Hey guys, welcome to Analytics Vidya. In our last genre TVI roadmap video, we talked about how you can get started as an absolute beginner and become a user or a super user of generative AI. In this part 1 video of the generative AI roadmap, we will discuss how you can go beyond being an end user and become a developer in the field of generative AI.
If you are a student looking to prepare yourself for future jobs, or if your current role demands more than just being an end user of generative AI tools, this roadmap is for you. We will also touch upon how you can further become a researcher in the field of generative AI.
To become a developer in generative AI, you need to master prompt engineering and have a deep understanding of generative model APIs. Prompt engineering involves writing effective prompts to elicit desired responses from large language models. You should also be familiar with the various prompt engineering techniques and have hands-on experience with generative model APIs.
Once you have a strong foundation in prompt engineering and generative model APIs, you can start building your own AI tools. Identify a problem that can be solved using generative AI and design a solution. This involves deciding how to use the generative AI model, what input it will require, and how the output will be used. With your understanding of prompt engineering and APIs, you can implement your solution and develop your own generative AI tools.
To further enhance your skills as a developer, you can move on to level 2, where you will learn about machine learning concepts and fine-tuning foundation models. Level 2 developers have a functional understanding of machine learning and can fine-tune pre-trained large language models for specific tasks. They can also build their own QA systems and retrieval augmented generation (RAG) systems using tools and frameworks like Hugging Face’s Transformers and OpenAI’s GPT.
If you aspire to contribute to the field of generative AI as a researcher, you can take the researcher learning path. Depending on your interest in NLP or computer vision, you will delve into the intricacies of building generative models from scratch. This involves learning about attention models, reinforcement learning algorithms, and deep learning concepts. You will also stay updated with the latest research in generative AI and participate in relevant online communities and conferences.
Becoming a developer or researcher in generative AI requires not only technical skills but also an understanding of the ethical implications of AI. It’s important to ensure that your models are fair, transparent, and respectful of user privacy.
In conclusion, the roadmap to becoming a generative AI developer or researcher involves mastering prompt engineering, understanding generative model APIs, and building your own AI tools. It’s a journey that requires continuous learning and staying updated with the latest advancements in the field. So, if you’re interested in the exciting world of generative AI, follow this roadmap and unlock a world of opportunities.
I hope you found this article helpful. If you have any questions or suggestions, feel free to leave them in the comments below. Thank you for watching, and don’t forget to subscribe to our Analytics Vidya channel for more informative generative AI videos. See you in the next video!
