So far in this session, you have looked at the economic impact of generative AI, explored some of its use cases in different industries and discussed the different categories in which use cases of generative AI usually fall. In the next few segments, you will learn about what you need to do in your role to leverage generative AI to its full potential. Specifically, we will discuss the skills people in different role to use generative AI effectively.
Let’s start by discussing some job descriptions that require some generative AI skills to get a better understanding of such skills.
In this video, you went through a few job descriptions related to generative AI. An example job description is given below.
Going over the skills that are being asked for in the market today is a good way to improve your chances of getting hired in a suitable role in the future. Before moving forward, answer the following question to check your understanding of what we have covered so far.
Now that you have gained an initial understanding of the skills relevant for generative AI, the next natural question that arises is, “How do I learn these skills?” Since generative AI, is such a nascent field which is such a constantly growing and changing, it is essential to have a mental roadmap of the learning journey associated with it.
Let’s hear from Kshitij as he walks us through the different stages of learning and adopting generative AI.
Kshitij broke down the generative AI learning journey into five steps:
- Generative AI explorer: Interacts with generative AI apps for fun, exploration and curiosity.
- Effective generative AI user: Has mastered prompt engineering and knows the art and science of interacting with generative AI structurally to get the desired outputs for complex tasks.
- Universal generative AI user: An effective user who has expertise across various generative AI tools and outputs such as images, videos and code.
- Generative AI developer: Can integrate generative AI tools with products and applications to automate, customise and create efficient generative AI-enabled software and data solutions.
- Generative AI researcher: Can build LLMs from scratch with extensive knowledge of ML, software, natural language processing and deep learning.
A learner does not need to progress through all the steps in the generative AI learning journey to start using it effectively in their role at the workplace. In this program, you will develop the generative AI skills required by a generative AI developer.
Now that you have understood the learning journey associated with generative AI, let’s understand the different levels of knowledge required to use generative AI effectively in various roles.
Kshitij used the following table to describe the levels of knowledge related to generative AI that may be required for people working in different roles.
This brings us to the end of the discussion on the skills required to use generative AI effectively.
In the next segment, we will summarise your learnings from this session.