Upon successful completion of this course, students will be able to:

• Understand and interact with large language models (LLMs) using APIs.
• Work with pre-trained LLMs using the Huggingface transformer library.
• Run open-source LLMs on their own computers.
• Use basic prompting techniques to get better results from LLMs.
• Apply advanced prompting methods for more complex and relevant LLM outputs.
• Explain how memory, embeddings, and vector databases help LLMs work.
• Build systems that combine LLM capabilities with external knowledge.
• Create LLM Agents that can perform tasks or interact with the world.
• Understand the basics of StreamLit and use it for interactive web apps.
• Develop AI applications with StreamLit that utilize LLMs.
• Fine-tune LLMs to make them better at specific tasks.