984 Programming Languages courses delivered Online

Recognised Accreditation This course is accredited by continuing professional development (CPD). CPD UK is globally recognised by employers, professional organisations, and academic institutions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. What is CPD? Employers, professional organisations, and academic institutions all recognise CPD, therefore a credential from CPD Certification Service adds value to your professional goals and achievements. Benefits of CPD Improve your employment prospects Boost your job satisfaction Promotes career advancement Enhances your CV Provides you with a competitive edge in the job market Demonstrate your dedication Showcases your professional capabilities What is IPHM? The IPHM is an Accreditation Board that provides Training Providers with international and global accreditation. The Practitioners of Holistic Medicine (IPHM) accreditation is a guarantee of quality and skill. Benefits of IPHM It will help you establish a positive reputation in your chosen field You can join a network and community of successful therapists that are dedicated to providing excellent care to their client You can flaunt this accreditation in your CV It is a worldwide recognised accreditation What is Quality Licence Scheme? This course is endorsed by the Quality Licence Scheme for its high-quality, non-regulated provision and training programmes. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Benefits of Quality License Scheme Certificate is valuable Provides a competitive edge in your career It will make your CV stand out Course Curriculum 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 00:01:00 R and RStudio Engine and Coding Environment 00:03:00 Installing R and RStudio 00:04:00 RStudio: A Quick Tour 00:04:00 Introduction to Basics Arithmetic With R 00:03:00 Variable Assignment 00:04:00 Basic data types in R 00:03:00 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 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 Factors What is Factor 00:02:00 Categorical Variables and Factor Levels 00:04:00 Summarizing a Factor 00:01:00 Ordered Factors 00:05:00 Data Frames What's a Data Frame 00:03:00 Creating a Data Frame 00:04:00 Selection of Data Frame elements 00:03:00 Conditional selection 00:03:00 Sorting a Data Frame 00:03:00 Lists Why Would You Need Lists 00:01:00 Creating Lists 00:03:00 Selecting Elements From a List 00:03:00 Adding more data to the list 00:02:00 Relational Operators Equality 00:03:00 Greater and Less Than 00:03:00 Compare Vectors 00:03:00 Compare Matrices 00:02:00 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 Conditional Statements The IF Statement 00:04:00 IF…ELSE 00:03:00 The ELSEIF Statement 00:05:00 Full Exercise 00:03:00 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 00:03:00 For Loop With Conditionals 00:01:00 Using Next and Break With For Loop 00:03:00 Functions What is 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 R Packages Installing R Packages 00:01:00 Loading R Packages 00:04:00 Different Ways To Load a Package 00:02:00 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 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 Useful Functions Mathematical Functions 00:05:00 Data Utilities 00:08:00 Regular Expressions Grepl & Grep 00:04:00 Metacharacters 00:05:00 Sub & Gsub 00:02:00 More Metacharacters 00:04:00 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 Getting and Cleaning Data Get and Set Current Directory 00:04:00 Get Data From the Web 00:04:00 Loading Flat Files 00:05:00 Loading Excel files 00:03:00 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 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 Ccomponent: 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 Supplementary Resources Supplementary Resources - Learning R Programming for Data Science 00:00:00 Certificate of Achievement Certificate of Achievement 00:00:00 Get Your Insurance Now Get Your Insurance Now 00:00:00 Feedback Feedback 00:00:00

This course first equips you with the fundamentals of Python and then progresses to teach you how to use various libraries such as NumPy, Pandas, Seaborn, Bokeh, and so on. This course contains several mini projects so that, by the end of this course, you will be equipped with the essential tools you need to become a visualization expert.

Learn Microsoft Enterprise Mobility and Security Training

This beginner's level course on Pandas acquaints you to the data analysis fundamentals using Pandas library and working with Pandas primary data structures, Series and DataFrame. Learn all about data input using indexing and filtering, data preprocessing, and handle missing values and duplicate rows to transform your data more efficiently with the help of this hands-on course.

Get hands-on with creating real-time cloth animation in Unreal Engine 4 and learn the basics of UE4 physics asset animation

This course is for you if you are already familiar with Arduino and Raspberry Pi and want to learn more about using these boards and how to combine them to make more complicated and significant projects. In this course, we will go from an intermediate level to an advanced level on both the individual boards as well as when combined and discover how to build our own unique projects using them. Discover how to combine Arduino and Raspberry Pi to create complex projects in this intermediate to advanced level course. Build unique projects with hands-on experience and take your skills to the next level. This is perfect for those familiar with both boards.

This course covers essential topics required for working with data structures and algorithms using JavaScript. From basics of data structures and algorithms to key concepts, such as arrays, lists, Big O time-space asymptomatic analysis, trees, and maps, this course will teach you everything with the help of engaging examples and activities.

This course is your guide to deep learning in Python with Keras. You will discover the Keras Python library for deep learning and learn how to use it to develop and evaluate deep learning models.

In this course, you will learn everything you need to know about working with Git and GitHub. By the end of this course, you will have the knowledge and confidence you need in order to apply for a job, work in a team, or work on open-source projects.

Introduce kids and beginners to the world of web development with our HTML and CSS Coding Course. Learn the fundamentals of coding through fun and interactive lessons. Build foundational skills in HTML for creating web content and CSS for styling websites. Whether you're a young learner or new to coding, this course provides a friendly and engaging introduction to building web pages from scratch.