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Generative AI & LLMs Level: Intermediate to Advanced 100% Free + Lab IDE

Generative AI & Large Language Models (LLMs) Engineering

Prompt Engineering, Transformers, RAG Architectures, Vector DBs, LangChain & Fine-Tuning

Master Generative AI engineering. Learn Transformer architectures, Attention mechanisms, advanced Prompt Engineering, Retrieval-Augmented Generation (RAG), Vector Databases, LangChain, and fine-tuning.

💡 Interactive Cloud IDE & Assessment

You can practice and run every code example directly in your browser with zero setup in ADV Lab Cloud IDE. Complete all chapters to earn your verified Certificate of Completion.

📚 Complete Course Syllabus & Step-by-Step Topics

Chapter 1: Generative AI Landscape & Foundation Models

Learn the fundamental theory, syntax blueprint, memory model, architectural best practices, and real-world implementation of Generative AI Landscape & Foundation Models in Generative AI & Large Language Models (LLMs) Engineering.

Includes: Definition • Syntax • Visual Diagram • Runnable Code in ADV Lab • Interview FAQs

Chapter 2: Transformer Architecture & Self-Attention Explained

Learn the fundamental theory, syntax blueprint, memory model, architectural best practices, and real-world implementation of Transformer Architecture & Self-Attention Explained in Generative AI & Large Language Models (LLMs) Engineering.

Includes: Definition • Syntax • Visual Diagram • Runnable Code in ADV Lab • Interview FAQs

Chapter 3: Prompt Engineering Patterns & Chain-of-Thought

Learn the fundamental theory, syntax blueprint, memory model, architectural best practices, and real-world implementation of Prompt Engineering Patterns & Chain-of-Thought in Generative AI & Large Language Models (LLMs) Engineering.

Includes: Definition • Syntax • Visual Diagram • Runnable Code in ADV Lab • Interview FAQs

Chapter 4: Embeddings & Vector Representations

Learn the fundamental theory, syntax blueprint, memory model, architectural best practices, and real-world implementation of Embeddings & Vector Representations in Generative AI & Large Language Models (LLMs) Engineering.

Includes: Definition • Syntax • Visual Diagram • Runnable Code in ADV Lab • Interview FAQs

Chapter 5: Vector Databases (Pinecone, Chroma, Milvus, Qdrant)

Learn the fundamental theory, syntax blueprint, memory model, architectural best practices, and real-world implementation of Vector Databases (Pinecone, Chroma, Milvus, Qdrant) in Generative AI & Large Language Models (LLMs) Engineering.

Includes: Definition • Syntax • Visual Diagram • Runnable Code in ADV Lab • Interview FAQs

Chapter 6: Retrieval-Augmented Generation (RAG) Architecture

Learn the fundamental theory, syntax blueprint, memory model, architectural best practices, and real-world implementation of Retrieval-Augmented Generation (RAG) Architecture in Generative AI & Large Language Models (LLMs) Engineering.

Includes: Definition • Syntax • Visual Diagram • Runnable Code in ADV Lab • Interview FAQs

Chapter 7: Building AI Agents with LangChain & LlamaIndex

Learn the fundamental theory, syntax blueprint, memory model, architectural best practices, and real-world implementation of Building AI Agents with LangChain & LlamaIndex in Generative AI & Large Language Models (LLMs) Engineering.

Includes: Definition • Syntax • Visual Diagram • Runnable Code in ADV Lab • Interview FAQs

Chapter 8: Function Calling & Structured Outputs

Learn the fundamental theory, syntax blueprint, memory model, architectural best practices, and real-world implementation of Function Calling & Structured Outputs in Generative AI & Large Language Models (LLMs) Engineering.

Includes: Definition • Syntax • Visual Diagram • Runnable Code in ADV Lab • Interview FAQs

Chapter 9: Fine-Tuning LLMs with LoRA and QLoRA

Learn the fundamental theory, syntax blueprint, memory model, architectural best practices, and real-world implementation of Fine-Tuning LLMs with LoRA and QLoRA in Generative AI & Large Language Models (LLMs) Engineering.

Includes: Definition • Syntax • Visual Diagram • Runnable Code in ADV Lab • Interview FAQs

Chapter 10: Deploying Production AI Systems & Guardrails

Learn the fundamental theory, syntax blueprint, memory model, architectural best practices, and real-world implementation of Deploying Production AI Systems & Guardrails in Generative AI & Large Language Models (LLMs) Engineering.

Includes: Definition • Syntax • Visual Diagram • Runnable Code in ADV Lab • Interview FAQs

❓ Frequently Asked Questions (FAQ)

Is this Generative AI & Large Language Models (LLMs) Engineering tutorial suitable for freshers?

Yes, our curriculum starts from absolute fundamentals and systematically guides you to advanced industry standards with hands-on projects.

How do I run and test Generative AI & Large Language Models (LLMs) Engineering code?

Use our integrated ADV Lab cloud editor to execute and debug code directly in your browser with zero local software installation.

Will I get a Certificate of Completion?

Yes! Upon completing the course topics and assessment, you receive a free, publicly verifiable certificate.