GLM 5.3 vs GLM 5.3 Flash Architecture Teardown
We read the config files and every tensor shape of GLM 5.3 and GLM 5.3 Flash without downloading the weights, and worked out why the smaller model caches eight times less for each token.
Code-first AI for production
Learn to build and deploy machine learning, RAG, and AI agent systems through practical, step-by-step projects.
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This is the only course which finally teaches how to fine-tune your own LLM.
Nicely explain different transformers and models with example notebooks.
the course has been designed in a well structured way from bert model to advanced lora qlora techniques and easy to understand the concept
This Udemy course delivered a structured learning path with clear, up-to-date resources and practical code examples.
The instructor explains in a very organised way which gives us an idea what are the fundamentals that are required.
This was a great course. I picked up a lot of new things, and the instruction was excellent. I'm really glad I enrolled.
As someone who struggled with Blender for months, this course finally made things click for me. The teaching style is simple, clear, and very engaging.
Really good course
This course is well structured, every session is easy to digest and very well explained. Kudos to the lecturer and team.
Great content, comprehensive code documentation, flow and topic selection. Laxmi provides a good learning experience.
I really like this course. It explains AI step by step in a simple and clear way. This should be the first course anyone takes to truly understand AI.
The course is very excellent especially to start learning llms.
This was a comprehensive and enjoyable course with some great projects at the end that helped reinforce the main concepts.
This is the one of the best course in this platform to automate the blender with Claude!!!!!
I have learned a lot in this course, thank you
ótimo curso para iniciar em contruções de agentes!
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Follow a sequenced roadmap instead of piecing together disconnected tutorials.
A structured, progressive roadmap for developers seeking to master AI agents, covering Python foundations, LangChain, LangGraph, and private multi-agent RAG.
A comprehensive curriculum taking you from zero programming knowledge to professional data manipulation, mathematical visualization, and core ML model building.
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We read the config files and every tensor shape of GLM 5.3 and GLM 5.3 Flash without downloading the weights, and worked out why the smaller model caches eight times less for each token.
We ran DeepSeek V4 Flash and Qwen 3.8 Flash Next, both at 1-bit, on 19 hard problems on one RTX 5090 desktop. The score gap is about finishing, not reasoning.
How a token ID becomes a vector: the embedding table, why one-hot encoding fails, what the dimensions mean, and how embeddings learn meaning during training.

Meet your instructor
I'm Laxmi Kant Tiwari, IIT Kharagpur alumnus, founder with a successful startup exit, and an engineer with 10+ years across industry and academia. Everything here is taught the way real production systems are built.
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I Ran 1-bit DeepSeek V4 Flash and Qwen 3.8 Flash Next Locally on CPU
IBM Granite 4.2 vs Qwen 3.8 27B vs Gemma 4 - Local LLM Benchmark
LangChain Tutorial for Beginners: LCEL Chains and Pipe Operator
In-Depth Courses
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Master Langchain v1, Local LLM Projects, Ollama, DeepSeek, LLAMA 3.2, Complete Integration Guide.
Agentic RAG and Chatbot, AI Agent, DeepSeek, LLAMA 3.2 Agent, FAISS Vector Database.
Build MCP servers & clients with Python, Streamlit, ChromaDB, LangChain, LangGraph agents, and Ollama integrations.
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