LLM Mastery: ChatGPT, Gemini, Claude, Llama3, OpenAI & APIs
LLM Mastery: ChatGPT, Gemini, Claude, Llama3, OpenAI & APIs
Basics to AI-Agents: OpenAI API, Gemini API, Open-source LLMs, GPT-4o, RAG, LangChain Apps, Colab, Prompt Engineering
Product Brand: Udemy
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Udemy Coupon Code for LLM Mastery: ChatGPT, Gemini, Claude, Llama3, OpenAI & APIs Course. Basics to AI-Agents: OpenAI API, Gemini API, Open-source LLMs, GPT-4o, RAG, LangChain Apps, Colab, Prompt Engineering
Created by Arnold Oberleiter | 19.5 hours on-demand video course
LLM Mastery Course Overview
LLM Mastery: ChatGPT, Gemini, Claude, Llama3, OpenAI & APIs
Dive into ‘LLM Mastery: ChatGPT, Gemini, Claude, Llama3, OpenAI & APIs’—where you will explore the fundamental and advanced concepts of LLMs, their architectures, and practical applications. Transform your understanding and skills to lead in the AI revolution.
This course is perfect for developers, data scientists, AI enthusiasts, and anyone who wants to be at the forefront of LLM technology. Whether you want to understand neural networks, fine-tune AI models, or develop AI-driven applications, this course offers everything you need.
This course is ideal for anyone looking to delve deeper into the world of LLMs—from developers and creatives to entrepreneurs and AI enthusiasts. Harness the transformative power of LLM technology to develop innovative solutions and expand your understanding of their diverse applications.
By the end of ‘LLM Mastery: ChatGPT, Gemini, Claude, Llama3, OpenAI & APIs’ you will have a comprehensive understanding of LLMs, their applications, and the skills to harness their power for various purposes. If you are ready to embark on a transformative journey into AI and position yourself at the forefront of this technological revolution, this course is for you.
What you’ll learn
- Functionality of LLMs: Parameters, Weights, Inference, and Neural Networks
- Understanding Neural Networks
- Operation of Neural Networks with Tokens in LLMs
- Transformer Architecture and Mixture of Experts
- Fine-Tuning and the Creation of the Assistant Model
- Reinforcement Learning (RLHF) in LLMs
- LLM Scaling Laws: GPU & Data for Improvements
- Capabilities and Future Developments of LLMs
- Use of Tools by LLMs: Calculator, Python Libraries, and More
- Multimodality and Visual Processing with LLMs
- Multimodality in Language as in the Movie ‘Her’
- Systems Thinking and Future Prospects for LLMs
- Self-Improvement after AlphaGo (Self-Improvement)
- Improvement Possibilities: Prompts, RAG, and Customization
- Prompt Engineering: Effective Use of LLMs with Chain of Thought and Tree of Thoughts Prompting & More
- Adaptation of LLMs through System Prompts and Personalization with ChatGPT Memory
- Long-Term Memory with RAG and GPTs
- The GPT Store: Everything You Need to Know
- Using GPTs for Data Analysis, PDFs, or Tetris Programming
- Embeddings and Vector Databases for RAG
- Integrating Zapier Actions in GPTs
- Open-Source vs. Closed-Source LLMs
- API Basics
- Usage of the Google Gemini API and Claude API
- Microsoft Copilot and Its Use in Microsoft 365
- GitHub Copilot: The Solution for Programmers
- The OpenAI API: Features, Pricing Models, and Everything You Need to Know About the OpenAI API Including App Creation
- Introduction to Google Colab for API Calls to OpenAI
- Creation of AI Apps and Chatbots with Langchain, Flowise, Vectorshift, LangGraph, CrewAI, Autogen, Langflow & more
- Creation of AI Agents for Various Tasks like Social Media Contetn with Agency Swarm and Langchain Agents
- Security in LLMs: Jailbreaks and Prompt Injections & more
- Comparison of the Best LLMs
- Google Gemini in Standard Interface and Google Labs with NotebookLM
- Claude by Anthropic: Overview
- Everything About Perplexity and POE
- OpenAI Playground: Features, Billing Account & Temperature of LLMs
- Google Gemini API: Video Analysis and More
- Open-Source LLMs: Models and Use of Llama 3, Mixtral, Command R+, and Many More
- HuggingChat: Interface for Open-Source LLMs
- Running Local LLMs with Ollama and Building Local Rag Chatbots
- Groq: Fastest Interface with LPU
- Installation of LM Studio for Using Local Open-Source like Llama3 LLMs for Maximum Security
- Using Open-Source Models in LM Studio and Censored vs. Uncensored LLMs
- Fine-Tuning an Open-Source Model with Huggingface
- Creating Your Own Apps via APIs in Google Colab with Dall-E, Whisper, GPT-4o, Vision, and More
- Microsoft Autogen for AI Agents
- CrewAI for AI Agents
- Flowise with LangChain Function Calling
- OpenAI Assistant API with function Calling for AI-Agents in different Frameworks
- Flowise with Open-Source LLM as ChatBot
- Security in LLMs and Methods to Hack LLMs
- Future of LLMs as Operating Systems in Robots and PCs
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Who this course is for
- To everyone who wants to learn something new and gain deep insights into LLMs
- To entrepreneurs who want to become more efficient and save money
- To individuals who are interested in AI and want to build their own models
Taught by Arnold Oberleiter
