Overview
Why this master class matters
Most developers can write code.
Very few know how to build and deploy AI systems that survive production.
The real challenges developers face:
- 1. AI models work in labs but fail in real applications
- 2. Integrating LLMs and AI models into existing systems is confusing
- 3. Production deployment, scaling, and security are afterthoughts
- 4. Companies now expect developers to be AI-ready
This master class shows how AI systems are actually built and deployed in production — LIVE.
What you’ll gain (clear outcome)
- 1. Understand what AI Engineers actually do day-to-day
- 2. See Python used to interact with modern AI models (live coding)
- 3. Learn how to integrate AI into real application workflows
- 4. Know when to use Azure AI vs. AWS AI for real projects
- 5. Get a clear, actionable roadmap to transition into AI roles
This is how companies expect developers to work with AI today.
Master class agenda
- 1. Developer ? AI Engineer: Skills that matter
- 2. Live Demo: Python for AI & Model Integration
- 3. Live Demo: Build Production-Ready AI Models
- 4. Azure AI vs AWS AI: Choosing the right stack
- 5. The AI Engineer Roadmap & Career Transition
Key takeaways
- 1. Clarity on the AI Engineer role and required skills
- 2. Practical understanding of AI integration & deployment
- 3. Actionable roadmap to transition into AI engineering
- 4. Confidence to start building AI-powered features immediately
Who should attend
- 1. Software Developers (.NET / Java / Python)
- 2. Backend & Full-Stack Engineers
- 3. Cloud Developers (Azure / AWS)
- 4. Tech Leads planning their next career move
