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:

  1. 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.
  2. 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.
  3. Advanced Techniques in LLMs:
    • Understand quantization and its importance.
    • Learn how to fine-tune existing LLMs with custom data.
  4. LangChain Framework:
    • Learn about LangChain, an AI framework for building chatbots and generative AI applications.
    • Recommended Resource: Code Basics channel playlist.
  5. 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).
  6. 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.
  7. 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.
  8. Deployment Skills:
    • Understand the deployment process for web applications (not covered in detail in the video).

The roadmap covers approximately 75% of the skills needed for generative AI roles, with a suggestion for further resources on deployment.

Speakers or Sources Featured:

Notable Quotes

— 07:00 — « Projects should be in a such a way that you are solving some real world problems unlike just copying from any YouTube video or any GitHub repository. »
— 07:11 — « If you're a Marvel fan, you must know Jarvis, Tony Stark's AI assistant, so I tried to build something like that only. »
— 07:44 — « This road map is almost enough for 75% of jobs that I have seen. »

Category

Educational

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