What you'll learn:
- Master the architecture and workflow of a RAG system for processing PDFs and multimodal data.
- Master the Fundamentals of AI, Machine Learning and Deep Learning (Basics)
- Master LangChain tools, frameworks, and workflows, including embedding techniques and retrievers.
- Fine-tuning models with OpenAI, LoRA, and other techniques to customize AI responses.
- Develop AI-driven applications with advanced RAG techniques, multimodal search, and AI agents for real-world use cases.
Become an AI Engineer and master Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), AI agents, and vector databases in this comprehensive hands-on course.
Whether a beginner or an experienced developer, this course will take you from zero to hero in building real-world AI-powered applications.
This course combines deep theoretical insights with hands-on projects, ensuring you understand AI model architectures, development and optimization strategies, and practical applications.
What You’ll Learn:
Deep Learning & Machine Learning Foundations
Understand neural networks, activation functions, transformers, and the evolution of AI.
Learn how modern AI models are trained, optimized, and deployed in real-world applications.
Master Large Language Models (LLMs) & Transformer-Based AI
Deep dive into OpenAI models, and open-source AI frameworks.
Build and deploy custom LLM-powered applications from scratch.
Retrieval-Augmented Generation (RAG) & AI-Powered Search
Learn how AI retrieves knowledge using vector embeddings, FAISS, and ChromaDB.
Implement scalable RAG systems for AI-powered document search and retrieval.
LangChain & AI Agent Workflows
Build AI agents that autonomously retrieve, process, and generate information.
Fine-Tuning LLMs & Open-Source AI Models
Fine-tune OpenAI, and LoRA models for custom applications.
Learn how to optimize LLMs for better accuracy, efficiency, and scalability.
Vector Databases & AI-Driven Knowledge Retrieval
Work with FAISS, ChromaDB, and vector-based AI search workflows.
Develop AI systems that retrieve and process structured & unstructured data.
Hands-on with AI Deployment & Real-World Applications
Build AI-powered chatbots, multimodal RAG applications, and AI automation tools.
Who Should Take This Course?
Aspiring AI Engineers & Data Scientists – Looking to master LLMs, AI retrieval, and search systems.
Developers & Software Engineers – Who want to integrate AI into their applications.
Machine Learning Enthusiasts – Seeking a deep dive into AI, GenAI, and AI-powered search.
Tech Entrepreneurs & Product Managers – Wanting to build AI-driven SaaS products.
Students & AI Beginners – Who need a structured, step-by-step path from beginner to expert.
Course Requirements
No prior AI experience required – the course takes you from beginner to expert.
Basic Python knowledge (recommended but not required - Python Fundamentals Included in the course).
Familiarity with APIs & JSON is helpful but not mandatory.
A computer with internet access for hands-on development.
Why Take This Course?
Comprehensive AI Training: Covers LLMs, RAG, AI Agents, Vector Databases, Fine-Tuning.
Hands-On Projects: Every concept is reinforced with real-world AI applications.
Up-to-Date & Practical: Learn cutting-edge AI techniques & tools used in top tech companies.
Zero to Hero Approach: Designed for absolute beginners & experienced developers alike.
Master AI Engineering and become an expert in GenAI, LLMs, and RAG today.
