Choose your batch
Each batch has its own dates, timing and fee. Pick one to see its details and book.
Live weekend classes
AI & Data Science Program
Live weekend classes and 12 industry projects, from your first line of Python to job-ready AI engineering.
- 12 months
- Sundays
- 3 hours a week
- 12 industry projects
- 14 industry tracks to choose from
- Beginner → Advanced → Expert
Learn AI and data science on weekends, alongside college or work. Every month you learn one area in live classes and finish an end-to-end project on real industry data, so by the end you have 12 projects to show employers. Classes are live and recorded, taught by industry practitioners, in small batches.
Fees
Monthly
₹2,999 / month
Pay each month (UPI AutoPay or card). Cancel any time; access runs to the end of the paid month.
One-time
₹32,390 for 12 months
The whole program, plus recordings of earlier batches.
How joining works
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1
Book a free seat
No payment now. Your seat is held in the next batch.
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2
Pay when the batch is confirmed
We email you; pay within 48 hours to keep your seat.
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3
Join live weekend classes
Classes are recorded, so you can catch up on anything you miss.
Choose your industry track
Everyone learns the same AI skills each month. Your 12 projects come from the industry you choose, so you finish with a portfolio for the jobs you want.
Cybersecurity & Digital Trust: AI detects intrusions, phishing and scams, finds fraud and helps security teams respond faster.
Free courses and datasets for Cybersecurity & Digital Trust →Month by month
Every month ends with an end-to-end project you can show employers, from Cybersecurity & Digital Trust.
Month 1 Python for data Beginner
Python basics, data types, loops and functions; working with files, CSV and JSON; virtual environments, Jupyter and Git.
Project · Cybersecurity & Digital Trust
Login log auditor
Read server login logs, find brute-force attempts and list the most suspicious IP addresses.
Month 2 Data analysis with pandas and SQL Beginner
pandas DataFrames, cleaning and joining data, group-by and pivot tables; SQL queries, joins and window functions.
Project · Cybersecurity & Digital Trust
Security events in SQL
Load firewall and security events into a database and use SQL to find unusual activity.
Month 3 Statistics and data visualisation Beginner
Descriptive statistics, probability, sampling, hypothesis tests and A/B testing; charts with Matplotlib, Seaborn and Plotly.
Project · Cybersecurity & Digital Trust
Phishing patterns study
Compare features of phishing and genuine web addresses with statistics and show which ones give phishing away.
Month 4 Machine learning foundations Beginner
Supervised learning, regression and classification, train/test splits and cross-validation, scikit-learn pipelines.
Project · Cybersecurity & Digital Trust
Phishing URL classifier
Predict whether a web address is a phishing site from its features with classification models.
Month 5 Feature engineering and model evaluation Advanced
Feature engineering, imbalanced data, ensembles (random forests, XGBoost, LightGBM), metrics, explainability with SHAP.
Project · Cybersecurity & Digital Trust
Network intrusion detection
Detect rare attacks in network traffic with gradient boosting on a public intrusion dataset, and explain alerts with SHAP.
Month 6 Deep learning with PyTorch Advanced
Neural networks, training loops, CNNs for images, transfer learning, GPUs on Google Colab.
Project · Cybersecurity & Digital Trust
Malware family classifier
Turn malware files into images and train a model that recognises their family, using a public research dataset.
Month 7 Natural language processing Advanced
Text cleaning, embeddings, transformers and Hugging Face, fine-tuning for classification, multilingual models.
Project · Cybersecurity & Digital Trust
Scam SMS and email detector
Detect phishing and UPI scam messages in English and Hindi, and explain what makes each one suspicious.
Month 8 Time series and forecasting Advanced
Trends and seasonality, ARIMA and Prophet, gradient-boosted forecasts, evaluating forecasts over time.
Project · Cybersecurity & Digital Trust
Traffic anomaly detection
Find unusual spikes in network traffic over time that may signal an attack, and compare methods.
Month 9 Large language models and RAG Expert
How LLMs work, prompting, embeddings and vector databases, retrieval-augmented generation, evaluating answers.
Project · Cybersecurity & Digital Trust
Security advisories assistant
Build a RAG assistant over CERT-In advisories and the DPDP Act that answers security questions with sources.
Month 10 AI agents and tool use Expert
Function calling, multi-step agents, planning and memory, guardrails and evaluation of agent behaviour.
Project · Cybersecurity & Digital Trust
SOC triage agent
Create an agent that reads security alerts, adds threat information, rates them and drafts an incident report for an analyst.
Month 11 MLOps and deployment Expert
APIs with FastAPI, Docker, CI/CD, model registries, monitoring and data drift, cloud deployment basics.
Project · Cybersecurity & Digital Trust
Secure model deployment
Deploy a model API with authentication and rate limits, and test how it holds up against adversarial inputs.
Month 12 Capstone and career preparation Expert
Scoping a real problem, project planning, portfolio, résumé and GitHub reviews, mock technical interviews.
Project · Cybersecurity & Digital Trust
Cybersecurity capstone
Solve a real security or fraud problem end to end with a mentor and present it to a panel.
What you can watch
| Monthly | Your batch's live classes and recordings, from the batch start to the current month, while your payments are up to date. |
|---|---|
| One-time | Your whole batch, plus recordings of earlier batches. |
| Joining a running batch | That batch's earlier recordings, so you can catch up. |
| After you finish | 12 more months of free access. |