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Generative AI & Prompt Engineering · Session 12: Final Capstone Project & Certification · tarahutailabs.com
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This is it — 12 sessions of mastery culminate in one capstone project. Build a complete AI-powered solution using every technique you have learned. Present, earn your certificate, and step into the future. "12 sessions da safar — aaj pura hunda hai."
This is the final session. You will build a complete AI-powered solution that combines ALL the techniques from Sessions 1-11. This is not just an exercise — this is your portfolio piece that proves you can engineer AI solutions for real business problems. "Eh sirf assignment nahi — eh tuhadi AI portfolio piece hai."
You have covered: Transformer Architecture (Session 1), Tokens & Context Windows (Session 2), Temperature & Parameters (Session 3), Model Comparison (Session 4), CRISP Framework (Session 5), Chain-of-Thought (Session 6), Few-Shot & Zero-Shot (Session 7), System Prompts (Session 8), Role-Based Prompting (Session 9), Prompt Chaining (Session 10), and Custom GPTs & Claude Projects (Session 11). Today you combine everything into one capstone project. "11 sessions da learning — 1 project vich."
Your project must integrate at least 4 different prompt engineering techniques from Sessions 1-11. For example: system prompts + chain-of-thought + few-shot + prompt chaining. The more techniques you combine effectively, the higher your score. "Ghatt ton ghatt 4 techniques — jitne zyada utna behtar."
Your project must address a genuine business problem. Not a toy example — a real challenge that a Punjab business or professional would face. Customer support, content creation, business analysis, or operations automation. "Asli business problem solve karo — fake nahi."
Submit a portfolio document with: problem statement, techniques used (with justification), all prompts, sample outputs, testing results, and lessons learned. This becomes your professional portfolio piece. "Har cheez document karo — eh tuhada resume hai."
Deliver a 5-minute presentation to the class: what problem you solved, which techniques you used, demo your solution live, and share one key insight. Practice before presenting. "5 minute da presentation — practice zaroor karo."
"Maine 12 sessions vich bahut kuch seekha, par kya main sach mein AI solution bana sakda/sakdi haan?" Yes. You have every technique, every framework, every strategy. This capstone proves it — not just to us, but to yourself. When you walk out today, you will have a portfolio piece and a certificate. That is the transformation from learner to practitioner.
Next: Choose your capstone project from 3 options.
Three project options designed for Punjab businesses. Each one uses different combinations of techniques from the course. Pick the one that matches your business or interest. "Tinn options — apni marzi naal chuno."
Build an intelligent customer support system that handles queries, escalates issues, and learns from interactions:
Design a comprehensive customer support persona with identity, behavioral rules, constraints, escalation protocols, and output format. The foundation of your support system.
Provide 5-10 example customer interactions showing ideal responses for common scenarios: order queries, complaints, returns, product questions, and technical issues.
Build reasoning chains for complex customer issues: diagnose the problem → identify the category → check policy → formulate response → suggest next steps.
Package everything into a Custom GPT with knowledge files (product catalog, FAQ, return policy) and conversation starters. Deploy as a shareable tool.
Build a complete content production pipeline that turns a single topic into a full marketing package:
Use Context, Role, Instructions, Scope, and Parameters for every prompt in the pipeline. Each step has precise CRISP-structured instructions for consistent quality.
Build a 5-link chain: Research → Outline → Draft → Polish → Distribution Package. Each link feeds its output as input to the next.
Set up a Claude Project with brand guidelines, style guides, and reference content uploaded. The project maintains brand consistency across all outputs.
Use different expert personas at each stage: Research Analyst for research, Content Strategist for outline, Copywriter for draft, Editor for polish, Marketing Manager for distribution.
Build an AI-powered business analysis system that processes data, generates insights, and produces executive reports:
Use low temperature (0.1-0.3) for data analysis and number crunching, medium (0.5-0.7) for insight generation, and higher (0.8) for creative recommendation brainstorming.
Build structured analytical reasoning: Data input → Pattern identification → Trend analysis → Insight extraction → Actionable recommendations with confidence levels.
Chain analysis steps: Data Cleaning → Statistical Summary → Trend Analysis → Competitive Benchmarking → Executive Report with recommendations.
Package the analyst into a Custom GPT with historical data files, industry benchmarks, and company KPIs uploaded. Anyone on the team can query business performance.
Yes! If you have a specific business problem you want to solve, propose it to the instructor. Requirements: must use 4+ techniques, solve a real problem, and include documentation. Some of the best capstones come from personal passion projects. "Apna idea vi changa hai — bas 4+ techniques use karo."
Next: How your project will be evaluated.
