Key takeaways
01
What is AI context, and why is it vital for AI analytics
02
Who the context engineer is, what the role is responsible for, and key skills
03
Common AI context engineering methodologies, best practices, and architectures
Why enroll?
Business intelligence used to move at the speed of a ticket queue. You built the pipeline, modeled the query, shipped the dashboard, and waited weeks. Now anyone in the business can ask a question in plain language and get an answer in seconds. But here’s the catch: AI doesn’t know your business.
The AI context engineer closes that gap. In this course, you’ll learn how to become the person who makes AI actually work for enterprise analytics. Upon passing the learning assessment, you’ll receive a certification to show your competency in AI Context Engineering.
If you’d like, you can continue your learning in AI Context Engineering 201, where you’ll get hands-on training putting these skills to work in one of the industry’s top Agentic Analytics Platforms and Context Layers, WisdomAI.
Who should take this course?
This course is for anyone who works with data and wants to stay ahead of AI.
Data analysts
Analytics engineers
Data engineers
Data scientists
Data architects
BI & reporting professionals
Students & early-career analysts
If you’ve ever written a SQL query or argued over a metric definition, you’re ready.
Course overview
3 modules
10 video lessons
1 graded assessment
Module 1
What is AI context
3 lessons
Module 2
What is AI Context Engineering (ACE)
3 lessons
Module 3
Practical applications and tools of the trade
4 lessons
Learning assessment
20 questions · certification upon passing assessment
About this course
Free
Beginner
Ungated & self-paced
10 video lessons
1 graded assessment
Certification upon passed assessment
Instructor
Ayushi Shah
