About Generative AI

18 comprehensive lessons on building Generative AI applications, prompt engineering, RAG architectures, and fine-tuning.

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Architecture & Workflow

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Key Benefits for Modern DevOps

• Automation: Eliminates repetitive manual procedures through codified configuration.
• Reliability & Consistency: Reduces configuration drift across development, staging, and production environments.
• High Observability: Provides deep telemetry into application and infrastructure health.

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Complete Curriculum Roadmap

This comprehensive handbook covers the entire Generative AI engineering lifecycle across 4 structured modules:

Module 1: Introduction to GenAI & LLMs

• LLM Fundamentals & Architecture: Introduction to Generative AI, Exploring & Comparing LLMs

→ Explore Introduction to GenAI & LLMs

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Module 2: Prompt Engineering & Design

• Prompting Techniques & Few-Shot: Prompt Engineering Fundamentals, Advanced Prompting Patterns

→ Explore Prompt Engineering & Design

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Module 3: RAG & Vector Search

• Retrieval-Augmented Generation: Building Search & RAG Applications

→ Explore RAG & Vector Search

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Module 4: Fine-Tuning & AI Agents

• Fine-Tuning LLMs: When and How to Fine-Tune
• Building Autonomous Agents: Designing Agentic AI Workflows

→ Explore Fine-Tuning & AI Agents