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Explore AI Engineering Full Course for Beginners | LLMs, RAG, LangChain, Agents & GenAI with 180,019 views, 3,158 likes, and 1,799 comments. Experience the impact of this video content that has captured audience attention.

🚀 AI Engineering Full Course for Beginners | LLMs, RAG, LangChain, AI Agents & Hugging Face Learn AI Engineering and Generative AI from the ground up. This complete hands-on course covers AI, Machine Learning, Deep Learning, Transformers, Foundation Models, LLMs, LangChain, RAG, Prompt Engineering, AI Agents, CrewAI and Hugging Face. 💻 COURSE CODE & EXAMPLES 👉 Official GitHub Repository: https://github.com/TechWithMala/ai-engineering-full-course-for-beginners Companion code and examples are organized by course module. Follow the lessons and practice with the corresponding code as you progress. 🎯 WHAT YOU'LL LEARN 🤖 AI & TRANSFORMERS • AI, ML, Deep Learning & Generative AI • AI history and evolution • Transformers, Encoder, Decoder & Attention 🧠 FOUNDATION MODELS & LLMs • Foundation Models and their evolution • Applications, types and popular models • LLM benchmarks and model selection • Responsible AI 🔗 LANGCHAIN • LangChain architecture and components • Chains, agents, tools and memory • Build practical LLM applications 📚 RAG • RAG architecture and implementation • Document processing and embeddings • Vector databases and retrieval • Text chunking strategies ✨ PROMPT ENGINEERING • Basic prompting • Role-Task-Context prompting • Few-shot prompting • Chain of Thought • Constrained outputs 🤝 AI AGENTS & MULTI-AGENT SYSTEMS • Tools and AI agents • CrewAI + LangChain • Web scraping, email, trading, math and SQL agents • Apify and multi-agent workflows 🤗 HUGGING FACE • Text summarization • Image understanding • Translation • Sentence embeddings 👨‍💻 PRACTICAL PROJECTS Build RAG applications, vector database systems, LangChain chains, SQL agents, web scraping agents, email and trading workflows, CrewAI multi-agent systems and Hugging Face applications. 🎓 WHO IS THIS FOR? Beginners, Python developers, software engineers, data scientists, ML/AI professionals, LLM developers and aspiring AI Engineers. Basic Python knowledge is recommended. No advanced AI knowledge is required. 🧭 AI ENGINEERING ROADMAP AI → ML → Deep Learning → Transformers → Foundation Models → LLMs → LangChain → RAG → Prompt Engineering → Memory → Chains → AI Agents → Multi-Agent Systems → CrewAI → Hugging Face ⏱️ COURSE TIMESTAMPS 00:00 – Introduction to AI, ML, Deep Learning & Generative AI 15:14 – History of Artificial Intelligence 16:32 – Attention Mechanism | Encoder 44:19 – Attention Mechanism | Decoder 1:09:05 – History of Foundation Models 1:12:29 – What Are Foundation Models? 1:16:12 – Applications of Foundation Models 1:17:09 – Types of Foundation Models 1:21:33 – Examples of Foundation Models 1:29:41 – LLM Benchmarks & Model Selection 1:37:53 – Ethical & Responsible AI 1:56:24 – LangChain Introduction 2:04:45 – LangChain Deep Dive 2:18:29 – RAG Explained 2:28:23 – Build a RAG Question-Answering System 3:19:07 – Vector Databases 3:29:05 – Text Chunking Methods 3:48:17 – Chunking Best Practices 3:51:14 – Character Text Splitter Demo 3:59:51 – Recursive Character Text Splitter Demo 4:06:08 – Markdown Header Text Splitter Demo 4:12:56 – Token Text Splitter Demo 4:20:06 – Prompt Engineering Introduction 4:26:42 – Basic Prompt Demo 4:40:12 – Role-Task-Context Prompting 4:50:27 – Few-Shot Prompting 4:59:00 – Chain of Thought Prompting 5:08:40 – Constrained Output Prompting 5:16:03 – Document Loaders: CSV, HTML & PDF 5:33:04 – LangChain Memory 5:36:45 – Conversation Buffer Memory 5:56:28 – Conversation Buffer Window Memory 6:07:41 – Conversation Summary Memory 6:21:24 – LangChain Chains 6:26:03 – Single Chain Demo 6:40:33 – Simple Sequential Chain 6:59:02 – Employee Performance Review 7:12:11 – Academic Questions 7:23:25 – MathChain Explained 7:30:29 – MathChain Project Demo 7:38:33 – RAG Chain 7:54:02 – Router Chain 8:09:02 – LLMRouter Chain 8:18:14 – SQL Chain 8:23:24 – Multi-Agent Frameworks & AI Agent Systems 8:30:20 – CrewAI Introduction 8:34:23 – CrewAI Components Deep Dive 8:40:45 – CrewAI + LangChain Tools 8:46:02 – CrewAI Web Scraping Agent 9:08:15 – CrewAI Personalized Email Agent 9:33:56 – CrewAI Financial Trading Agent 10:03:29 – Web Scraping with Apify 10:16:29 – AI Agents with Math Tools 10:33:50 – SQL Agent with LangChain & SQLAlchemy 10:57:27 – Hugging Face & Text Summarization 11:13:38 – Image Understanding & Visual Q&A 11:22:31 – Sentence Translation with Hugging Face 11:28:26 – Text Summarization with Transformers 11:31:28 – Sentence Embeddings with Hugging Face 🚀 START YOUR AI ENGINEERING JOURNEY Learn modern AI concepts and build practical Generative AI applications with Transformers, LLMs, RAG, LangChain, AI Agents, CrewAI and Hugging Face. 🔔 SUBSCRIBE TO TECH WITH MALA Practical tutorials and hands-on projects covering AI Engineering, Generative AI, LLMs, RAG, AI Agents, LangChain, LangGraph and modern AI technologies. 👍 Like the video 💬 Comment with the AI topic you'd like to see next #AIEngineering #GenerativeAI #LLM #LangChain #RAG #AIAgents #CrewAI #HuggingFace

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