2686 Code courses in London delivered Online

Do you need a qualification in data protection or are you thinking about learning more about data protection for your organisation? The BCS Practitioner Certificate in Data Protection designed for those with some data protection responsibilities in an organisation and wish to achieve and demonstrate a broad understanding of the law and progresses from what is taught in the BCS Foundation Certificate in Data Protection.

A beginner-level course that will help you learn all you need to know about building applications using Python 3, FAST API, MongoDB, and NoSQL as well as front-end technologies such as HTML, CSS, JSX, and REACT JS with live demonstrations. You need to know the basics of HTML, CSS, and JavaScript to get started

In the fast-paced world of data science and machine learning, you have to stay up-to-date and keep ahead of the competition. For this, you have to constantly be on the lookout for the latest trends in tools and techniques for data science and machine learning. You don't want to miss out on the latest trend and the tool of the future! Right now, that tool is the Julia programming language. It's the hot new language that all ML and data science experts are very excited about. Learning Julia will open up several doors for you in your career!

Learn the advanced concepts of the Laravel and Vue.js frameworks and build a complete real-world project

Do you want to know how to add interaction or dynamic content to your webpages; then this is the course for you! Multiple hands-on projects are included in this course that are designed to help you learn more about JavaScript and interacting with the DOM.

ITIL® 4 Specialist: High Velocity IT: In-House Training The ITIL® 4 Specialist: High-Velocity IT module is part of the Managing Professional stream for ITIL® 4. Candidates need to pass the related certification exam for working towards the Managing Professional (MP) designation. This course is based on the ITIL® 4 Specialist: High-Velocity IT exam specifications from AXELOS. With the help of ITIL® 4 concepts and terminology, exercises, and examples included in the course, candidates acquire the relevant knowledge required to pass the certification exam. This module addresses the specifics of digital transformation and helps organizations to evolve towards a convergence of business and technology, or to establish a new digital organization. It was designed to enable practitioners to explore the ways in which digital organizations and digital operating models function in high-velocity environments. Working practices such as Agile and Lean, and technical practices and technologies such as Cloud, Automation, and Automatic Testing are included. What You Will Learn At the end of this course, participants will be able to: Understand concepts regarding the high-velocity nature of the digital enterprise, including the demand it places on IT. Understand the digital product lifecycle in terms of the ITIL operating model. Understand the importance of the ITIL guiding principles and other fundamental concepts for delivering high-velocity IT. Know how to contribute to achieving value with digital products. Course Introduction Let's Get to Know Each Other Course Learning Objectives Target Audience Characteristics ITIL® 4 Certification Scheme Course Components Course Agenda Module-End Exercises Exam Details Introduction to High-Velocity IT High-Velocity IT Digital Technology Digital Organizations Digital Transformation High-Velocity IT Approaches Relevance of High-Velocity IT Approaches High-Velocity IT Approaches in Detail High-Velocity IT Operating Models Introduction ITIL® Perspective High-Velocity IT Aspects High-Velocity IT Applications ITIL® Building Blocks for High-Velocity IT Digital Product Lifecycle Service Value Streams Four Dimensions of Service Management ITIL® Management Practices High-Velocity IT Culture Key Behavior Patterns ITIL® Guiding Principles Supporting Models and Concepts for Purpose Ethics Design Thinking Supporting Models and Concepts for People Reconstructing for Service Agility Safety Culture Stress Prevention Supporting Models and Concepts for Progress Working in Complex Environments Lean Culture ITIL® Continual Improvement Model High-Velocity IT Objectives and Techniques High-Velocity IT Objectives High-Velocity IT Techniques Techniques for Valuable Investments Prioritization Techniques Minimum Viable Products and Services Product / Service Ownership A/B Testing Techniques for Fast Developments Basic Concepts Related to Fast Development Infrastructure as Code Reviews Continual Business Analysis Continuous Integration / Continuous Delivery (CI/CD) Continuous Testing Kanban Techniques for Resilient Operations Introduction to Resilient Operations Technical Debt Chaos Engineering Definition of Done Version Control Algorithmic IT Operations ChatOps Site Reliability Engineering (SRE) Techniques for Co-created Value Basic Concepts of Co-created Value Service Experience Techniques for Assured Conformance DevOps Audit Defense Toolkit DevSecOpsPeer Review

Learn to use cutting-edge language models ChatGPT, Dalle-2, and Midjourney to create high-quality written content and generative art in this course. Discover how to fine-tune these models for specific tasks and explore the ethical implications and future-proofing strategies for using AI in your work.

