Curriculum
How the program is structured
AI Fundamentals for Data Professionals
Core AI/ML concepts and terminology, framed around existing data experience.
Data Pipelines for RAG
Building and maintaining the data pipelines that feed retrieval systems.
Applied AI & Evaluation
Applying LLM engineering concepts to data workflows, with evaluation methodology.
Capstone & Verification
Build a practical project end-to-end and complete the role-specific technical assessment.
What you'll learn and who this is for
Full Skill List
Prerequisites
Working experience with data pipelines, SQL or applied data analysis.
By the end, you'll be able to
- Build data pipelines that feed retrieval-augmented AI systems reliably.
- Apply core LLM engineering concepts to existing data workflows.
- Design an evaluation approach for AI system output quality.
- Talk through data-to-AI pipeline decisions in a technical interview.
Who this program is for
- Data analysts and data engineers with existing SQL, data pipeline or analytics experience.
- Professionals looking to move from data-focused roles into applied AI engineering.
Projects, assessment and verification
Practical Projects
- AI Document Intelligence
- Enterprise RAG Assistant
Assessment
Technical assessment covering applied AI, data pipelines for RAG and evaluation methodology.
Verification
Verified ITtoAI profile with assessed skills and reviewed project submissions.
Career Relevance
Builds on existing data expertise to meet AI engineering requirements around retrieval and evaluation.
Completing this program does not guarantee employment, placement or salary outcomes. It builds practical capability and an evidence-based profile that demonstrates it.