← Back to the cataloguePrompt Engineering
Beginner to Advanced
Level
Classroom . Online . Hybrid
Mode
Course overview
A focused course on writing, testing and maintaining prompts for production use. The course treats prompting as engineering work: version-controlled instructions, structured output, measurable quality and controlled cost. Techniques are practised across ChatGPT, Claude, Gemini and Perplexity so learners can see how the same prompt behaves on different models.
The final exercise is a documented prompt library for a chosen business function, with an evaluation sheet.
Who it is for
- Anyone using AI tools daily at work
- Marketers, analysts and support teams
- Developers building AI features
- Trainers and content teams
Prerequisites
No programming required. Comfort with web tools is enough.
How it runs
Learn → Practise → Build → Experience → Demonstrate, ending in a capstone. Delivered by practitioners from the engineering bench, in Madurai, Coimbatore and online.
Final project
Prompt Library for One Business Function
Programme sheet
The printed sheet carries the full module breakdown, labs, project work and certification path. Fees, dates and formats for the next intake are confirmed by the education team on enquiry.
Learning outcomes
01
Choose a prompting pattern that suits the task.
02
Force structured, parseable output.
03
Test prompt quality with a repeatable evaluation set.
04
Defend prompts against injection and leakage.
05
Write system prompts that hold behaviour over long chats.
06
Chain prompts into multi-step workflows.
07
Reduce token cost without losing accuracy.
Module structure
8 modulesHow models read prompts . Determinism and temperature . Tokens and context . Model differences
Lab
Same Prompt Across Four Models
Zero-shot . Few-shot . Delimiters and formatting . One-shot . Instruction framing . Negative instructions
Module 03
Reasoning Patterns
Tree-of-thought . Self-consistency . Step-back prompting . Task decomposition
Lab
Multi-Step Reasoning Tasks
Module 04
Role and System Design
Role prompting . System prompt structure . Tone and constraints . Persona consistency . Refusal handling
Lab
Support Assistant System Prompt
Module 05
Structured Output
JSON output . Schemas . Tables and lists . Validation . Retry strategies
Lab
Schema-Validated Extraction
Module 06
Chaining and Workflows
Prompt chaining . Routing . Summarise-then-act . Tool use . Human review points
Tools — Claude, Gemini, Perplexity
Module 07
Evaluation and Optimisation
Test sets . Rubrics . LLM-as-a-judge . A/B testing prompts . Token and latency budgets
Module 08
Safety and Maintenance
Prompt injection . Data leakage . Sensitive data handling . Versioning . Documentation
Assessment & certification
Module assignments and labs
25%
Final project and review
40%
Learners who complete all modules, submit the final project and clear the review receive a course completion certificate from Kaizen Infinities Private Limited. Project work is documented for the learner's portfolio, and interview preparation is included in the closing sessions.
Career outcomes . Roles this programme prepares for
Prompt EngineerAI Content SpecialistAI Support DesignerAI Workflow ConsultantConversation Designer
