Generative AI & AI Agents: From Fundamentals to Production

Course Overview

This course covers Generative AI and AI agents through 66 focused lessons organized into 10 modules. It starts with AI foundations, prompt engineering, model APIs, retrieval-augmented generation (RAG), agent systems, and deployment. The course is designed for software developers, aspiring AI engineers, and those preparing for technical interviews in AI.

Topics include AI basics, generative models, prompt design, API usage, NLP techniques, RAG pipelines, agent architectures, frameworks, and deployment strategies. Lessons feature visual explanations, examples, and PDF notes to support learning.

Key Takeaways

• Understand AI, machine learning, deep learning, and generative models.
• Design prompts and use LLM APIs with validation, memory, security, and error handling.
• Explain and evaluate RAG pipelines, embeddings, retrieval, and hallucination reduction.
• Compare AI agent architectures and frameworks; plan deployment, monitoring, and cost optimization.
• Learn API fundamentals, FastAPI, Docker, CI/CD, Kubernetes basics, and frontend integration.

Prerequisites

Basic familiarity with Python, JSON, and HTTP is recommended for API and deployment topics. A computer and internet connection are required.

Target Learners

Software developers and aspiring AI engineers interested in Generative AI applications, as well as candidates preparing for AI or Generative AI engineering interviews.