2722 Code courses in London delivered Online

IELTS Crash Course (One-to-One Coaching – 8 Hours & Online Self-Paced Course – 40 Hours)

This is a complete crash course about KNIME for beginners. Here, we will learn how to do data cleaning and data preparation without any code, using KNIME. We will also cover data visualization using Tableau and Power BI Desktop. Then we will understand the predictive analytics capabilities of KNIME and finally, cover machine learning in KNIME.

Learn Orchestration and Automation in DevOps with Puppet with lectures, demos, and hands-on coding exercises

Learn how to perform security audits, penetration testing, and code auditing for modern software in the web/cloud, mobile, and desktop. This course will help you master industry standards and enable you to carry out professional assessments to secure technologies as well as communicate risks to high-level executives, management, and technical staff.

Starting with the basics, such as variables and operators, to advanced concepts, such as inheritance and encapsulation, this course covers the entire spectrum to help you gain the skills needed to start developing applications in TypeScript.

This course will help you to learn the basic concepts of Python programming. From understanding variables to functions and debugging the programs to exception handling, you will master it all with the help of engaging exercises and projects.

This course is designed for complete beginners, where you will develop iPhone applications by building five complete apps using SwiftUI 3 code and Xcode 13. You will not only build the apps but also learn how to submit and upload apps to the App Store and share your creation with the world.

Welcome to this course on SwiftUI animations iOS 16. This is a fun-to-code course with multiple hands-on projects geared toward various skill levels. Each project is marked 'Easy', 'Intermediate', or 'Advanced', allowing you to start coding projects according to your skill level and gradually move on to the higher levels when ready.

JavaScript isn't just for fancy buttons and dropdown menus anymore. It's the backbone of modern web development and a powerful tool for crafting stunning, dynamic visual stories. This course takes you on a journey through JavaScript’s core features and then introduces you to the art of data visualisation—turning raw information into meaningful, interactive charts and graphics. Whether you're looking to sharpen your programming knowledge or want to make data a little less dull, this course keeps things sharp, smart, and structured. From plotting simple graphs to building responsive dashboards, you'll explore how JavaScript pairs beautifully with libraries like D3.js and Chart.js. Everything is broken down into digestible sections—no fluff, no filler, just the essentials taught with a touch of wit and clarity. You don’t need to be a coding wizard to join in, just a willingness to learn and a screen to learn it on. This is where data gets a makeover, and JavaScript shows off its creative side. Expert Support Dedicated tutor support and 24/7 customer support are available to all students with this premium quality course. Key Benefits Learning materials of the Design course contain engaging voiceover and visual elements for your comfort. Get 24/7 access to all content for a full year. Each of our students gets full tutor support on weekdays (Monday to Friday) Course Curriculum: Introduction Getting Started Introduction to Getting Started Course Curriculum How to Get Pre-Requisites Getting Started on Windows, Linux or Mac How to ask a Great Questions FAQ's Setting up Local Development Environment What is JavaScript Choosing Code Editor Installing Code Editor(Sublime Text) Installing Code Editor(Visual Studio Code) Hello World Program Getting Output Summary JavaScript Fundamentals Introduction Internal JavaScript External JavaScript Inline JavaScript Async and defer Variables Data Types Numbers Boolean Arrays() Objects Comments Summary Strings Introduction Strings String Formatting String Methods Summary Operators Introduction Arithmetic operators Assignment operators Comparison operators Logical operators Summary Conditional Statements Introduction If statement If-else statement If-else-if statement Switch-case statement Summary Control Flow Statements Introduction While loop Do-while loop For loop Break Continue Coding Exercise Solution for Coding Exercise Summary Functions Introduction Creating a Function Function Call() Function with parameters Function Bind() Summary Data Visualization (Google Chart) Introduction How to Use Google chart script Line Graph chart Scatter plots chart Bar chart Pie chart 3D Pie chart Summary Error Handling Introduction Try-catch Try-catch-finally Summary Client-side Validations Introduction On Submit Validation Input Numeric Validation Login Form Validation Password Strength Check Validation Summary Course Assessment To simplify the procedure of evaluation and accreditation for learners, we provide an automated assessment system. Upon completion of an online module, you will immediately be given access to a specifically crafted MCQ test. The results will be evaluated instantly, and the score will be displayed for your perusal. For each test, the pass mark will be set to 60%. When all tests have been successfully passed, you will be able to order a certificate endorsed by the Quality Licence Scheme. 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 £9 for PDF Certificate and £15 for the Hardcopy Certificate within the UK ( An additional £10 postal charge will be applicable for international delivery). Who is this course for? This Master JavaScript with Data Visualization course is designed to enhance your expertise and boost your CV. Learn key skills and gain a certificate of achievement to prove your newly-acquired knowledge. Requirements This Master JavaScript with Data Visualization course is open to all, with no formal entry requirements. Career path Upon successful completion of the Master JavaScript with Data Visualization Course, learners will be equipped with many indispensable skills and have the opportunity to grab.

