Real work by real learners
Generative AI Student Projects & Case Studies
Live AI products built by learners of our Generative AI Training in Hyderabad — from an AI abacus tutor for children to an AI kundali matching tool. See exactly what you could build in 3 months.
15+ projects per learner
400+ learners trained
60+ placed since 2024
3 live case studies
Next batch starts 5 October 2026 · Online & classroom near JNTU Metro Station
What projects do Generative AI Masters students build?
Students of the Generative AI Training in Hyderabad at Generative AI Masters build working AI applications for real users — not toy demos. Each project combines a large language model (the OpenAI API), Python logic and a web interface built with Streamlit, and solves a specific problem for a real audience such as children, teachers or families.
Every learner completes 15+ projects during the 3-month programme, guided by Lead AI Trainer Dinesh Tunguturi. The three case studies below are live today and show the range: education technology, kids' learning and a culturally specific astrology tool.
At a glance
Tools used: Python, OpenAI API, Streamlit
Project types: AI tutors, activity generators, calculation-and-matching tools
Who builds them: freshers, graduates and working professionals
Where they run: live websites used by real audiences
Course: 3 months · 60+ live hours · online or near JNTU
Featured student case studies
Each project below was designed, built and shipped by a learner during or right after the course. They are live today, used by real audiences, and published with each student's consent.
01
EdTech · Children & teachers
Abacus Learning App with an AI Abacus Tutor
Charan · Batch 12 · August 2024
The problem
Abacus practice depends on printed worksheets and a teacher checking every answer and bead technique, which limits how much children can practise at home.
What the AI does
✔ Generates practice sums matched to each child's level
✔ Explains the bead moves for every step of a sum
✔ Checks answers instantly and shows where a mistake happened
Built with
Python OpenAI API Streamlit
Who uses it
Children learning abacus, and abacus teachers who set and review practice work.
See it live ↗02
Kids' learning · Chess & languages
Brolly Juniors: AI-Powered Learning Activities for Kids
Gayatri · Batch 10 · June 2024
Why it matters
Children's after-school activities such as chess and new languages need fresh, level-appropriate practice every week. AI generates that material on demand, so learning stays varied and engaging.
What the AI does
✔ Creates chess puzzles for children to solve
✔ Powers interactive activities that help children learn new languages
Built with
Python OpenAI API Streamlit
Who uses it
School-age children on Brolly Juniors, a kids' learning platform in Hyderabad, and the parents and teachers who guide them.
See it live ↗03
Astrology · Families & astrologers
Anugraha Siddhi: AI Kundali Generation & Matching Tool
Mouli · Batch 26 · January 2026
Why it matters
Preparing a janma kundali and checking marriage compatibility (Guna Milan) by hand takes an expert's time. The tool gives families a fast, consistent starting point before they consult an astrologer.
What the AI does
✔ Generates a kundali from date, time and place of birth
✔ Matches two kundalis and presents the compatibility result
Built with
Python OpenAI API Streamlit
Who uses it
Families and astrologers using Anugraha Siddhi, a Hyderabad astrology and Vedic services provider.
See it live ↗How the project module works in our Generative AI course
Every learner in our Generative AI training in Hyderabad builds working applications, not just notebooks. The course includes 15+ hands-on projects, and each capstone follows the same five steps our case-study students used.
1
Choose a real problem
Pick a problem from a real business, a family business or your own domain, and agree the scope with your trainer.
2
Design the AI solution
Define the users, inputs and outputs, and decide whether the app needs prompting, RAG, an AI agent or fine-tuning.
3
Build in live labs
Write the app in Python with LLM APIs and a Streamlit or FastAPI front end, with doubts cleared in live classes.
4
Test and improve
Check answers for accuracy, handle errors and edge cases, and keep API costs and safety under control.
5
Deploy and present
Deploy the app, demo it to your batch, and add it to your GitHub, resume and LinkedIn profile.
Skills a Generative AI project proves to employers
Recruiters hiring for Generative AI roles in Hyderabad want evidence that you can ship a working application. One deployed project demonstrates all of these skills:
Prompt engineering
Writing system prompts and templates that give reliable, consistent outputs.
