Description
The Generative AI Bootcamp is designed for those interested in developing and implementing generative AI applications. The course helps participants learn everything from the basics of Python and AI to more advanced concepts such as foundational models, attention mechanisms, transformers, and prompt engineering. The main focus of the course is on building generative AI applications using powerful libraries such as LangChain and CrewAI. In addition, participants will learn the details of Retrieval-Augmented Generative (RAG), including input preparation, text segmentation methods, embeddings, vector storage, and similarity search. Also, concepts related to vector databases such as Pinecone, Chroma, and Weaviate, and various text segmentation methods in RAG systems are fully covered.
The course also covers important topics such as responsible AI and the importance of removing biases, and teaches how to create an OpenAI account and generate an API key. During the course, participants will learn about the types of memories for large language models (LLMs) and how the different components of LangChain connect together. This course provides a comprehensive and practical approach to mastering generative AI and its associated tools.
What you will learn
- How to download and install Anaconda Distribution, Jupyter Notebook, and Visual Studio Code, which are essential tools for AI development.
- Use Markdown capabilities in Jupyter Notebook to document and organize code.
- Install CUDA Toolkit, cuDNN, and PyTorch and enable GPU to exploit graphics processing power in AI models.
- Python basics, including introduction, installation, and import of packages, variables, identifiers, type conversion, reading input from the keyboard, control structures and loops, functions, strings, and data structures such as lists, tuples, sets, and dictionaries.
- Basic concepts of artificial intelligence, machine learning, deep learning and generative artificial intelligence and the history of artificial intelligence.
- The attention mechanism and how data is encoded and decoded by transformers, which are key components of advanced language models.
- Fundamental models, including their history, applications, types, and examples.
- The performance of language models, the top open source large language models, and how to choose the right foundational model.
- Responsible AI practices and the importance of addressing biases.
- Building productive AI applications using LangChain and RAG.
- Deep understanding of RAG (Retrieval-Augmented Generation), including input preparation, text segmentation methods, embeddings, vector storage, similarity search, and the RAG pipeline.
- Familiarity with vector databases for RAG systems such as Pinecone, Chroma, Weaviate, Milvus, and FAISS.
- And…
This course is suitable for people who:
- Developers interested in building productive AI applications using LangChain and RAG.
- Programmers who are interested in building multi-factor frameworks.
- Artificial intelligence engineers and data scientists.
Generative AI Bootcamp Course Details
- Publisher: Udemy
- Instructor: Mala H
- Training level: Beginner to advanced
- Training duration: 14 hours and 3 minutes
- Number of lessons: 72
Course headings
Generative AI Bootcamp Course Prerequisites
- We cover Python basics but prefer to have familiarity with the Python programming language.
- Access to a computer with good internet connection.
- Have access to OpenAI, Claude Anthropic, or you can use open source models
- Basic understanding on using different code editors – Jupyter notebook, VScode, etc.
Course images
Sample course video
Installation Guide
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Subtitles: None
Quality: 720p
Download link
File(s) password: www.downloadly.ir
File size
5.2 GB