A practical, 5-hour master lesson on AI-assisted development and DevOps practices.
May 15, 2026 | OTEAcademy – Athens, Greece
This intensive master lesson transforms how development teams leverage AI throughout the entire software development lifecycle. Participants will master Claude Code and Cursor IDE for rapid application development, documentation, and debugging, then extend these skills into automated testing and CI/CD pipelines.
The course bridges the gap between AI-assisted coding and production-ready DevOps practices.
FULL TIME
5 HOURS
IN PERSON INSTRUCTOR LED TRAINING
HANDS ON FRAMEWORKS AND USE CASES
This foundational session introduces participants to the modern AI development landscape and the role of AI pair programming in today’s engineering workflows. Attendees will gain clarity on how tools like Claude Code and Cursor IDE fit into the software lifecycle, when to use each effectively, and how they enhance developer productivity. The session walks through environment setup, API configuration, and workspace optimization, while establishing best practices for AI-assisted development. By the end, participants will have a fully configured setup and a clear understanding of how to leverage AI tools strategically in real-world projects.
Learning Objectives:
This session dives into AI-assisted full-stack development, equipping participants with the skills to generate production-quality code efficiently. Attendees will learn how to craft effective prompts for complex features, scaffold multi-file projects, and design APIs, databases, and frontend components using AI. Through practical examples—including building REST APIs, generating database schemas and migrations, creating React or Vue components, and implementing authentication flows—participants will understand how to accelerate development while maintaining structure, scalability, and code quality.
Learning Objectives:
In this session, participants will harness AI to streamline documentation for their projects. Attendees will learn to generate API docs, README files, inline comments, ADRs, and user guides automatically, ensuring documentation stays current as code evolves. By applying AI-driven strategies and prompt patterns, participants will create consistent, high-quality, and maintainable documentation that supports both development and collaboration.
Learning Objectives:
This session introduces participants to AI-assisted debugging and code improvement techniques. Attendees will learn how to quickly identify and fix bugs, interpret error messages and stack traces, detect logic or performance issues, and refactor legacy code. The focus is on understanding how AI can streamline debugging workflows, enhance code quality, and help maintain secure, efficient applications.
Learning Objectives:
In this session, participants explore Model Context Protocol (MCP) integration to extend AI capabilities with external knowledge. Attendees will learn about key MCP servers such as Microsoft Learn Context, Context7, GitHub MCP, and database MCPs, and understand their use cases for real-time documentation access and enhanced code context. The session emphasizes practical application, showing how MCPs can be configured and combined in Claude Code and Cursor to build smarter, context-aware AI-assisted features.
Learning Objectives:
This session provides an introduction to AI-powered DevOps, highlighting where AI can enhance the software development lifecycle. Participants will explore modern DevOps practices, continuous integration fundamentals, and testing strategies across unit, integration, E2E, and security levels. The session also covers GitHub Actions architecture and how AI can be leveraged for automated test generation and pipeline optimization.
Learning Objectives:
In this session, participants learn how to use AI to generate high-quality unit tests with Jest. Covering test structure, mocking, async handling, and code coverage, attendees explore AI techniques for creating edge cases, generating test data, and maintaining test reliability. By the end, they’ll be able to implement AI-assisted TDD workflows and achieve robust, maintainable code.
Learning Objectives:
This session teaches participants how to leverage AI for end-to-end (E2E) testing with Playwright. Attendees will learn browser automation, selectors, assertions, and test organization, while using AI to generate tests from user stories, handle dynamic content, and implement cross-browser and visual regression testing. By the end, participants can confidently validate complete user workflows with AI-assisted E2E tests.
Learning Objectives:
This session equips participants to use AI for automated security testing and penetration testing. Attendees will explore OWASP Top 10 risks, common web vulnerabilities, authentication testing, and dependency scanning. Using AI, they will generate security test cases, identify potential vulnerabilities, and create penetration test scripts, gaining hands-on skills to safeguard applications effectively with tools like OWASP ZAP, npm audit, and Snyk.
Learning Objectives:
In this session, participants learn to build end-to-end CI/CD pipelines using GitHub Actions, integrating AI to automate testing, builds, and reporting. Attendees explore workflow syntax, triggers, jobs, secrets, and environment management while implementing quality gates and code checks. Through practical exercises, they will leverage AI to generate workflows, optimize pipeline performance, implement caching strategies, and run parallel jobs, gaining hands-on experience in creating efficient, automated DevOps pipelines.
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