AIPrompt engineering training
Stop guessing at prompts.Start specifying tasks.
Learn to structure instructions, context and examples, then test and refine model responses against clear evaluation criteria.
Answer five short questions to identify a suitable starting point.
- Build practical projects
- Learn a repeatable development process
- Understand how to test and explain your work
Project progress
- Define the problem
- Establish a baseline
- Build the solution
- Test the result
- Explain the work
Evaluation
Illustrative- Answer supported by sourcePass
- Citation includedPass
- Out-of-scope question Flagged
Project-based learning
Every path is built around a defined deliverable.
Clear learning pathways
Four paths, with stated prerequisites.
Evaluation and testing
Measure quality, not just whether it runs.
Real-world application
Problems with users, constraints and edge cases.
The problem
Too much theory
Understanding concepts is important. Applying them to a defined problem is what turns knowledge into practical experience.
No clear starting point
Different goals require different learning paths. Find a starting point that matches your experience and available time.
Difficulty proving what you know
Build projects that help you explain your decisions, demonstrate the output, and discuss the limitations.
Learn by building. Improve by testing. Grow by explaining.
How it works
A repeatable process.Not another pile of tutorials.
Every project follows the same five stages, so the method transfers to problems the course never covered.
Define the problem
Step 01
Define the problem
Identify the user, constraints, requirements, and desired outcome.
What this looks like in practice
Write a one-paragraph problem statement and list what the solution must and must not do before touching a model.
Step 02
Establish a baseline
Decide how to measure success before building.
What this looks like in practice
Collect a handful of representative examples and agree what a good answer looks like, so later changes can be compared fairly.
Step 03
Build the solution
Choose appropriate models, data, tools, and workflow components.
What this looks like in practice
Start with the simplest version that could work, then add retrieval, tools or automation only where the baseline shows a need.
Step 04
Test the result
Evaluate output quality, failure cases, and limitations.
What this looks like in practice
Run the solution against your examples, including awkward and invalid inputs, and record where it fails as well as where it succeeds.
Step 05
Explain the work
Document decisions, trade-offs, and results.
What this looks like in practice
Produce a short write-up covering what you built, why, how it was tested and what it cannot do — the part most portfolios skip.
Ready to build your first real AI project?
Find your starting point in five questions, or talk to us on WhatsApp or by phone.
Projects
Build things you canactually demonstrate.
Explore practical examples of how AI can be applied to meaningful problems.
Difficulty: FoundationalAI Document Assistant
Problem: Finding reliable answers across a collection of documents.
- Parsing
- Retrieval
- Context assembly
- Citations
Deliverable: A document-question-answering workflow with visible source references.
Difficulty: IntermediateIntelligent Workflow Automation
Problem: Repetitive tasks require manual processing and consistent decision-making.
- Schemas
- Business rules
- API calls
- Exception queues
Deliverable: An automation workflow with observable steps and error handling.
Difficulty: AdvancedAI Output Evaluator
Problem: AI-generated outputs can be inconsistent or incorrect.
- Rubrics
- Test sets
- Scoring
- Failure analysis
Deliverable: A repeatable evaluation process and an illustrative quality report.
Not sure which project fits you?
Five quick questions suggest a path and a first project.
Find my learning path
Learning paths & pricing
Choose what you need to learn next.Courses from ₹3,999.
Four focused paths, priced in Indian Rupees (₹). Open Details on any card for the full syllabus, prerequisites and the project you’ll build.
Clear prerequisites
Pay per path
Guidance before you pay
Learning-path assessment
Find your best place to start.
Answer five short questions to identify a practical next step for your AI learning journey.
- No email required to see your result
- Your answers stay in your browser
- A guide, not a test
Inside the kit
Free- Problem definition worksheet
- Success-metric checklist
- Project planning template
- Testing and evaluation checklist
- Results documentation template
Free resource
Give your next AI project abetter starting point.
A practical set of worksheets to help you define a problem, plan a solution, test the result, and document what you learn.
The AI Project Starter Kit
About
Learn the thinkingbehind the tools.
Tools change quickly. The reasoning behind good AI work — defining problems, measuring results, and being honest about limits — lasts.
Reasoning over recipes
Every technique is taught with the decision behind it, so you can adapt it to problems the course never covered.
Evidence over impressions
A solution is only as good as the tests that check it. You will learn to measure before you claim.
Honesty about limits
Knowing where a system fails is part of the deliverable — not an embarrassing footnote.
FAQs
Questions, answered.
Quick answers about prerequisites, time, pricing and support.
Do I need programming experience?
Not for every path. LLM Foundations and Prompt Engineering do not require programming. AI Workflow Automation expects some programming experience, and Agentic AI Engineering expects you to be comfortable building software. Each course lists its prerequisites.
Which course should I start with?
Take the five-question learning-path assessment above. It suggests a starting point based on your goal, coding experience, project history, main obstacle and available time. It is a guide, not a test — you can always ask us before deciding.
What will I build?
Each path is organised around a practical project, such as a document assistant with source references, a workflow automation with error handling, or an evaluation process for AI outputs. You also document how you tested the work and what its limitations are.
How much time should I commit?
Steady progress matters more than long sessions. The assessment asks how much time you have each week and adjusts its pacing advice accordingly. Confirmed time expectations will be published for each course.
Do I need to buy every course?
No. The paths are designed so you can start where it makes sense for you. Most learners will only need one or two, depending on their goals.
How much do the courses cost?
Courses range from ₹3,999 to ₹17,999 depending on the path. Every price is listed in the Pricing section, in Indian Rupees.
How long does each course take?
Course durations have not been published yet. When they are confirmed they will appear on each course card. If you need an estimate now, send us a question.
Is a job guaranteed after completing a course?
No. We do not guarantee jobs, promotions, salary changes or certification. The courses aim to give you practical skills and projects you can explain; outcomes depend on many factors outside any course.
What support is available?
Support arrangements are being finalised and will be described on each course before enrolment. You can ask about support through the enquiry form.
What is the refund policy?
The refund policy will be published on the refund policy page before any enrolment opens. Nothing is charged through this website at present.
How do I contact AOR?
Message us on WhatsApp, book a 30-minute call, or use the enquiry form at the bottom of this page.
Still have a question?
Others are already building. Are you?
Tutorials teach. Projects prove.Start building yours this week.
- Wait 3 more months
- More tutorials. Still nothing to show.
- Start this week
- A real project you can demo and explain.
Courses from
₹3,999
One path. One project.
Real skills.
1-minute assessment · no email needed
Prefer to ask a question first?
Tell us what you want to learn and we will reply by email with a suggested starting point. The assessment remains the quickest way to get a recommendation.