Don't learn AI Agents without Learning these Fundamentals
Video Overview & Insights
🧪AI Agents Labs for Free: https://kode.wiki/3Wh4DZ6
🔗 Free Resources mentioned:
🤖 AI Agents For Beginners → https://kode.wiki/4d7HXDJ
📦 RAG Crash Course → https://kode.wiki/42tYcoz
🔌 MCP Tutorial for Beginners → https://kode.wiki/4cvYZeE
💬 Which topic are you learning next? Drop it below! 👇
Learn everything about AI agents from scratch in this comprehensive tutorial. No prior knowledge required. We'll take you from zero to building production-ready AI systems with hands-on labs.
🎯 What You'll Learn:
Well-structured and informative presentation.
• AI Fundamentals - LLMs, tokens, embeddings, and context windows
• LangChain - Simplify AI development with pre-built components
Could you please turn on subtitles.
• Prompt Engineering - Zero-shot, few-shot, and chain-of-thought techniques
• Vector Databases - Semantic search with ChromaDB and Pinecone
Thanks for this video, really helpful to understand the fundamentals, found nothing like it on youtube so far.
• RAG (Retrieval Augmented Generation) - Build intelligent document search
• LangGraph - Create multi-step AI workflows and agents
Ai agint it's so caplcatad
• MCP (Model Context Protocol) - Connect AI to external tools
🔧 Hands-On Labs Include:
This was exactly what I needed, thanks!
✓ Making your first OpenAI API calls
✓ Building semantic search engines
OK
✓ Creating RAG systems for document retrieval
✓ Developing multi-agent workflows
Life saver! Such a nice video!!
✓ Integrating external tools with MCP
Perfect for developers, data scientists, and anyone wanting to understand modern AI development. Follow along with free labs and build a real-world AI assistant that searches 500GB of documents in under 30 seconds.
This was exactly what I needed, thanks!
🚨Start Your AI Journey with KodeKloud: https://kode.wiki/4qsrspX
⏰ TIMESTAMPS:
Best one that covered every bits of AI and its ecosystem. Thank you for putting this together. You guys great.
00:00 - Introduction to AI Agents
00:40 - How LLMs work in real time?
Very well explained. Thank you!
04:56 - Embeddings & Vector Representations
05:56 - How LangChain works?
yesssssssssssssssssssssssssssssss
10:12 - Practice Labs - Your First AI API Call
14:57 - Practice Labs - LangChain
Watching @.75 speed
17:57 - Prompt Engineering Techniques
21:21 - Practice Labs - Master Prompt Engineering
Very nice video 🎉🎉
24:46 - Vector Databases Deep Dive
31:27 - Practice Labs - Build Semantic Search Engine
cool video in addition to building the basics from scratch and connecting the whole comprehensive RAG dots and each and every library and all the workflow step by step and giving a birds eye overview within 1 hour is a herculian task covered with ice like refreshing feeling with out ovewhelming and bombarding things is a usp of this content kudos
35:15 - RAG (Retrieval Augmented Generation)
38:14 - Practice Labs - RAG Implementation
Has anyone figured out how to engineer a prompt for CoPilot's Prompt Coach agent? 🤔🤓
42:14 - LangGraph for AI Workflows
45:51 - Practice Labs - Build Stateful AI Workflow
Very good overview
48:51 - Model Context Protocol (MCP)
51:56 - Practice Labs - Advanced MCP Concepts
This filled in a lot of holes in my understanding... thank you very much!
55:21 - Conclusion
🔔 Subscribe to KodeKloud for more AI development tools and tutorials!
SKIP THIS !!
Goes too fast ... all you see is a blur of screens ... each one up no more than half a second. You won't learn anything at all in this video.
#AiAgents #AI #Aifundamentals #LangChain #MCP #LLMs #RAG #Langgraph #vectordb #promptengineering #VectorDatabases #Tutorial #kodekloud
Excellent
More User Perspectives
Guy is faster than flash.
@vamshikrishna7766Keep up the great work!
@MannyKrishnamoorthyLove this content!
@MannyKrishnamoorthyso happy i found your channel. not even halfway through the video but already learning so much! thanks for this awesome content
@reneeaishah3042veryyyyyy niceeeeeeeeeee
@suryanath8150❤
@happygirl240Amazing content! 🚀
@MayeWellmanToo advance for beginners 😢
@QuantumYugaThank you for posting this super informative video with hands on check points and exercise. i really like that real time usage of each AI concept used in Big Tech companies - like OpenAI, Spotify and Neflix along with metrics in your exercises - keep going.
@Shruti_MandaokarFantastic explanation, thank you!
@RajRaj-t3h2qI know absolutely everything in this video and still found it useful !
@damir1234567890Very well done, appreciate this video!
@ALIMOHAMED-w1r5uBOLANG MU
@ChrystDizonSuch a greater video
@iTube4Uabsolutely wonderful. Thanks for sharing!
@abramswee0.5x
@BrownMunde-e8kPeople be like, tokens? Haha
@godwinsboom❤❤
@Chung-k9kThank you for this video, very enlightening!
@TrangPhúc-m4bWhat is the IDE you are using which it can have features like tasks? It's very cool.
@sofianfadli7910Thanh you so much, you make the complicated thing become so easy to understand
@thuylinhang9469No prior knowledge required and the fellow jumps directly to reference OpenAI's sdk at 6:30. You don't explain rocket science by assuming the knowledge of relativity. Pathetic and click bait.
@sadimawsThank you guys for such an amazing outstanding video 💯
@RajRishiYadav1996Great tips, thanks for sharing!
@EucherDuffyNKOUKAThank you for this video, very enlightening!
@HauwauAbubakar-h4dThis was exactly what I needed, thanks!
@RwhcSufismGreat video! Really enjoyed it.
@IbrahimKabir-m2fAbsolutely brilliant, thank you
@kevincarey5925This is all Greek to me. I wish I was more intelligent.
@ConGamePro