Learn In తెలుగు Artificial Intelligence and Machine Learning
4.8K+ students have already registered
Why choose this course?
Prestigious certification from Vishlesan i-Hub, IIT Patna
Real world capstone projects designed to solve practical challenges
Delivery in Telugu, learn from experts who speak your language
Placement assistance, resume reviews, coaching(Eligibility: 7 CGPA, 65% attendance)
*Certificate Eligibility: Minimum 65% overall attendance and 30% marks in cumulative evaluations score
Career Outcomes
AI Solutions Engineer
₹5 - ₹47 LPA
Deploy AI systems, automate workflows & integrate business AI tools.
Source: GlassdoorSoftware Dev Engineer
₹12 - ₹37.4 LPA
Scalable product engineering & AI-integrated software systems.
Source: 6figrML Engineer
₹10 - ₹35 LPA
Build & deploy production ML models across fintech, e-commerce & health-tech.
Source: Industry avg3× avg salary vs non-tech peers after 1 year
70% of AI engineer roles require React + Python stack
51% rise in AI hiring in Hyderabad
Companies like Google and Infosys are actively hiring for AI Engineers + Data Scientists from Hyderabad right now
What will you learn?
Go from zero to job-ready in AI/ML with beginner-friendly, industry-aligned curriculum from I-Hub IIT Patna, taught in Telugu — covering Python, data analysis, machine learning, and generative AI with hands-on projects. Built for beginners, designed to get you building real things fast.
Meet our Instructor Team
Sainathreddy Sankepally
Ex-Cred, Swiggy
Prasad Seema Kurthi
AI Star, ex-Amex, Grab, University of Virginia
Balaji Chippada
Warner Bros Discovery
Sainathreddy Sankepally
Ex-Cred, Swiggy
Prasad Seema Kurthi
AI Star, ex-Amex, Grab, University of Virginia
Balaji Chippada
Warner Bros Discovery
*Note: Instructors teaching your batch may change based on specific module expertise, or circumstances such as personal emergencies, unavailability etc.
Course Details
Foundations of Data
- AI vs ML vs GenAI landscape Git/GitHub/CLI VS Code/Colab environments & secrets
- Python for Data (types, flow, functions, files) · notebooks discipline
- NumPy + pandas (indexing, joins/merge, groupby, missing values)
- SQL lite (SELECT/WHERE/GROUP BY + one JOIN) · spreadsheets (pivots, XLOOKUP) · pandas ↔ SQL mental model
- Plotting & storytelling (matplotlib/plotly) · EDA checklist
- APIs (requests, JSON) + basic ethics/ToS · ingest → clean → EDA snack app (optional Streamlit)
Mini Projects Unlocked
CryptoWatch — Real-Time Market Sentiment Tracker
FoodSafety Insights — Restaurant Inspection Intelligence
TrendPulse — What's Actually Trending Right Now
Classical ML
- ML workflow & habits: problem framing, train/validation/test split, baselines, cross‑validation, metric tables
- Data prep: missing values, duplicates, categorical encoding, scaling, leakage guard, simple feature engineering (dates, counts), class imbalance basics
- Regression: Linear Regression + regularization; metrics MAE/RMSE/R²; quick error analysis
- Classification: Logistic Regression; Trees & Random Forests; metrics accuracy, precision/recall, F1, ROC‑AUC; threshold tuning
- Model comparison & selection: choose by metric + simplicity
Mini Projects Unlocked
ChurnGuard — Predicting Customer Exit Before It Happens
LoanLens — Automated Credit Risk Assessment
RentRight — Predicting Fair Apartment Prices
GenAI & Agents
- LLM fundamentals: tokens, context windows, temperature/top‑p, cost/latency basics
- Prompting patterns: role, few‑shot, CoT; tiny prompt‑eval set
- Agents 101 (basics): single agent, 1–2 tools, JSON schemas, retries/backoff, hard stop; mini‑build (CSV Analyst or FAQ Helpdesk)
- Function/Tool calling: structured outputs (JSON/validation), idempotent tool design
- Shipping Sprint (FastAPI): wrap the agent as an API ( /chat ) with Pydantic schemas, env/secrets, logging + request IDs; deploy to Render or HF Spaces; run a 10‑prompt live eval
- RAG 101: embeddings, chunking, retrievers, vector stores; RAG eval (answer correctness & context recall), semantic search
- Agents + RAG: reuse the Agents 101 loop with a retriever tool; same eval harness
- Orchestration (intro): LangGraph basics—nodes, transitions, retries; ship a small agent flow
Mini Projects Unlocked
DataGenie — Natural Language Data Analyst
SupportAI — Intelligent FAQ Helpdesk Agent
ResearchPilot — Automated Market Research Agent
Multi-Model Answerboard (AI Fiesta-style)
One chat, multiple model answers side-by-side with cost/speed badges; toggle RAG for cited answers and add smart routing + A/B prompt
English & Soft Skills Training
Everyday English for Self-Expression
Learn how to talk about yourself comfortably and confidently in common situations.
Building Clear and Correct Sentences
Strengthen sentence formation so your English sounds natural and complete.
Speaking with Impact and Awareness
Learn to organise thoughts, speak smoothly, and communicate with confidence.
Professional Communication & Soft Skills
Apply spoken English skills to professional and workplace-like situations.
Please Note :- "Due to the evolving nature of the industry expectations and partner institute feedback, some syllabus aspects may change. Any updates will be communicated during the Inauguration Session(s) or at the start of the relevant module"