Learn to design, test and improve prompts that get reliable output from ChatGPT, Claude and Gemini — in classroom or live online batches.
Practise writing prompts, comparing outputs and diagnosing where instructions fail. Explore how prompt design can support your work, with no prior AI background required.
The PDF contains a proposed syllabus update. Confirm the final batch curriculum and course arrangements with the team.
| Course detail | Information |
|---|---|
| Course | Prompt Engineering |
| Learning modes | Classroom, live online and corporate |
| Starting point | No prior AI background required |
| Certification | Brolly AI course completion certificate |
| Duration and fees | Confirm for your chosen batch |
| Batch schedule | Weekday and weekend batches |
| Trainer | Shaheda Tabassum |
Attend in person at the Hyder Nagar centre, or join the same batch live online. Both modes run.
Sit through a real session, meet the trainer, review the material, then decide.
Meet the teaching team and discuss who will lead your batch. Ms. Shaheda Tabassum works on LLM applications, RAG systems and AI assistants.
Issued after you complete training and project requirements. Same certificate for classroom and online.
Customised prompt-engineering programmes for company teams, delivered on-site or online.
Brolly AI teaches AI subjects only — generative AI, machine learning, MLOps and prompt engineering — not a general IT training centre.
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
Explore this proposed learning outline with the team before enrolling. Confirm the final modules and practical work for your batch.
Contact Brolly AI for current classroom and online fees, corporate pricing, any instalment options and what the fee includes. Confirm course materials, tool-account costs and support before enrolling.
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Prompt engineering is the practice of writing and structuring instructions so an AI model produces the output you actually want. It combines clear task framing, context, examples, output format rules and testing — to make responses more useful and consistent. Outputs still need review.
A large language model does not read your mind. It predicts a response from the words you give it. Change the framing, add an example, or specify the output format, and the answer changes — sometimes completely. Prompt engineering gives you a structured way to guide and evaluate those responses.
“Write about our new product.”
The model has to guess the audience, purpose and format.
Test the response, check the facts and refine the prompt. Clear instructions guide output; they don’t guarantee correctness.
Prompting is strongest when combined with your existing domain knowledge.
Fewer rewrites and re-prompts. You learn to state the task, context and format up front instead of correcting the model five times.
Reusable prompt templates give the same structure every time — useful for teams that need the same format across many people.
Summaries, drafts, comparisons, formatting and cleanup take far less time once you have a working prompt library.
Better prompts mean better code suggestions, clearer bug explanations and faster test generation from AI coding assistants.
Chain prompts together so one output feeds the next step — the basis of most AI automations inside companies.
System prompts, guardrails and output schemas are the core of any chatbot or AI feature in a product.
You learn to spot hallucinations, weak reasoning and format drift — and how to design prompts that reduce them.
ChatGPT, Claude and Gemini respond differently to the same prompt. Knowing how to adapt matters more than memorising one tool.
Prompting is the entry point into RAG, agents and LLM app development if you want to go further later.
See how you will learn.
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These tools form the proposed learning outline. Confirm the final tool list and any paid-account requirements for your batch.
Everyday prompting, custom instructions, long-conversation control.
System prompts, temperature and model settings in a controlled environment.
Structured prompts, long documents, format enforcement.
Multimodal prompts and prompting inside Workspace.
Prompting inside everyday office documents and email.
Research prompts and source-grounded answers.
Trying open models and comparing how they respond to the same prompt.
Prompting for code, tests and debugging.
Suggested exercises for practising and evaluating prompts. Discuss which labs are included in your batch.
Take a weak prompt and improve it in three passes, recording what changed in the output each time.
Run the same prompt through ChatGPT, Claude and Gemini and document where each one is stronger.
Change only the assigned role and measure how much the answer shifts for the same task.
Add, remove and reorder examples until a classification task becomes reliable.
Request JSON in a fixed schema, validate the output and handle malformed responses.
Build a template that keeps tone consistent across ten different content pieces.
Prompt for a function, then for its tests, then for a review of your own code.
Pull specific fields out of a messy PDF or invoice into a fixed table format.
Design prompts that force citations and reduce confident-sounding fabrication.
Score two prompt versions against a rubric and pick the winner with evidence.
Feed the output of one prompt into the next to complete a multi-step task.
Try to break your own system prompt, then patch the holes you find.
See how you will learn.
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Recommended project ideas to discuss for your capstone. Confirm the final projects for your batch before enrolling.
A prompt system that produces on-brand content in a fixed format from a short brief.
Score a resume against a job description and return structured, specific feedback.
Generates role-specific questions, then critiques the answers against a rubric.
Reply templates with tone control, escalation rules and a safe fallback.
Summarises sources, forces citations and flags where evidence is thin.
One brief, many channel variants — all consistent with a single voice guide.
Extracts fields from contracts or invoices into a clean structured table.
Turns raw notes and numbers into a structured summary with assumptions listed.
