Resources

The two textbooks recommended for this class were chosen for their complementary focus on both theoretical foundations and practical applications of large language models (LLMs) in real-world scenarios.

This guide provides a comprehensive walkthrough for setting up and utilizing Docker Desktop on Windows and macOS systems. It details specific hardware requirements, such as virtualization support and memory needs, alongside step-by-step instructions for graphical and command-line installations.

An Application Programming Interface (API) is a set of rules and protocols that enables communication between different software systems, acting as a bridge to facilitate data exchange and interaction.

No-code tools empower users to create autonomous AI systems without requiring programming expertise. These platforms provide intuitive interfaces, making it easier to design and deploy AI-driven applications.

A list of various open-source frameworks available to you to build your own agentic AI application:

Cross-origin resource sharing (CORS) is a mechanism for integrating applications. CORS defines a way for client web applications that are loaded in one domain to interact with resources in a different domain. This configuration is needed to allow local model providers to server web-applications what were loaded from a different site.

Ollama is a tool designed to host large language models (LLMs) locally on macOS, Linux, and Windows systems, offering OpenAI-compatible APIs for seamless integration with existing applications. By running models locally, Ollama eliminates the need for cloud-based services, ensuring privacy and reducing costs.