Unleashing the Power of Deep Learning: Mastering Neural Network with R Dive into the fascinating realm of artificial intelligence with our course, 'Deep Learning Neural Network with R.' Imagine a world where machines learn and make decisions, mimicking the intricacies of the human brain. This course is your gateway to unlocking the secrets of deep learning, focusing on neural networks implemented using the versatile R programming language. Immerse yourself in hands-on projects, from creating single-layer neural networks for agriculture analysis to mastering multi-layer neural networks for predicting deaths in wars. The journey begins with reviewing datasets and creating dataframes, leading you through running neural network code and generating insightful output plots. Join us in this captivating exploration, where coding meets creativity, and algorithms come to life. Learning Outcomes Master the fundamentals of single-layer neural networks, gaining the skills to analyze agricultural datasets effectively. Acquire proficiency in implementing multi-layer neural networks, specifically tailored for predicting outcomes in complex scenarios like deaths in wars. Develop hands-on experience in creating and manipulating dataframes for enhanced data analysis. Gain a deep understanding of neural network syntax, commands, and code execution in the R programming language. Hone your ability to generate meaningful output plots, transforming raw data into visually compelling insights. Why choose this Deep Learning Neural Network with R 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 Deep Learning Neural Network with R course for? Aspiring data scientists and analysts eager to delve into the world of deep learning. R programming enthusiasts looking to enhance their skills with practical applications. Students and professionals in computer science, statistics, or related fields. Individuals seeking to understand the implementation of neural networks in real-world scenarios. Anyone fascinated by the intersection of coding, data analysis, and artificial intelligence. Career path Machine Learning Engineer: £40,000 - £70,000 Data Scientist: £35,000 - £60,000 Artificial Intelligence Researcher: £45,000 - £80,000 Research Scientist (Machine Learning): £50,000 - £90,000 Data Analyst (AI/ML): £30,000 - £55,000 Senior AI Developer: £60,000 - £100,000 Prerequisites This Deep Learning Neural Network with R does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Deep Learning Neural Network with R 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 Section 01: Single Layer Neural Networks Project - Agriculture (Part - 1) Reviewing Dataset 00:14:00 Creating Dataframes 00:09:00 Generating Output 00:12:00 Section 02: Single Layer Neural Networks Project - Agriculture (Part - 2) Running Neural Network Code 00:11:00 Importing Dataset 00:09:00 Neural Network Plots for Hidden Layer 1 00:08:00 Section 03: Multi-Layer Neural Networks Project - Deaths in wars (Part - 1) Syntax and Commands for MLP 00:11:00 Running the Code 00:08:00 Testing for Dataframes 00:13:00 Predict Results 00:08:00 Section 04: Multi-Layer Neural Networks Project - Deaths in wars (Part - 2) Creating R Folder 00:14:00 Generating Output Plot 00:12:00 Testing and Predicting the Outputs 00:16:00