Prompt chain for writing, testing and reviewing a small feature.
A documented, versioned set of prompt templates a real team could adopt.
A multi-step prompt chain that completes a repetitive task end to end.
A test set and scoring sheet that proves one prompt version beats another.
Build a project portfolio and an AI skill before you start applying for roles.
Add a practical, demonstrable skill on top of your degree. Portfolio work matters more than the certificate here.
Apply prompting to the work you already do — reports, documentation, analysis, communication.
Get more out of coding assistants and learn to write the system prompts behind AI features.
Add rigorous prompt design and evaluation to your model work.
Speed up querying, cleaning, summarising and reporting.
Consistent, on-brand content at volume without losing quality control.
Use AI as a drafting and research aid while keeping your own voice.
Do more with a small team by automating repeatable work.
A realistic entry point into AI that doesn't require a heavy coding background.
HR, finance, operations, teaching, legal — prompting applies to all of them.
Corporate batches where a whole team adopts the same prompting standards.
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Meet your trainer and find a batch that fits your schedule.
No coding or AI background is required to begin learning prompt engineering. Bring basic computer skills, comfortable written English, a laptop and a stable internet connection. Ask which accounts and any Python preparation your selected batch requires.
The proposed outline targets these practical skills. Employment depends on your background, effort and the market.
Frame any task with the right context, constraints and output format on the first attempt.
Identify whether the problem is ambiguity, missing context, a bad example or a model limitation — and fix it.
Create parameterised templates a whole team can use consistently.
Adapt the same task to each model's strengths instead of relying on one tool.
Chain prompts together so complex tasks complete reliably end to end.
Test prompt versions against a rubric and defend your choice with evidence.
Content, support, analysis, documentation and reporting in your own domain.
Show documented before/after results in an interview instead of just naming tools.
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Generative AI Specialist & LLM Architect
9+ years in Artificial Intelligence, Machine Learning and Generative AI
Core expertise: Large Language Models, Prompt Engineering, Retrieval-Augmented Generation, AI agents, NLP systems, Deep Learning, MLOps and cloud deployment on AWS.
Industry projects: LLM-based AI assistants, RAG-powered knowledge platforms, intelligent chatbots, fraud detection systems and predictive AI solutions for healthcare and manufacturing.
Teaching style: explains transformers, embeddings and AI agents in simple language, with hands-on coding and job-focused training.
Book a free demoIn person at the Kukatpally centre. Direct trainer access, group discussion and lab support in the room.
Same syllabus, delivered live. Interactive sessions with online practical labs and flexible scheduling.
Customised programmes for company teams, on-site or online, with content mapped to your workflows.
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
| Batch | Days | Learning mode | Next session |
|---|---|---|---|
| Weekday batch | Weekdays | Classroom or live online | Confirm the next start date and class time |
| Weekend batch | Weekends | Classroom or live online | Confirm the next start date and class time |
Choose a weekday or weekend batch. Contact the team for the next start date, exact timings and available seats before enrolling.
A Brolly AI course completion certificate after finishing the training and project requirements. The same certificate applies to classroom and online batches. Ask about assessment and issuance details.
This is an institute certificate, not a certification from OpenAI, Google, Microsoft or an accreditation body. It records completion of your training and project work. Include documented prompt projects alongside the certificate in your portfolio.
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
Prompting can complement an existing role. Broader technical or domain skills may be needed for the roles below; completing a course does not guarantee employment.
Designs, tests and maintains prompts for a product or internal team. Usually expects some technical comfort and strong writing.
Works across prompting, model selection and AI feature delivery. Typically needs broader AI knowledge alongside prompting.
Produces and edits AI-assisted content at scale while holding brand voice and factual accuracy.
Builds prompt-driven workflows that remove repetitive steps from business processes.
Advises teams on where AI genuinely helps, then designs the prompts and processes to make it work.
Shapes AI features from the user side — system prompts, tone, guardrails and failure handling.
Builds applications on top of LLM APIs. Requires programming skills in addition to prompting.
Designs conversation flows and the prompts behind support and assistant bots.
The most common outcome: a marketer, analyst, developer or support lead who now works noticeably faster.
Ask which interview preparation, portfolio reviews, resume guidance or mock interviews are included for this course. Confirm whether placement assistance or internship opportunities are offered, and request their scope and terms before enrolling.
Discuss support optionsSee how you will learn.
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| What to check | What to ask for |
|---|---|
| Curriculum | Modules that are actually about prompt design, evaluation and workflows |
| Practical work | A named lab or exercise attached to each module |
| Projects | What you build, what you submit, and whether you keep it as portfolio work |
| AI tools | A current list, and clarity on whether you need paid accounts |
| Trainer | A named trainer with a verifiable profile — and confirmation they teach this batch |
| Batch dates | A current date, or an honest "next batch forming" |
| Fees | A number or a range before you hand over your phone number |
| Certification | Who issues it, and whether it is an institute certificate or an external one |
| Placement | The specific activities included, in writing |
| Reviews | Linked Google reviews you can open and read |
| Demo | A real teaching session you can sit through |
Use these steps to connect the syllabus, tools and project ideas on this page. Bring your current work and learning goals to the demo to discuss a suitable starting point.
