managers, supervisors, and HR staff in improving interviewing skills. Course Introduction Introduction 00:02:00 Section 01 Lesson 01: What is Unconscious Bias 00:05:00 Lesson 02: Overcoming Unconscious Bias 00:03:00 Section 02 Lesson 01: Creating the Job Description 00:03:00 Lesson 02: Planning the Questions 00:03:00 Lesson 03: Building a Scorecard 00:02:00 Lesson 04: Preparing for the Interview 00:02:00 Section 03 Lesson 01: Setting Candidates at Ease 00:01:00 Lesson 02: Conducting the Interview 00:03:00 Lesson 03: Selling the Job 00:02:00 Section 04 Lesson 01: Making the Big Decision 00:02:00 Course Recap Recap 00:01:00

This course will help you learn the programming fundamentals with Python 3. It is designed for beginners in Python and is a complete masterclass. This course will help you understand Python GUI, data science, full-stack web development with Django, machine learning, artificial intelligence, Natural Language Processing, and Computer Vision.

Embark on a transformative Python web development journey with this course and dive deep into creating a dynamic book rental system from scratch. Master Django's import-export capabilities, design elegant UI with Tailwind CSS, implement advanced features, and more. Elevate your skills and build real-world applications effortlessly!