441 API courses in Bradford delivered On Demand

Overview This comprehensive course on Docker Training for .Net and Angular Developers will deepen your understanding on this topic. After successful completion of this course you can acquire the required skills in this sector. This Docker Training for .Net and Angular Developers 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 Docker Training for .Net and Angular Developers. It is available to all students, of all academic backgrounds. Requirements Our Docker Training for .Net and Angular Developers 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 14 sections • 74 lectures • 05:36:00 total length •Module 01: Introduction: 00:05:00 •Module 02: About Me: 00:03:00 •Module 01: Container Overview: 00:02:00 •Module 02: What are containers?: 00:02:00 •Module 03: Containers Vs Virtual Machines: 00:02:00 •Module 04: Containers inside virtual machines: 00:02:00 •Module 05: Developers Vs Ops Team: 00:02:00 •Module 06: Docker Image Vs Containers: 00:02:00 •Module 07 Installation Steps deertr: 00:05:00 •Module 08: Docker Options: 00:10:00 •Module 09: Hands on with Docker: 00:14:00 •Module 01: Creating First Docker File: 00:07:00 •Module 02: Docker Build: 00:05:00 •Module 03 Docker Run: 00:05:00 •Module 04: Docker Run complex HTML site: 00:06:00 •Module 01: Docker commands like ps, ps-a, start, stop: 00:03:00 •Module 02: Docker containers and images cleanup: 00:08:00 •Module 01: Docker Pull: 00:02:00 •Module 02: Docker Run: 00:03:00 •Module 03: Docker Logs: 00:02:00 •Module 04: Docker Inspect: 00:02:00 •Module 05: Docker Stats: 00:02:00 •Docker File Instructions: 00:02:00 •Docker File overview for DotNet App: 00:04:00 •Docker File overview for Angular App: 00:02:00 •Console App example using STDIN example: 00:06:00 •Running Console App using Dockerfile: 00:04:00 •Command Vs Entrypoint: 00:03:00 •Running ASP.NET Core app using Dockerfile: 00:04:00 •Verifying Files uploaded in docker container: 00:03:00 •Debugging Docker Container: 00:06:00 •Running Angular app in a container: 00:09:00 •Verifying files in angular container: 00:03:00 •Creating Docker Compose file: 00:06:00 •Running Docker Compose: 00:05:00 •Introduction: 00:07:00 •Docker Network Creation: 00:08:00 •Creating Container for SQL Server: 00:06:00 •Connecting Dotnet app with SQL Container: 00:05:00 •Adding Docker Compose: 00:07:00 •Dotnet App failing to connect with SQL Server container: 00:04:00 •SQL Container connected with Dotnet app: 00:02:00 •Volume with SQL Container: 00:09:00 •Project Setup: 00:03:00 •Docker File Creation: 00:07:00 •Running On HTTP: 00:04:00 •Dev Certificate Creation: 00:04:00 •Running the container: 00:03:00 •Introduction: 00:04:00 •Tye build: 00:02:00 •Tye run: 00:04:00 •Creating Frontend App using Razor Template: 00:04:00 •Creating Backend App using Web API Template: 00:04:00 •Adding Service Discovery: 00:05:00 •Tye Run with Backend and Frontend Projects: 00:04:00 •Adding Redis: 00:11:00 •Tye Run with Redis: 00:04:00 •Pushing the image on DockerHub: 00:05:00 •Azure Container Registry (ACR) creation: 00:03:00 •Push images to Azure Container Registry (ACR): 00:05:00 •Spinning up Azure Container Instances using Azure Container Registry Images: 00:05:00 •Another way of creating Azure Container Instances: 00:04:00 •Consuming ACI endpoint in angular app: 00:06:00 •Deploying container to web app: 00:04:00 •Introduction: 00:03:00 •Workfile creation: 00:04:00 •Adding steps to login into ACR: 00:06:00 •Docker build and push step: 00:04:00 •Build failure: 00:05:00 •Fixed the Issue and Deployed to ACR: 00:04:00 •SQL Server container preparation: 00:03:00 •SQL Server container creation: 00:04:00 •Connect to SQL Container and publish database schema: 00:07:00 •Thank You: 00:02:00

This intermediate-level course will help you learn how to use multi-threading and asynchronous programming to speed up programs that are heavily bottlenecked by IO operations. The course covers core concepts such as implementing multiprocessing in Python, creating various readers and schedulers, and monitoring your coding progress.

