Roadmap to Learn Generative AI(LLM's) In 2024 With Free Videos And Materials- Krish Naik
Summary
TLDRIn this YouTube video, Kushak introduces a roadmap for learning generative AI in 2024, focusing on large language models (LLMs) and their applications in NLP. He emphasizes the importance of understanding MLOps platforms and creating end-to-end projects to aid career transitions into data science. The video outlines prerequisites like Python, basic machine learning, and deep learning concepts, and suggests exploring frameworks like LangChain and chainlit for deployment. Kushak also covers vector databases and encourages viewers to check out his free community course to determine if generative AI is right for them.
Takeaways
- 📅 Kushak plans to focus on MLOps and Generative AI in 2024, continuing his efforts from 2023.
- 🛠️ He aims to understand various MLOps platforms and create educational content to help others transition into data science careers.
- 🔄 Kushak has covered numerous end-to-end projects and MLOps tools in his YouTube videos, benefiting many viewers.
- 🌟 He predicts that Generative AI will play a significant role in 2024, especially with the rise of LLM applications and frameworks.
- 🚀 Kushak's primary goal for 2023 was to grasp different MLOps platforms and create relevant video content.
- 📈 He is also keen on exploring Generative AI, focusing on solving use cases and understanding various frameworks and models.
- 💻 For 2024, Kushak plans to allocate 60-70% of his focus to Generative AI and the remaining 30% to MLOps platforms.
- 📝 He has created a detailed roadmap for learning Generative AI in 2024, tailored for both data analytics professionals and core developers.
- 🌐 The roadmap includes prerequisites like Python programming, basic machine learning, NLP, and deep learning concepts, along with practical implementations.
- 🔗 Kushak emphasizes the importance of understanding and implementing LLM models, like GP4, Hugging Face, and Llama, for career growth in data science.
Q & A
What is the main focus of Kushak's YouTube channel for 2024?
-The main focus for 2024 is to understand different frameworks, cloud platforms, techniques, and business use cases in the field of generative AI, with a particular emphasis on large language models (LLMs).
What was Kushak's primary goal in 2023 regarding MLOps platforms?
-Kushak's primary goal in 2023 was to understand various MLOps platforms, create videos, upgrade his skills in those areas, and provide those learnings to his audience to help them transition into data science and MLOps industries.
How does Kushak plan to allocate his focus between MLOps and generative AI in 2024?
-In 2024, Kushak plans to focus 60-70% of his efforts on generative AI and the remaining 30% on MLOps platforms.
What are some of the LLM models and platforms that Kushak mentions in the script?
-Kushak mentions LLM models like GPD-4 Turbo, MRA-7B, and Google's Gemini. He also refers to platforms like Hugging Face, OpenAI, and LangChain.
What is the significance of the roadmap to learn generative AI that Kushak created?
-The roadmap to learn generative AI is significant as it provides a structured path for learners to acquire the necessary skills and knowledge in generative AI, including prerequisites and resources for both data analytics professionals and core developers.
What are the prerequisites that Kushak suggests covering before diving into generative AI?
-The prerequisites suggested by Kushak include Python programming, basic machine learning, natural language processing, and basic deep learning concepts.
Why is Python programming language emphasized in Kushak's roadmap?
-Python is emphasized because it is widely used in the development of LLM models, and having a strong foundation in Python allows for easier access to APIs, implementation, and deployment of AI applications.
What is the role of vector databases in the context of generative AI as discussed by Kushak?
-Vector databases play a crucial role in generative AI for storing and retrieving text converted into vectors for performance optimization, which is essential for deploying LLM projects.
How does Kushak plan to help his audience apply their learnings to real-world projects?
-Kushak plans to help his audience by creating end-to-end project videos that demonstrate the deployment of generative AI models in various platforms and use cases, thus bridging the gap between theory and practical application.
What is the purpose of the free community course mentioned by Kushak?
-The free community course is designed to allow individuals to explore whether generative AI is suitable for them, providing access to videos and materials that cover the basics and applications of generative AI.
Outlines
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