Lead the GenAI revolution. Future-proof your skills by understanding AI basics, machine learning, algorithms, ethical practices, and real-world applications. Stay ahead in tech leadership.

In one form or the other, AI is going to be infused in all the tech products. Meaning, that in order to stay a relevant leader, it has become essential to have a solid, broad understanding of AI. While you may not be implementing the solution, you need to speak the language of AI.
 
Whether you’re leading a team on creating AI solutions, or you just want a better understanding of AI, then this course is for you. In this course, I have deconstructed the concepts most relevant for you.
 
You will start by learning the basics of AI, its connection with machine learning, and the different types of algorithms you should be familiar with. You’ll then learn the rules, best practices, and infrastructure for creating great AI products that users trust. Then, you will go through some real case studies of AI application and do a deep dive into Ethical AI. You'll end by getting an outlook into the current status and future of AI. In a nutshell, this course is your no-fuss, comprehensive guide to the essentials of AI.

Grokking AI for Engineering & Product Managers

### What is transfer learning?
Say you were a statistician, and now you are learning about data science. You would use your past knowledge to build upon your skillset as a data scientist.

Transfer learning has the same idea. This deep learning technique enables developers to harness deep learning models used for one task and apply them to another domain. The pre-trained models are used as starting points, especially on computer vision and natural language processing tasks. 

For example, say you are creating an application to identify wolves in the wild, but there aren’t any publicly available models that are good enough for your needs. With transfer learning, you can begin with a state of the art CNN model used for image recognition of animals, and you can fine-tune it to recognize images of wolves.



# What is transfer learning?
Say you were a statistician, and now you are learning about data science. You would use your past knowledge to build upon your skillset as a data scientist.

Transfer learning has the same idea. This deep learning technique enables developers to harness deep learning models used for one task and apply them to another domain. The pre-trained models are used as starting points, especially on computer vision and natural language processing tasks. 

For example, say you are creating an application to identify wolves in the wild, but there aren’t any publicly available models that are good enough for your needs. With transfer learning, you can begin with a state of the art CNN model used for image recognition of animals, and you can fine-tune it to recognize images of wolves.



This lesson defines transfer learning and discusses its uses. 

The Fundamentals

AI in Practice

Real Case Studies

Responsible AI

What's Next

Transfer Learning

What is transfer learning?