This course will provide an introduction to AI language models, with a focus on two of the most powerful and widely-used models in the field: GPT and LLMs. Students will gain an understanding of the underlying technology behind these models, how they are trained and used, and their potential applications in natural language processing. The course will also cover other key terms and concepts in the field of AI language models, providing a comprehensive overview of the field and its potential applications.
Course Overview:
Module 1: Introduction to AI Language Models
- Overview of natural language processing and its applications
- Explanation of key terms and concepts, including GPT and LLMs
- Discussion of the potential applications of AI language models
Module 2: Understanding GPT
- Overview of the GPT architecture and its training process
- Discussion of the strengths and weaknesses of the model
- Examples of how GPT is used in natural language processing applications
Module 3: Introduction to LLMs
- Overview of LLMs and how they differ from other language models
- Explanation of the training process for LLMs
- Examples of how LLMs are used in natural language processing applications
Module 4: Advanced Topics in AI Language Models
- Optimization techniques for prompt engineering
- Parameter tuning for AI models
- Ethical considerations in AI language models
Throughout the course, students will have the opportunity to explore real-world examples of AI language models in action, and will gain hands-on experience working with these models through interactive exercises and assignments. By the end of the course, students will have a strong foundation in the basics of AI language models, as well as a deeper understanding of their potential applications and the challenges they present.