Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
9 Hour(s) 23 Minute(s)
Language
English
Taught by
Justin Coleman, Tim Reynolds
Rating
Course Overview
COMPLETELY REDONE - The only comprehensive guide to LLMs. Master Agentic AI, Reasoning Models (o3), Fine-Tuning, and RAG
Unlock the Next Generation of AI: Master GPT-5, o3, and the Agentic Revolution!
(Freshly Updated for 2026! Covers the latest "Reasoning" models and Autonomous Agents)
Are you ready to move beyond basic chatbots and master the intelligence engines that are reshaping the world? Welcome to "LLM Mastery 2026"—your definitive launchpad into the advanced world of Large Language Models (LLMs) and Generative AI.
The AI landscape has shifted. It is no longer just about generating text; it is about Reasoning and Agency. This course takes you from the foundations of BERT and Transformers all the way to building autonomous AI Agents powered by GPT-5 and OpenAI’s o3 (Reasoning) series.
Why This Course is Your Career Accelerator in 2026: In today's market, "knowing how to use ChatGPT" is not enough. Employers and clients demand engineers who can build systems—applications that can think, plan, and execute tasks autonomously.
This course is meticulously crafted for:
Aspiring AI Engineers: Build your first "Agentic" workflow.
Data Scientists: Fine-tune open-source models (Llama 3, Mistral) on your own data.
Software Developers: Integrate "Reasoning" capabilities (o3/o1) into your apps.
Researchers & Students: Deeply understand the math behind Attention Mechanisms and Transformers.
What Awaits You Inside? We don't just teach theory; we build. You will code alongside us using PyTorch and Jupyter Notebooks.
Decode the Foundations Move beyond the hype. Understand the architecture of BERT, T5, and GPT. Learn how "Attention" changed everything and how tokens become intelligence.
Master Reasoning Models (o3 & o1) Learn the secrets behind OpenAI’s "Reasoning" models. Understand Chain-of-Thought (CoT) prompting and how to optimize for models that "think" before they speak.
Build Autonomous AI Agents The future is Agentic. Learn to build AI systems that can browse the web, write code, and use tools to solve complex problems autonomously using frameworks like LangGraph or custom Python logic.
Advanced Fine-Tuning Stop relying on generic APIs. Learn to Fine-Tune LLMs on your custom datasets to create specialized models for medical, legal, or coding tasks.
Multimodal AI & Vision Explore the frontier of Vision Transformers (ViT) and Multimodal models that can see, hear, and speak—powering the next wave of robotics and real-world AI.
Production-Grade RAG Build "Retrieval Augmented Generation" systems that don't hallucinate. Connect your LLM to live data sources, PDFs, and databases to build truly knowledgeable assistants.
Ignite Your Career & Become an AI Powerhouse:
Portfolio-Ready Projects: Build a Sentiment Analyzer, a Medical Summarization Bot, and a fully functional Autonomous Research Agent.
Interview Dominance: We cover the technical questions top tech companies ask—from "What is a Key/Query/Value vector?" to "How do you reduce hallucination?"
Future-Proof Skills: Master the tools of 2026, ensuring your skills stay relevant for years to come.
Join the Vanguard of the AI Revolution. The difference between watching the future and building it is this course. Don't let the AI revolution outpace you.
Enroll NOW to master GPT-5, o3, and the future of Agentic AI!
Course Content
- 7 section(s)
- 84 lecture(s)
- Section 1 Welcome
- Section 2 Getting Started with Large Language Models
- Section 3 Course materials - Notebooks & Data
- Section 4 Introduction to Reinforcement Learning
- Section 5 Solving Reinforcement Learning Problems with OpenAI/ChatGPT
- Section 6 Deep Reinforcement Learning Applications
- Section 7 Thank You
What You’ll Learn
- Identify and select the most suitable transformer-based model for specific NLP tasks.
- Comprehend how transformers process text and generate predictions.
- Fine-tune transformer-based models with custom datasets.
- Develop and implement actionable pipelines using fine-tuned models.
- Deploy fine-tuned models for production use.
- Perform effective prompt engineering for optimal outputs from GPT-o1 and ChatGPT.
- Understand the concepts of attention mechanisms and their application in NLP.
- Grasp the principles of transfer learning and its role in NLP.
- Utilize BERT for natural language understanding tasks.
- Conduct pre-training and fine-tuning of BERT models.
- Apply hands-on experience with BERT for various NLP tasks.
- Explore natural language generation using GPT models.
- Gain practical experience with GPT models for text generation tasks.
- Integrate BERT and GPT models for advanced NLP applications.
- Understand the fundamentals and applications of the T5 model.
- Engage in hands-on projects with T5 for different NLP tasks.
- Deploy transformer models in real-world scenarios.
- Utilize massively large language models effectively.
- Apply best practices and strategies for using ChatGPT and other LLMs in various applications.
Skills covered in this course
Reviews
-
赵赵聪聪
This course is one of the most valuable courses because it shows the tech behind the Chatgpt. I hope there're more courses like this one in Udemy.
-
NN. Ruksana Begum
Good
-
SSinan Ozdemir
A near direct ripoff of my content here: https://www.oreilly.com/library/view/introduction-to-transformer/9780137923717
-
AAmir Hassanbeik
hard to follow the speaker