LLM API integration
Calling models such as GPT, Claude and Gemini from Python and handling responses, rate limits and costs.
RAG and vector databases
Connecting an LLM to private documents using embeddings and databases such as ChromaDB or Pinecone.
AI agents
Building tool-using agents with LangChain, LangGraph or CrewAI that complete multi-step tasks.
Deployment
Turning a notebook into an app real people can use, with Streamlit or FastAPI.
Evaluation and responsible AI
Testing outputs, reducing hallucinations and protecting user data.
Why a project portfolio matters more than a certificate
A certificate shows you attended a course. A live project link lets an interviewer open your app, try it and ask how you built it, which is exactly the conversation you want in a Generative AI interview. Our placement support (resume and LinkedIn reviews, mock interviews and referrals) is built around the projects you complete, and 60+ learners have been placed so far.
Generative AI project ideas you can build in the course
Beyond the capstone, the curriculum covers the project types companies are hiring for. These are examples of what learners build during the 60+ live hours:
Beginner
AI content and marketing assistant
Generates blog outlines, social posts and ad copy in a brand's tone from a short brief.
Python · OpenAI API · Streamlit
Intermediate
RAG chatbot for company documents
Answers questions from PDFs, policies or manuals and cites the passage it used.
LangChain · ChromaDB or Pinecone · FastAPI
Intermediate
AI tutor and quiz generator
Explains topics step by step and creates practice questions at the learner's level, the idea behind the abacus and Brolly Juniors projects.
Python · OpenAI API · Streamlit
Advanced
Multi-agent research assistant
A team of agents that search, summarise and draft a report, each with its own role and tools.
LangGraph · CrewAI · AutoGen
Advanced
Fine-tuned domain model
An open-source LLM adapted to a domain such as legal, healthcare or customer support.
Hugging Face · LoRA · QLoRA
Advanced
Multimodal AI app
Works with images, voice and text together, for example describing product photos or summarising recorded calls.
Vision and speech models · Streamlit
Student projects: frequently asked questions
What projects do students build in the Generative AI course at Generative AI Masters?
Students build 15+ hands-on projects and a capstone that solves a real problem. Recent capstones include an AI abacus practice tool (abacusexperts.com), AI chess puzzles and language activities for Brolly Juniors, and an AI kundali generation and matching tool for Anugraha Siddhi.
Do I need coding experience to build a Generative AI project?
No. There is no coding prerequisite. Module 1 starts with Python from scratch, and learners from BCA, B.Sc, MBA and other non-IT backgrounds complete their projects with trainer support.
Which tools did the featured students use?
All three featured projects were built with Python, the OpenAI API and Streamlit. Other projects in the course use LangChain, LangGraph, CrewAI, vector databases, Hugging Face and FastAPI.
Can I see the source code of these projects?
The code is kept in private repositories because the apps serve real users. You can try the live apps linked on this page and ask the trainer for a walkthrough during your free demo class.
Who guides students while they build their projects?
Projects are guided by Lead AI Trainer Dinesh Tunguturi and the trainer team. Batches have at most 15 students, so every project gets individual feedback.
Will a project help me get a Generative AI job?
A deployed project gives you something concrete to show in interviews. Placement support includes resume and LinkedIn reviews, mock interviews and referrals, and 60+ learners have been placed. We don't promise jobs; results depend on your effort and the job market.
When does the next batch start and what are the fees?
The next batch starts on 5 October 2026. Fees are ₹35,000 for live online classes and ₹40,000 for classroom training near JNTU Metro Station, Kukatpally, Hyderabad. EMI is available.
Build your own Generative AI project. Next batch starts 5 October 2026
Join a small batch of at most 15 students, go from Python basics to AI agents in 60+ live hours, and finish with deployed projects you can show employers. ₹35,000 online · ₹40,000 classroom near JNTU Metro, Kukatpally · EMI available.
★ 4.9 from 51 Google reviews · 400+ learners trained · 60+ placed