Overview This comprehensive course on Machine Learning for Predictive Maps in Python and Leaflet will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Machine Learning for Predictive Maps in Python and Leaflet 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 Machine Learning for Predictive Maps in Python and Leaflet. It is available to all students, of all academic backgrounds. Requirements Our Machine Learning for Predictive Maps in Python and Leaflet 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 Learning this new skill will help you to advance in your career. It will diversify your job options and help you develop new techniques to keep up with the fast-changing world. This skillset will help you to- Open doors of opportunities Increase your adaptability Keep you relevant Boost confidence And much more! Course Curriculum 9 sections • 33 lectures • 05:59:00 total length •Introduction: 00:10:00 •Python Installation: 00:04:00 •Creating a Python Virtual Environment: 00:07:00 •Installing Django: 00:09:00 •Installing Visual Studio Code IDE: 00:06:00 •Installing PostgreSQL Database Server Part 1: 00:03:00 •Installing PostgreSQL Database Server Part 2: 00:09:00 •Adding the settings.py Code: 00:07:00 •Creating a Django Model: 00:10:00 •Adding the admin.py Code: 00:21:00 •Creating Template Files: 00:10:00 •Creating Django Views: 00:10:00 •Creating URL Patterns for the REST API: 00:09:00 •Adding the index.html code: 00:04:00 •Adding the layout.html code: 00:19:00 •Creating our First Map: 00:10:00 •Adding Markers: 00:16:00 •Installing Jupyter Notebook: 00:07:00 •Data Pre-processing: 00:31:00 •Model Selection: 00:20:00 •Model Evaluation and Building a Prediction Dataset: 00:11:00 •Creating a Django Model: 00:04:00 •Embedding the Machine Learning Pipeline in the Application: 00:42:00 •Creating a URL Endpoint for our Prediction Dataset: 00:06:00 •Creating Multiple Basemaps: 00:09:00 •Creating the Marker Layer Group: 00:10:00 •Creating the Point Layer Group: 00:12:00 •Creating the Predicted Point Layer Group: 00:07:00 •Creating the Predicted High Risk Point Layer Group: 00:12:00 •Creating the Legend: 00:09:00 •Creating the Prediction Score Legend: 00:15:00 •Resource: 00:00:00 •Assignment - Machine Learning for Predictive Maps in Python and Leaflet: 00:00:00

Complete Python training course description Python is an agile, robust, expressive, fully objectoriented, extensible, and scalable programming language. It combines the power of compiled languages with the simplicity and rapid development of scripting languages. This course covers Python from the very basics of 'hello world!' through to object oriented programming and advanced topics such as multi threading. Hands on follows all the major sections in order to reinforce the theory. What will you learn Read Python programs. Write Python programs. Debug Python programs. Use Python's objects and memory model as well as its OOP features. Complete Python programming training course details Who will benefit: Anyone wishing to learn Python. Prerequisites: None. Duration 5 days Complete Python programming training course contents Welcome to Python: What is Python? Origins, features. Downloading and installing Python, Python manuals, comparing Python, other implementations. Getting started: Program output, the print statement, "hello world!", Program input, raw_input(), comments, operators, variables and assignment, numbers, strings, lists and tuples, dictionaries, indentation, if statement, while Loop, for loop. range(), list comprehensions. Files, open() and file() built-in functions. Errors and exceptions. Functions, Classes, Modules, useful functions. Python basics: Statements and syntax, variable assignment, identifiers, basic style guidelines, memory management, First Python programs, Related modules/developer tools. Python Objects: Other built-in types, Internal Types, Standard type operators, Standard type built-in functions, Categorizing standard types, Unsupported types. Numbers: Integers, Double precision floating point numbers, Complex numbers, Operators, Built-in and factory functions, Other numeric types. Sequences: strings, lists, and tuples: Sequences, Strings, Strings and operators, String-only operators, Built-in functions, String built-in methods, Special features of strings, Unicode, Summary of string highlights, Lists, Operators, Built-in functions, List type built-in methods, Special features of lists, Tuples, Tuple operators and built-in functions, Tuples special features, Copying Python objects and shallow and deep copies. Mapping and set types: Mapping Type: dictionaries and operators, Mapping type built-in and factory functions, Mapping type built-in methods, Dictionary keys, Set types, Set type operators, Built-in functions, Set type built-in methods. Conditionals and loops: If, else and elif statements, Conditional expressions, while, for, break, continue and pass statements, else statement . . . take two, Iterators and iter(), List comprehensions, Generator expressions. Files and input/output: File objects, File built-in functions [open() and file()], File built-in methods and attributes, Standard files, Command-line arguments, File system, File execution, Persistent storage modules. Errors and exceptions: What are exceptions? Detecting and handling exceptions, Context management, Exceptions as strings, Raising exceptions, Assertions, Standard exceptions, Creating Exceptions, Why exceptions, Exceptions and the sys module. Functions: Calling, creating and passing functions, formal arguments, variable-length arguments, functional programming, Variable scope, recursion, generators. Modules: Modules and files, Namespaces, Importing modules, Module import features, Module built-in functions, Packages, Other features of modules. Object-Oriented Programming (OOP): Classes, Class attributes, Instances, Instance attributes, Binding and method invocation, Static methods and class methods, Composition, Sub-classing and derivation, Inheritance, Built-in functions for classes, and other objects, Customizing classes with special methods, Privacy, Delegation, Advanced features of new-style classes (Python 2.2+), Related modules and documentation. Execution environment: Callable and code Objects, Executable object statements and built-in functions, Executing other programs. 'Restricted' and 'Terminating' execution, operating system interface. Regular expressions: Special symbols and characters, REs and Python, Regular expressions example. Network programming: Sockets: communication endpoints, Network programming in Python, SocketServer module, Twisted framework introduction. Internet client programming: What are internet clients? Transferring files, Network news, E-mail. Multithreaded Programming: Threads and processes Python, threads, and the global interpreter lock, The thread and threading Modules. GUI programming: Tkinter and Python programming, Tkinter Examples, Brief tour of other GUIs. Web programming: Web surfing with Python: creating simple web clients, Advanced Web clients, CGI: helping web servers process client data, Building CGI applications, Using Unicode with CGI, Advanced CGI, Web (HTTP) Servers. Database programming: Python database application programmer's interface (DB-API), ORMs. Miscellaneous Extending Python by writing extensions, Web Services, programming MS Office with Win32 COM, Python and Java programming with Jython.

If you are someone wishing to learn to code in Python, then this is just what you need. This course will help you build a solid foundation in coding with Python 3. It includes lots of opportunities for practice that will help put your learnings into action!