Course Tracks
AI Tools & Workflow
Practical AI tooling, prompt engineering, and automation workflows for professionals who need to use AI effectively in real work environments.
What you'll learn
From Prompts to Production Workflows
This track covers how senior engineers actually integrate AI tools into their day-to-day work — not demo environments, not toy examples.
Prompt Engineering
Systematic prompt design, chain-of-thought, few-shot learning, and managing prompt templates at production scale.
LLM API Integration
OpenAI, Anthropic, and open-source LLMs in real applications. Rate limiting, error handling, cost control, and observability.
AI-Assisted Development
Copilot, Cursor, and Claude API used the way senior engineers use them — for code review, documentation, test generation, and refactoring.
RAG & Knowledge Systems
Retrieval-augmented generation pipelines — chunking, embeddings, vector stores, and reranking for real internal knowledge systems.
Agentic Patterns
Tool use, function calling, and multi-step agent design. Build agents that work reliably in production, not just in notebooks.
Workflow Observability
Logging, tracing, and evaluation frameworks for AI-assisted workflows. Know when your AI pipeline is degrading before your users do.
Courses in this track
Available Now
Prompt Engineering for Engineers
Move beyond basic prompts. Learn systematic prompt design, chain-of-thought techniques, and production-grade prompt management for real workflows.
Intermediate
Self-Paced
AI-Assisted Development Workflows
Integrate AI coding tools into real engineering workflows. Copilot, Cursor, Claude API, and modern AI assistants used the way senior engineers actually use them day-to-day.
Intermediate
Self-Paced
LLM API Integration in Production
Build reliable applications on top of OpenAI, Anthropic, and open-source LLMs. Learn rate limits, retries, cost control, monitoring, and observability from day one.
Advanced
Self-Paced