Practical course for developers and engineering professionals who want to integrate AI into their daily work, accelerate development processes, and learn how to work in an AI-native approach.
Who Is the AI Assisted Course For?
- Software Engineers (Junior–Senior)
- Team Leads and Tech Leads
- QA Engineers and Automation Specialists
- DevOps / Cloud Engineers
- Engineering Managers
- Technical specialists who want to adapt to AI-driven development
- Developers already using Copilot / ChatGPT who want to reach a new level of productivity and efficiency
What You Will Learn
- Use AI to accelerate development and routine engineering tasks
- Work with Copilot, ChatGPT, Claude, and AI coding assistants
- Generate, refactor, and analyze code with AI
- Create effective prompts for engineering workflows
- Use AI for debugging, documentation, and code review
- Automate repetitive engineering tasks
- Integrate AI into daily engineering workflows without sacrificing quality
- Understand the principles of AI-native engineering and modern development approaches
Course Program
Module 1
INTRO TO AI-ASSISTED ENGINEERING
Topic 1.1. How AI is transforming modern software development
- AI-assisted vs traditional development
- New engineering workflows
- What is AI-native engineering
- The role of engineers in the AI era
Topic 1.2. AI tools ecosystem for developers
- GitHub Copilot
- ChatGPT / Claude / Gemini
- Cursor / Windsurf / AI IDEs
- AI tools for debugging, documentation, and automation
Module 2
PROMPTING FOR ENGINEERS
Topic 2.1. Prompt engineering for developers
- Structure of engineering prompts
- Context-driven prompting
- Working with large codebases
- Multi-step prompting
Topic 2.2. AI for coding workflows
- Code generation
- Refactoring
- Unit tests
- Documentation generation
- API explanations
Module 3
AI IN DAILY ENGINEERING WORK
Topic 3.1. AI-assisted development workflow
- Sprint work with AI
- AI pair programming
- Faster prototyping
- Research and troubleshooting
Topic 3.2. Productivity & automation
- Workflow optimization
- Repetitive task automation
- AI for meetings and engineering communication
- Knowledge management
Module 4
AI-NATIVE ENGINEERING
Topic 4.1. Engineering mindset transformation
- How the engineer’s role is changing
- Human + AI collaboration
- AI limitations and risks
- Security and responsible AI usage
Topic 4.2. Future of software engineering
- Vibe coding
- AI-native teams
- New engineering roles
- How to adapt your career to the AI era
After Course
Students will gain practical competencies in:
- AI-assisted software development
- Prompt engineering for developers
- AI productivity workflows
- AI-supported debugging and code review
- Engineering automation
- AI-native development practices
- Modern AI tooling for engineers
- Faster prototyping and delivery
Recommended Background Knowledge
- Basic understanding of software development
- Experience working with code will be an advantage
- Understanding of engineering workflows
- Technical background is preferred
- Previous experience with AI tools is not required
Advanced
Junior
Middle
*If you have a personal discount promo code, please enter it in the comment field of the registration form.
Payment in installments without commission and interest is available from PrivatBank
In case of any questions, please contact the manager Sofia
