Summary of "GenAI Roadmap - Job ready AI path"

Summary of "GenAI Roadmap - Job Ready AI Path"

The video presents a comprehensive roadmap for learning generative AI, focusing on the essential skills and knowledge required to become job-ready in this field. The roadmap is structured in a step-by-step format, guiding viewers through various topics and resources.

Detailed Steps and Methodology:

Natural Language Processing (NLP):
- Understand the basics of NLP and its applications.
- Learn text processing techniques:
  - Tokenization
  - Stop word removal
  - Stemming and lemmatization
  - Lower casing and punctuation removal
- Study parts of speech (POS) tagging and its applications in NLP.
- Explore named entity recognition (NER) and its significance.
- Learn text vectorization methods:
  - Bag of Words
  - TF-IDF
  - Word embeddings
- Engage in basic projects like text classification or sentiment analysis.
- Recommended Resource: Video by Krishna AA.
Large Language Models (LLMs):
- Start with the research paper "Attention is All You Need" (Google) and find explanatory videos.
- Familiarize yourself with various LLMs (both paid and open-source).
- Use resources like Hugging Face for open-source models.
- Explore running models locally using Olama.
- Learn about prompt engineering to effectively interact with LLMs.
Advanced Techniques in LLMs:
- Understand quantization and its importance.
- Learn how to fine-tune existing LLMs with custom data.
LangChain Framework:
- Learn about LangChain, an AI framework for building chatbots and generative AI applications.
- Recommended Resource: Code Basics channel playlist.
Backend Development:
- Build small chatbot projects.
- Learn backend frameworks like Django or FastAPI (recommended: FastAPI).
- Understand REST APIs and HTTP methods (GET, POST, PUT, DELETE).
- Use tools like Postman or Insomnia to test API endpoints.
- Integrate a database (MySQL, MongoDB) for data storage and retrieval.
- Learn authentication techniques (OAuth, Bearer token).
Frontend Development:
- Acquire skills in HTML, CSS, and Tailwind CSS.
- Learn JavaScript and frameworks like ReactJS, Angular, or Vue.js.
- Recommended Resource: Code with Harry for frontend tutorials.
Project Development:
- Build projects that solve real-world problems rather than replicating existing ones.
- Personal example: Building a Jarvis-like AI assistant helped the speaker secure a job.
Deployment Skills:
- Understand the deployment process for web applications (not covered in detail in the video).