krishnaik06/Roadmap-To-Learn-Generative-AI-In-2025

Roadmap To Learn Generative AI In 2025

Prerequisites

1. Python Programming Language -1 Month

Python:

1. Complete Python Playlist In English:

2. Complete Python Playlist In Hindi:

3. Flask Playlist:

4. Fast API Tutorials

2. Basic Machine Learning Natural Language Processing (Day 1 - Day 5)

1. Why NLP?
2. One hot Encoding, Bag Of Words,
3. TFIDF
4. Word2vec,AvgWord2vec

3. Basic Deep Learning Concepts (Day 1- Day 5)

1. ANN - Working Of MultiLayered Neural Network
2. Forward Propogation, Backward Propogation
3. Activation Functions, Loss Functions
4. Optimizers

4. Advanced NLP Concepts (Day 6 - Last Video)

1. RNN, LSTM RNN
2. GRU RNN
3. Bidirection LSTM RNN
4. Encoder Decoder, Attention is all you need ,Seq to Seq
5. Transformers

5. Starting the Journey Towards Generative AI (GPT4,Mistral 7B, LLAMA, Hugging Face Open Source LLM Models,Google Palm Model)

1. Generative Tutorials

2. Generative Tutorials With AWS

3. Generative Tutorials With Azure

4. Genertaive AI With Google Gemini Playlist:

5. Finetuning LLM

5. Vector Databases And Vector Stores

1. ChromaDB
2. FAISS vector database, which makes use of the Facebook AI Similarity Search (FAISS) library
3. LanceDB vector database based on the Lance data format
4. Cassandra DB For storing Vectors

6. Deployment Of LLM Projects

1. AWS
2. Azure
3. LangSmith
4. LangServe
5. HuggingFace Spaces