Learning Path

Agentic AI Enterprise

Here's what you'll learn:

Build autonomous, reasoning AI agents using tools like LangChain, vector databases, and RAG.

Learn to design and deploy agentic workflows that plan, act, and integrate seamlessly with production systems.

Core architecture of modern AI agents through hands-on labs led by industry experts at the forefront of Agentic AI.

Enroll in this learning track and begin your journey to improving your skills.

38 Lessons

Transformer and Attention Mechanism

Master the foundations of Transformers and attention mechanisms to power AI applications. Understand tokenization, embeddings, and self-attention to enhance your AI skills.

32 Lessons

Introduction to Large Language Models

Explore large language models, their components, and challenges in enterprise. Learn embeddings, vector databases, and customization techniques for specific tasks.

40 Lessons

A Practical Introduction to Vector Databases

Unlock the power of vector databases. Explore embeddings, optimization techniques, and advanced querying methods to build effective retrieval pipelines for today's applications.

32 Lessons

Introduction to Agentic AI

Explore the evolution of Agentic AI, its capabilities, and its impact on real-world AI systems. Gain insights into building smarter, more autonomous language models.

70 Lessons

Mastering LangChain

Mastering LangChain is a course that will teach us how to build context-aware AI apps using LCEL, Runnables, memory, RAG, agents, and LangGraph through real examples in document handling and decision-making.

41 Lessons

Context Engineering

Elevate your automation skills by mastering the design of reliable, adaptive agent systems. Create workflows that respond to real-world needs and enable seamless agent collaboration.

29 Lessons

Fine-Tuning Large Language Models

Learn the core principles of LLMs with a focus on fine-tuning, transfer learning, and methods like prompt tuning, prefix tuning, and LoRA. Gain hands-on practice customizing LLMs using a Llama2 7B quantized model.

20 Lessons

Evaluation of Large Language Models

Learn how to evaluate large language models for accuracy, safety, alignment, and performance using human and automated metrics to ensure reliable, ethical, and high-quality AI systems.

19 Lessons

Final Project: Build A Multi-Agent LLM Application

Build and deploy an LLM app by choosing a project: a basic chatbot, a data-powered chatbot agent, or a chat-with-your-data app. Learn CI/CD, cloud deployment, and finish with a real project ready to scale in real scenarios.