Student Profile

This course is ideal for:

• AI Professionals and Data Scientists who want to deepen their skills in AI orchestration and copilot development.
• BPM Engineers interested in building, integrating, and deploying AI-driven solutions using large language models (LLMs) and workflow orchestrators.
• Developers and Data Engineers who work with AI/ML solutions and want to understand the architecture and practical applications of generative AI copilots and orchestrators.
• Advanced AI Students or Researchers with a background in machine learning or NLP, looking to build practical skills in creating AI applications with generative AI technologies.

Prerequisites

To succeed in this course, participants should have:

1.Fundamentals of Generative AI

Completion of prior courses in Prompt Engineering, Taxonomy-Augmented Generation (TAG), and Retrieval-Augmented Generation (RAG) or

Successful completion of Foundation level course in Generative AI from AAII

2.Basic Programming or BPM Skills:

Proficiency in Python, or BPM skills is preferred for successfully designing and building Orchestration building blocks

3.  Foundations in Machine Learning and NLP:    

 Experience with machine learning pipelines, including data preprocessing, as well as familiarity with NLP concepts and text processing is also preferred.

4.Analytical Mind set:

Students should have an analytical mindset and interest in exploring new tools.

This combination of skills and knowledge will enable students to dive deeply into AI-driven orchestration, copilot development, and end-to-end application building.