AI Engineering Explained: LLM, RAG, MCP, Agent, Fine-Tuning, Quantization

By the end of this session, you’ll be familiar with: • LLM • RAG • MCP • Agent • Fine-tuning • Quantization Live session on AI Engineering Overview by Amit Shekhar, Founder @ Outcome School #artificialintelligence #machinelearning #ai #llm #agent Software engineers like you join Outcome School AI and Machine Learning Program to achieve the outcome that is a high-paying tech job in AI and Machine Learning. Join Outcome School AI and Machine Learning Program: https://outcomeschool.com/program/ai-... Founder of Outcome School: Amit Shekhar About Amit Shekhar: Founder @ Outcome School • IIT 2010-14 • I have taught and mentored many developers, and their efforts landed them high-paying tech jobs, helped many tech companies in solving their unique problems, and created many open-source libraries being used by top companies. I am passionate about sharing knowledge through open-source, blogs, and videos. Connect with Amit Shekhar: X: https://x.com/amitiitbhu LinkedIn:   / amit-shekhar-iitbhu   GitHub: https://github.com/amitshekhariitbhu YouTube:    / @amitshekhar   Instagram:   / amitshekhariitbhu   Follow Outcome School: X: https://x.com/outcome_school LinkedIn:   / outcomeschool   YouTube:    / @outcomeschool   GitHub: https://github.com/OutcomeSchool Instagram:   / outcome_school  

Is RAG Still Needed? Choosing the Best Approach for LLMs
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Is RAG Still Needed? Choosing the Best Approach for LLMs

RL for Agents Workshop - Deep Dive on Training Agents with RL and Open Source
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RL for Agents Workshop - Deep Dive on Training Agents with RL and Open Source

Best Designed Public APIs (Stripe, Github, Youtube & more)
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Best Designed Public APIs (Stripe, Github, Youtube & more)

System Design Explained: APIs, Databases, Caching, CDNs, Load Balancing & Production Infra
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System Design Explained: APIs, Databases, Caching, CDNs, Load Balancing & Production Infra

How to Start Coding | Programming for Beginners | Learn Coding | Intellipaat
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How to Start Coding | Programming for Beginners | Learn Coding | Intellipaat

Why AI Tokens are so Expensive - Computerphile
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Why AI Tokens are so Expensive - Computerphile

Full Archon Guide - Build AI Coding Harnesses That Actually Ship (LIVE)
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Full Archon Guide - Build AI Coding Harnesses That Actually Ship (LIVE)

You Can Learn AI Agent Harness, Loop, LLM Ops & Eval In 19 Min | Tracing, Memory, RAG
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You Can Learn AI Agent Harness, Loop, LLM Ops & Eval In 19 Min | Tracing, Memory, RAG

Cheap AI models now tie the expensive ones. So why did this engineer spend $40?
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Cheap AI models now tie the expensive ones. So why did this engineer spend $40?

Build a Complete Medical Chatbot with LLMs, LangChain, Pinecone, Flask & AWS 🔥
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Build a Complete Medical Chatbot with LLMs, LangChain, Pinecone, Flask & AWS 🔥

Don't learn AI Agents without Learning these Fundamentals
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Don't learn AI Agents without Learning these Fundamentals

20 AI Concepts Explained in 40 Minutes
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20 AI Concepts Explained in 40 Minutes

AI Engineering in 41 Minutes: From Demo to Production
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AI Engineering in 41 Minutes: From Demo to Production

Building an AI Dark Factory:  A Codebase That Writes Its Own Code, Live
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Building an AI Dark Factory: A Codebase That Writes Its Own Code, Live

Deepseek drops another HUGE breakthrough
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Deepseek drops another HUGE breakthrough

😱 If you understand this lesson... you might get rid of anxiety, obsessive thoughts, and dissatis...
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😱 If you understand this lesson... you might get rid of anxiety, obsessive thoughts, and dissatis...

Keynote: After the AI Hype – What’s Real, and What’s Next - Richard Campbell - 2026
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Keynote: After the AI Hype – What’s Real, and What’s Next - Richard Campbell - 2026

Full body waifus, Claude Fable is back, LongCat 2.0, mind-reading AI, live video editing: AI NEWS
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Full body waifus, Claude Fable is back, LongCat 2.0, mind-reading AI, live video editing: AI NEWS

Full Walkthrough: Workflow for AI Coding — Matt Pocock
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Full Walkthrough: Workflow for AI Coding — Matt Pocock

Harnesses in AI: A Deep Dive — Tejas Kumar, IBM
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Harnesses in AI: A Deep Dive — Tejas Kumar, IBM