Prompt and Context Engineering for Workflows
A prompt pack with a small evaluation set. Show evidence-based improvement and distinguish source-backed output from inference.
Register your interest. Dates and delivery are confirmed before enrolment opens.
What you will be able to do.
Build understanding, put it into practice and finish with work you can explain.
- Show evidence-based improvement and distinguish source-backed output from inference.
Is this for you?
Beginner learners who can demonstrate the entry competencies listed below. Preparation suggestions are optional.
Before you begin
Create a folder, open a supplied file and submit a named artifact
How you will show your progress
Show evidence-based improvement and distinguish source-backed output from inference.
From first principles to applied work.
Explain → Demonstration → Guided practice → Review
Planned outline. Lessons, trainer and schedule are confirmed before this course opens.
0190 live minutesDefine tasks and success criteria
10 min explanation · 15 min demonstration · 45 min practice · 20 min review
Define a structured meeting-summary task and pass conditions
02120 live minutesStructure context examples and outputs
15 min explanation · 20 min demonstration · 60 min practice · 25 min review
Build prompt context examples and a validation schema
03180 live minutesBuild a reusable workflow
25 min explanation · 35 min demonstration · 90 min practice · 30 min review
Create reusable prompt versions without embedding sensitive data
0490 live minutesEvaluate variation and improve prompts
10 min explanation · 15 min demonstration · 45 min practice · 20 min review
Compare outputs on fixed examples and explain observed failures
How you will practise and be assessed.
The planned assessment checks your result, your judgement and your ability to apply what you learned independently.
- 01
Build the promised result
Demonstrate the promised artifact
WHAT YOUR WORK SHOULD SHOWShow evidence-based improvement and distinguish source-backed output from inference.
- 02
Test a limit or failure
Compare outputs on fixed examples and explain observed failures
WHAT YOUR WORK SHOULD SHOWThe documented failure/uncertainty is visible, and no prohibited action or unsupported success claim occurs.
- 03
Apply it independently
Independently explain and change one assumption in a prompt pack with a small evaluation set.
WHAT YOUR WORK SHOULD SHOWThe learner predicts and verifies the change; AI output is not accepted without understanding.
Where this course stands.
Lab assets and supported tool versions are confirmed before teaching
Explore the source reference- Course ID
- S008
- Content
- Course outline in review
- Trainer
- Instructor to be confirmed
- Enrolment
- Not open · requests welcome
- Publication
- Planned
- Catalogue date
- 2026-10-15
Want to learn this?
Share your interest. We’ll confirm availability, batch dates and the fee separately, so you can decide when the details are ready.
- Your course is already selected
- Just your name and email to get started
- No payment or booking commitment
Know what your batch includes.
Learning support, assessment requirements and any certificate terms are confirmed with the batch before enrolment. Include your goals in your course request so the proposed format can be matched to what you need.
AI Agents vs Workflows: Choose the Right Approach
Beginner · 2 hours
From₹98· 2 hoursOpen micro-course
MCP Explained: Tools, Resources and Permission Boundaries
Intermediate · 2 hours
From₹98· 2 hoursOpen micro-courseTool Calling and Structured JSON Outputs
Intermediate · 2 hours
From₹98· 2 hoursOpen micro-course