10 AI models: A gentle deep dive
Unit overview
The world of AI models may be best described as a vast, tall tower of knowledge that is also rapidly expanding. None of you will be surprised to hear that this course will not be able to cover the field comprehensively.
What we intend do, however, is to give you a detailed overview of things that matter for AI builders.
Prerequisites
- None
Learning objectives
What are these?
Each unit includes a set of Learning Goals and Learning Outcomes which form the unit's guiding principles.
- Learning Goals describe the unit's key topics and ideas.
- Learning Outcomes on the other hand describe tangible skills that the learner should be able to demonstrate
Here, we will cover:
Learning Goals- What AI models are and what they do
- Overview of model architecture & training
- Common types of models (generative and embedding)
- Examples of models and use cases
- How to access AI models (with code example)
By the time you are finished, you will be able to:
Learning Outcomes- Explain the core concepts of AI model architecture and training
- Describe multiple model types and their appropriate use cases
- Implement basic code for accessing models
- Interpret key details of model cards or specifications
Questions and feedback
If you have any questions or feedback, let us know in the user forum.