Learn task framing, context, constraints and output format. Practise rewriting a weak request and checking what changed.
Try the same task with different models, roles and examples. Record accuracy, format and the effort needed to edit each response.
Create a reusable prompt workflow around a concrete problem. Keep test cases, failure examples and the decisions behind each revision.
Prepare to discuss the workflow, evaluation results and limitations in a project review or interview. Pair prompting with your domain or technical skills.
See how you will learn.
Meet your trainer and find a batch that fits your schedule.
Read learner feedback across Brolly AI programmes and ask the team about experiences from your chosen course.
Read Brolly AI reviews on GooglePrompt engineering is the practice of writing structured instructions that make an AI model produce accurate, consistent and useful output. It covers task framing, context, examples, output format and systematic testing.
Classroom and live online training in practical prompt design. Explore the proposed curriculum on this page and confirm the final syllabus, labs and project requirements with the team.
The proposed outline covers prompt structure, zero-shot and few-shot prompting, role and context prompts, structured output, evaluation, workflows and model-specific practice. Confirm the final syllabus for your batch.
Students, freshers, working professionals, developers, data and AI professionals, marketers, content writers, entrepreneurs, career switchers and non-IT professionals. No technical background is required to begin.
No. Prompt engineering is about writing clear instructions in natural language. Coding only becomes relevant if you later build AI applications on top of model APIs.
Python is not required for prompt engineering itself. Ask whether your selected batch includes Python or AI application development.
Basic computer skills, comfortable written English, and the ability to think through a problem in steps. No AI, ML or programming background is needed.
Confirm the duration, session length and total training hours for your selected classroom or online batch with the team.
Brolly AI has not published a fee for this course. Contact Brolly AI on +91 90521 44555 or WhatsApp for current course fee details for classroom and online batches, and for any instalment options.
Yes. Classroom training runs at the Brolly AI centre in Kukatpally, Hyderabad. Mention that you want the offline batch when you enquire, since classroom seats are limited.
Yes. Live online batches cover the same syllabus with interactive sessions and online practical labs.
Yes. You receive a Brolly AI course completion certificate after finishing the training and project requirements. It is an institute certificate, not an external accreditation.
The proposed outline includes ChatGPT, OpenAI Playground, Claude, Gemini, Copilot, Perplexity, Hugging Face and AI coding assistants. Confirm the final tool list and account costs before enrolling.
Discuss the project ideas on this page, such as a content generator, resume analyser, support prompt system, document assistant or team prompt library. Confirm your batch’s capstone requirements and available projects.
Yes, mainly as a way to build demonstrable project work early. Be realistic: freshers rarely get hired into a pure prompt engineer role. It is most useful combined with a technical or domain skill.
Yes. Most professionals apply it immediately to reporting, documentation, analysis, content and communication in their existing role, which is usually a faster return than a job change.
Yes. Non-IT learners often do well because effective prompting depends on deep knowledge of your own domain, which you already have.
Ask the team whether placement assistance is included for this course and which activities it covers. Training does not guarantee a job.
Ask whether an internship is offered for your batch, and confirm its duration, work, eligibility and payment terms before enrolling.
Use Book a free demo to enquire about this course, call +91 90521 44555 or message the team on WhatsApp. Attend the demo, confirm the batch and mode, then decide whether to enrol.
The syllabus covers instruction and role prompts, zero-shot, one-shot, few-shot, extraction, classification, transformation, structured outputs, decomposition, chaining, reasoning-pattern experiments, retrieval-grounded prompts, multimodal prompts and tool-use patterns. It also covers how to evaluate and maintain them.
Yes. The proposed scope includes context selection, evaluation datasets, schemas, application checks, retrieval, tool boundaries, skills and workflow design. It also teaches how to recognise when changing the prompt will not fix the underlying problem.
No. The appropriate method depends on the model and task. Current reasoning-model guidance can favour simple direct instructions. The course compares observable results and checkable answers without requiring hidden internal reasoning.
No. Model behaviour, context handling, settings and supported tools differ. Keep the task and evaluation cases consistent while testing each environment; document any model-specific adaptation.
A useful portfolio contains the problem brief, permitted sample inputs, prompt versions, evaluation cases, error analysis and a reproducible demonstration. An isolated screenshot of a good answer provides much less evidence of your method.
Yes. Select Download syllabus (PDF) at the top of this page or after the curriculum. The ungated PDF includes all proposed modules, readiness guidance, four project briefs and assessment criteria. Business details marked in the PDF still need confirmation.
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Visit the Kukatpally training centre or discuss live online options. Call ahead to arrange a centre visit and confirm current timings.
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