Your capstone is scored on 5 dimensions totaling 100 points. Pass mark is 70/100. This rubric ensures you demonstrate real mastery, not just surface-level understanding. "70/100 layi pass — par excellence layi 90+ target karo."
| Criterion | What We Evaluate | Points |
|---|---|---|
| Prompt Quality | Are your prompts well-structured? Do they use CRISP framework? Are they specific, clear, and optimized? Do they produce consistent, high-quality outputs? We look at specificity, constraint handling, and output quality. | 25 |
| Technique Integration | How many techniques did you use? (Minimum 4) Are they integrated naturally or forced? Does each technique add genuine value to the solution? We check that you understand WHY each technique was chosen. | 25 |
| Business Value | Does this solve a real problem? Would a Punjab business actually use this? Can you articulate the ROI? Is the solution practical and deployable? We evaluate real-world applicability. | 20 |
| Documentation | Is every prompt documented with context? Are decisions justified? Is there a testing log? Could someone else replicate your solution from the documentation alone? Completeness and clarity matter. | 15 |
| Presentation | Is the 5-minute presentation clear and compelling? Did you demo the solution live? Did you share insights and lessons learned? Confidence and clarity in communication. | 15 |
Surface-level prompts without optimization. Fewer than 4 techniques. No real business application. Incomplete documentation. No live demo. Can resubmit after revision.
Masterfully crafted prompts with CRISP. 5+ techniques seamlessly integrated. Clear business ROI demonstrated. Complete, replicable documentation. Engaging presentation with live demo and insights.
90-100 (Excellence): Outstanding integration and business value. Portfolio-ready work. Potential showcase on TARAhut AI Labs website.
80-89 (Distinction): Strong technical execution with clear business understanding.
70-79 (Pass): Meets all requirements with adequate technique usage.
Below 70 (Resubmit): Needs revision. One resubmission allowed within 7 days.
The difference between 75 and 95 is not more techniques — it is deeper integration. A 95-score project shows that removing any technique would break the solution. Each technique is load-bearing, not decorative. Also, top scorers always include a "Lessons Learned" section showing what they tried that did NOT work and why they changed approach. "Techniques decorative nahi hone chahidiyan — har ek zaruri honi chahidi hai."
Next: Step-by-step build guide with example prompts.
Follow these 5 steps to build your capstone project. Each step includes example prompts and templates you can customize for your chosen project. "5 steps follow karo — capstone ban jauga."
Use CRISP to write a clear problem definition. This becomes the foundation of your entire project:
Design the system prompt that powers your entire solution. Use the Session 8 framework:
Build a multi-step prompt chain where each step feeds into the next:
Package your solution using Session 11 techniques:
Document everything for your submission and professional portfolio:
Minutes 0-10: Finalize problem statement and technique selection.
Minutes 10-35: Build system prompt, chain-of-thought, and few-shot examples.
Minutes 35-50: Create prompt chain and test individual links.
Minutes 50-65: Deploy as Custom GPT or Claude Project. Run 20 test queries.
Minutes 65-80: Write portfolio documentation.
Minutes 80-90: Prepare 5-minute presentation. Practice once.
Next: Final quiz covering the entire 12-session course.
8 questions covering the entire 12-session Generative AI & Prompt Engineering course. Prove your mastery across all techniques.
"Tusi 12 sessions complete kar laye — Generative AI & Prompt Engineering da poora course. Tusi hun officially AI prompt engineers ho." You are no longer learning AI. You are engineering with it.
Upon successful completion of your capstone project (70+ score), you will receive the TARAhut AI Labs — Generative AI & Prompt Engineering Certificate. This certificate verifies that you can:
✅ Understand AI model architecture and parameters
✅ Engineer precise, optimized prompts using CRISP framework
✅ Apply chain-of-thought, few-shot, and zero-shot techniques
✅ Design system prompts and role-based personas
✅ Build prompt chains for complex workflows
✅ Deploy Custom GPTs and Claude Projects
✅ Solve real business problems with AI
The certificate includes a unique verification code and QR link. Add it to your LinkedIn profile.
Your prompt engineering foundation opens doors to advanced AI capabilities. Here is your learning roadmap:
Autonomous AI systems that can plan, use tools, browse the web, write code, and execute multi-step tasks without human intervention. Agents use prompt engineering as their foundation but add tool-use, memory, and planning capabilities. The next frontier. "AI agents = autonomous AI workers."
Connect AI to your own databases, documents, and knowledge bases in real-time. Instead of uploading static files, RAG dynamically retrieves relevant information for each query. Essential for enterprise AI solutions. "RAG = AI jo tuhade database ton real-time answers denda hai."
Train AI models on your own data to create specialized models that understand your domain deeply. Fine-tuning goes beyond prompts — you are actually modifying the model's knowledge and behavior. For specialized industry applications. "Fine-tuning = apna khud da AI model train karo."
Enable AI to call real APIs, query databases, send emails, update CRMs, and interact with external systems. Function calling turns AI from an advisor into an executor. This is how production AI applications are built. "Function calling = AI jo kaam bhi kare, sirf bole nahi."
We are launching advanced courses in 2026:
🔮 AI Agents Masterclass — Build autonomous AI systems with tool-use and planning
🤖 RAG & Enterprise AI — Production-grade AI with your business data
⚙️ AI for Developers — API integration, fine-tuning, and deployment
💼 AI Business Strategy — For founders and managers building AI-first companies
Join the waitlist at learn.tarahutailabs.com to be notified when enrollment opens.