Course Overview

" Generative AI Mastery: Building Intelligent Copilots & Orchestrators " course is a comprehensive, hands-on program tailored for AI practitioners aiming to develop advanced AI-driven copilots and orchestrators. Throughout the course, you will dive deep into essential tools like Langchain and Flowise, gaining the skills needed to create customized, intelligent solutions. The curriculum covers practical aspects of building and integrating these systems, including thorough testing and evaluation methods to ensure optimal performance. You'll work with real-world use cases, enabling you to design and deploy intelligent workflows that significantly enhance user experiences and streamline operations.

Prerequisites:

To enroll, students must have completed courses in Prompt Engineering, Retrieval-Augmented Generation (RAG), and Taxonomy-Augmented Generation (TAG). These prerequisites ensure that participants have the necessary background to fully engage with the advanced content and challenges presented in this course.

 Expected Outcomes

1. Proficiency in AI-Orchestration Tools and Techniques
   Participants will gain hands-on experience with advanced tools like Langchain, LlamaIndex, and Hyde, equipping them with the ability to design and implement efficient AI-driven orchestrators that automate complex tasks and decision-making processes.
2. Skill in Building Functional AI Copilots
   Attendees will be able to create AI copilots capable of assisting users in specific tasks by leveraging LLMs, chains, and custom prompts, thus enhancing productivity and user experience in various applications.
3. Mastery of Orchestration Building Blocks
   Through structured exercises, participants will become proficient in utilizing orchestration components, including LLMs, chains, parsers, document loaders, text splitters, and vector stores, optimizing data handling and memory for complex AI workflows.
4. Understanding of Advanced Orchestration Concepts and Ethics
   Participants will develop a robust understanding of advanced orchestration concepts such as Langsmith and multi-model integration while critically evaluating the ethical and societal implications of their implementations, ensuring responsible and conscientious AI use.
5. Ability to Build Full-Stack AI Applications
   By the end of the course, participants will have created a fully functional, end-to-end AI application that combines orchestrators and copilots. They will understand the process from design to deployment and performance evaluation, gaining the skills needed to implement and scale AI solutions in real-world scenarios.