Generative AI for Developers – Comprehensive Course

freeCodeCamp.org · Intermediate ·🧠 Large Language Models ·1y ago

Key Takeaways

This video course covers Generative AI for developers, exploring large language models, data preprocessing, fine-tuning, and RAG, with hands-on projects using Hugging Face, OpenAI, and LangChain.

Original Description

In this comprehensive Generative AI course from @dswithbappy, you'll dive deep into the world of generative AI, exploring key concepts such as large language models, data preprocessing, and advanced techniques like fine-tuning and RAG. Through hands-on projects with tools like Hugging Face, OpenAI, and LangChain, you’ll build real-world applications from text summarization to custom chatbots. By the end, you'll have mastered AI pipelines, vector databases, and deployment techniques using platforms like Google Cloud Vertex AI and AWS Bedrock. 💻 Code and resources: https://github.com/entbappy/Generative-AI-Mastery-Resources Boktiar's other channel and LinkedIn: https://www.youtube.com/@CodeCommander-d6t https://www.linkedin.com/in/boktiarahmed73/ More courses: https://euron.one/ ❤️ Try interactive AI courses we love, right in your browser: https://scrimba.com/freeCodeCamp-AI (Made possible by a grant from our friends at Scrimba) ⭐️ Contents ⭐️ 0:00:00 Course Introduction 0:04:36 Introduction of the Instructor 0:05:52 Introduction to Generative AI 0:23:51 End to end Generative AI Pipeline 0:59:53 Data Preprocessing & cleaning 1:25:12 Data representation & vectorization for the model training 2:28:57 Text Classification Practical 2:42:05 Introduction to Large Language Models & its architecture 3:03:28 In depth intuition of Transformer-Attention all your need Paper 3:33:19 How ChatGPT is trained 3:43:44 Introduction of Hugging Face 3:56:02 Hands-On Hugging Face - Transformers, HF Pipeline, Datasets, LLMs 4:10:20 Data processing,Tokenizing and Feature Extraction with hugging face 4:17:34 Fine-tuning using a pretrain models 4:30:19 Hugging face API key generation 4:31:40 Project: Text summarization with hugging face 4:54:56 Project: Text to Image generation with LLM with hugging face 5:09:45 Project: Text to speech generation with LLM with hugging face 5:12:14 Introduction to OpenAI 5:21:12 How to generate OpenAI API key? 5:24:46 Local Environment Setup 5:27:13 Hands
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This comprehensive course teaches developers how to build and deploy Generative AI models using popular tools like Hugging Face and OpenAI. Students will learn about large language models, data preprocessing, and advanced techniques like fine-tuning and RAG.

Key Takeaways
  1. Introduction to Generative AI
  2. Building end-to-end Generative AI pipelines
  3. Data preprocessing and cleaning
  4. Data representation and vectorization
  5. Text classification practical
  6. Introduction to Large Language Models and architecture
  7. Fine-tuning using pre-trained models
  8. Hands-on projects with Hugging Face and OpenAI
💡 Fine-tuning pre-trained models can significantly improve the performance of Generative AI models.

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Chapters (22)

Course Introduction
4:36 Introduction of the Instructor
5:52 Introduction to Generative AI
23:51 End to end Generative AI Pipeline
59:53 Data Preprocessing & cleaning
1:25:12 Data representation & vectorization for the model training
2:28:57 Text Classification Practical
2:42:05 Introduction to Large Language Models & its architecture
3:03:28 In depth intuition of Transformer-Attention all your need Paper
3:33:19 How ChatGPT is trained
3:43:44 Introduction of Hugging Face
3:56:02 Hands-On Hugging Face - Transformers, HF Pipeline, Datasets, LLMs
4:10:20 Data processing,Tokenizing and Feature Extraction with hugging face
4:17:34 Fine-tuning using a pretrain models
4:30:19 Hugging face API key generation
4:31:40 Project: Text summarization with hugging face
4:54:56 Project: Text to Image generation with LLM with hugging face
5:09:45 Project: Text to speech generation with LLM with hugging face
5:12:14 Introduction to OpenAI
5:21:12 How to generate OpenAI API key?
5:24:46 Local Environment Setup
5:27:13 Hands
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