Audience: Devs with experience in full-stack or backend development, and familiarity with DevOps/CI/CD and architectural best practices.
Format: Combination of theoretical sessions, practical demos, and hands-on exercises. However, we will place greater emphasis on practical usage of AI tools tailored toward coding and task automation.
Duration: 7 modules, each 2–3 hours (flexible, depending on exercise depth).
Main Goal:
Master new AI-powered coding tools and LLM frameworks that automate coding, testing, documentation, and continuous quality improvement.
Understand benchmarks and metrics to evaluate AI solutions for development and testing.
Adopt emerging workflows such as documentation-first and vibe coding and learn their benefits in professional environments.
Learn how to deploy and scale AI solutions efficiently and securely, focusing on integration with the development lifecycle rather than traditional MLOps pipelines.