Learn to build a complete Internet of Things solution with Arduino, a SQL Database, and a web server

Experience the future of geographical analysis with our Machine Learning for Predictive Maps in Python and Leaflet course. Master the unique blend of programming, machine learning, and geographic information systems, all while honing your ability to predict and visualise spatial data in a powerful and effective way. This course offers you an unparalleled understanding of modern map creation, combined with the magic of prediction using machine learning models. Starting from the ground up, you'll be introduced to all the necessary setups and installations. After that, you will be diving into the depth of Django server-side code and front-end application code writing. The heart of the course lies in learning how to automate the machine learning pipeline, leading you to easily create predictive models.  Improve your maps with Leaflet programming, making your predictions accurate and also visually striking. By the end of this course, you will be armed with experience furnished by our comprehensive project source code and assignments, empowering you to drive data-driven decisions and insightful spatial analysis. Join us and map your way to success! Sign up today. Learning Outcomes:Upon completion of the Machine Learning course, you will be able to: Understand how to set up and install relevant software and libraries.Master Django server-side and application front-end code writing.Gain proficiency in the concepts and implementation of Machine Learning.Learn to automate Machine Learning pipelines for efficient workflows.Acquire skills in Leaflet programming for enhanced map visuals.Handle project source code effectively for real-world projects.Apply knowledge practically via assignments and gain experience. Who is this course for?This Machine Learning course is ideal for: Aspiring Data Scientists keen on harnessing geographical data.GIS professionals aiming to integrate Machine Learning into their skill set.Software Developers interested in creating geographically-focused applications.Analysts keen on enhancing their data visualisation skills with mapping. CertificationAfter studying the course materials of the Machine Learning for Predictive Maps in Python and Leaflet course, 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 have a range of certification options to choose from. You can claim a CPD Accredited PDF Certificate for £4.99, a CPD Accredited Hardcopy Certificate at £8.00, or you may choose to receive a PDF Transcript for £4.99 or a Hardcopy Transcript for £9.99. Select according to your needs, and we assure timely delivery of your chosen certificate. RequirementsThis professionally designed Machine Learning for Predictive Maps in Python and Leaflet course does not require you to have any prior qualifications or experience. It is open to everyone. You will be able to access the course from anywhere at any time. Just enrol and start learning! Career Path:Our Machine Learning course will help you to pursue a range of career paths, such as: Junior Data Analyst: £25,000 - £35,000 annually.Data Scientist: £40,000 - £60,000 annually.GIS Analyst: £30,000 - £45,000 annually.Geospatial Software Developer: £35,000 - £55,000 annually.Machine Learning Engineer: £50,000 - £80,000 annually.Lead Data Scientist (GIS speciality): £70,000 - £100,000+ annually. Course Curriculum Section 01: Introduction Introduction 00:10:00 Section 02: Setup and Installations 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 Section 03: Writing the Django Server-Side Code Adding the settings.py Code 00:07:00 Creating a Django Model 00:10:00 Adding the admin.py Code 00:21:00 Section 04: Writing the Application Front-end Code 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 Section 05: Machine Learning 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 Section 06: Automating the Machine Learning Pipeline 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 Section 07: Leaflet Programming 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 Section 08: Project Source Code Resource 00:00:00 Assignment Assignment - Machine Learning for Predictive Maps in Python and Leaflet 00:00:00

This course aims to equip you with the skills to create an operational mobile Instagram app feed using React Native and ChatGPT. Additionally, it offers comprehensive resources to develop a well-rounded project that you can showcase as a prototype upon completion. You will use all the latest and trending tools for application development from scratch.

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Learn how to build real-world applications using Spring Framework 5 and Spring Boot 2

This course helps you prepare for your CISSP certification. In this course, we will be discussing CISSP? Certification Domain 8 - Software Development Security. This course focuses on how to secure software as we develop it. Domain 8 makes up 11% of the exam questions.

Enhance your coding skill set by learning Java multithreading and parallel programming. Figure out common problems such as debugging codes, splitting a problem into multiple independent pieces, and measuring the runtime and performance of your code. Save time and avoid going into the same pitfalls while learning multithreading.

The course focuses on the five domains that should be known for the CompTIA PenTest+ PT0-002 exam. Learn to successfully plan and scope a pen test engagement with a client, find vulnerabilities, exploit them to get into a network, then report on those findings to the client with the help of this comprehensive course.