Git & GitHub
Git training with GitHub: handle commits, branches and merge conflicts with confidence and collaborate through pull requests and code reviews.


Courses on Git, software testing, API development, test automation and AI-assisted development. Compare topics and enquire about training.
Software development covers the working practices around programming: version control, testing, APIs, automation and AI tools in development teams. The topics suit developers, testers, team leads and career changers with first programming skills. For working together on code, “Git & GitHub” fits. To safeguard quality, choose “Software testing”. For automated browser tests, there is “Playwright: automate browser workflows reliably”. Decide by your team’s bottleneck: collaboration, quality or automation. Prerequisites, scope and dates are confirmed on enquiry.
Git training with GitHub: handle commits, branches and merge conflicts with confidence and collaborate through pull requests and code reviews.
Software testing training: plan a test strategy, design targeted test cases, automate UI tests with Playwright and analyse failures properly.
Design a GraphQL interface around its users and operational needs. A fictional service catalogue provides the setting for queries, mutations, authorisation and error responses, including a review of unnecessary data-fetching costs.
Develop a small interface prototype using reusable elements and clear states. Focus on traceable design decisions and a handover that helps developers understand error and empty states as well.
Automate a role-based approval flow with Playwright. Use role locators instead of timed sleeps, and isolate browser contexts and test data for parallel runs.
Test a checkout flow using stubbed payment responses. Use stable data selectors and stub the payment API for both approved and declined transactions.
A development workshop from clear task specification to a reviewed repository change, focusing on small steps, tests and human approval.
A technical introduction to a testable AI application, focusing on interfaces, defined outputs, error handling and controlled resource use.
A development workshop for bounded agent workflows with verifiable tool calls. Exercises separate reading, proposing and approval-sensitive actions.
An independent workshop for the AI+ Developer Practitioner™ certification goal. A small data project exposes engineering decisions and individual areas for further study.
Understand code, build features, repair tests and review changes: bring ChatGPT and Codex into your development work in a controlled way.
Plan, estimate and report on testing using risk, develop your team and prepare for the ISTQB CTAL-TM v3.0 certification exam.
Test ML systems with suitable data, metrics and test cases, understand AI quality characteristics and prepare for ISTQB CT-AI v2.0.
Develop applications for OpenShift: set up the project structure, build features and APIs, then test, secure and prepare them for operation.
Use Git confidently in a team: branching strategies, pull requests, merge conflicts and code reviews for beginners who share a repository.
Write secure code and test applications: spot common vulnerabilities, write tests and add security checks to your code reviews and pipelines.
In the API design course you design interfaces, document them clearly, plan versioning and secure them with tests and a security review.
The software testing course teaches the basics: plan tests, work through small examples, isolate defects and document results in a meaningful way.
In the browser automation course you write stable web tests, track down defects systematically and document your code and the next steps.
The course shows how to automate API tests and fit them into development workflows, including debugging, security aspects and documentation.
The quality engineering course shows experienced practitioners how to embed quality assurance in agile product teams, from tests to code review.