Data Science & AI Engineering

Next intake: Next Cohort: 2025-26

DATA SCIENCE & AI ENGINEERING

Python, NumPy, Pandas, Scikit-learn for data analysis

Deep learning with TensorFlow, Keras, and PyTorch

NLP with Hugging Face and NLTK; build intelligent agents

MLOps: MLflow, Kubeflow, FastAPI, Docker workflows

Cloud: AWS & Azure; capstone with industry training and Demo Day

Secure your seat

Duration:10 Months

Live Classes (15+ offline locations or 1:20 online)

Your Learning Journey

A 10-month structured path from data science foundations to advanced AI techniques and MLOps deployment.

Level-1 BEGINNER

Data Science Foundations (3 months)

Master Python, NumPy, and Pandas for data manipulation and exploration.

Month 1

Python for Data Science

Master Python, NumPy, and Pandas for data manipulation and exploration.

•Python basics and libraries

•Data cleaning and preprocessing

•Data visualization with Matplotlib/Seaborn

•Exploratory data analysis

Month 2

Statistics & Machine Learning

Understand probability, regression, classification, and clustering with Scikit-learn.

•Descriptive and inferential statistics

•Linear and logistic regression

•Clustering methods (K-Means, DBSCAN)

•Model evaluation metrics

Month 3

Data Insights & Decision Making

Discover patterns and insights to drive data-informed decisions.

•Feature engineering techniques

•Data storytelling with visualization

•Practical case studies

•Introduction to AI ethics

Level-2 ADVANCED

Advanced AI Techniques (Phase 1 + 3 months)

Build and train neural networks with TensorFlow, Keras, and PyTorch.

Month 4

Deep Learning & Neural Networks

Build and train neural networks with TensorFlow, Keras, and PyTorch.

•Artificial neural networks basics

•Convolutional Neural Networks (CNNs)

•Transfer learning

•Model regularization techniques

Month 5

Natural Language Processing

Explore NLP with Hugging Face, NLTK, and transformer models.

•Tokenization and embeddings

•Sentiment analysis and text classification

•Sequence models (RNN, LSTM)

•Using Hugging Face transformers

Month 6

AI Agents & Autonomous Systems

Develop intelligent agents capable of decision-making in real-world scenarios.

•Multi-agent system basics

•Reinforcement learning introduction

•Autonomous decision workflows

•Practical projects with agents

Level-3 PROFESSIONAL

MLOps & AI Deployment (Phase 2 + 4 months industry training)

Learn CI/CD for ML with MLflow, FastAPI, and Docker.

Month 7

MLOps Foundations

Learn CI/CD for ML with MLflow, FastAPI, and Docker.

•Model versioning with MLflow

•Serving models using FastAPI

•Docker for ML environments

•Intro to Kubernetes

Month 8

Scaling & Monitoring

Deploy production-ready AI systems with monitoring dashboards.

•Monitoring with Prometheus/Grafana

•Model drift detection

•Pipeline automation

•CI/CD integration

Month 9

Cloud AI Deployment

Deploy AI services on AWS and Azure with scalable architecture.

•AWS Sagemaker and Azure ML

•Containerized deployment with AKS/EKS

•Serverless ML APIs

•Cost optimization

Month 10

Capstone & Demo Day

Build a production AI microservice and present at Demo Day.

•End-to-end ML pipeline project

•Ethics and bias mitigation

•Industry mentorship

•Demo Day presentation

Why This Program?

Data Science and AI Engineering are among the fastest-growing career fields worldwide.

Generative AI is Mainstream

Most organizations urgently need skilled data scientists to implement and scale AI solutions.

Higher Salaries with AI Skills

AI expertise opens higher-paying roles across industries and faster career advancement.

Thousands of New Jobs

Data science jobs are projected to grow 36% between 2023–2033 (U.S. Bureau of Labor Statistics).

Generative AI is Mainstream

Most organizations urgently need skilled data scientists to implement and scale AI solutions.

AI expertise opens higher-paying roles across industries and faster career advancement.

Higher Salaries with AI Skills

Thousands of New Jobs

Data science jobs are projected to grow 36% between 2023–2033 (U.S. Bureau of Labor Statistics).

Tools You'll Master

Industry-standard libraries and platforms for data science, deep learning, NLP, and MLOps deployment.

Eligibility

Who Should Apply?

Designed for learners from technical and non-technical backgrounds who want to enter data and AI roles.

Students & Fresh Graduates

Beginner-friendly for those new to data science, statistics, and AI technologies.

Analysts & Business Roles

Operations, business, or analyst professionals looking to upskill into data-driven decision making.

Developers & Career Switchers

Software engineers, IT professionals, or career changers aiming to move into AI engineering and MLOps.

Program Fee

Transparent pricing includes live classes, labs, projects, and capstone mentorship with industry experts.

INR24,000

50% OFF

INR12,000

only

Ready to build production-grade AI systems?

Speak with a career advisor to see how this 10‑month program—from DS foundations to MLOps—fits your goals.

Start Application

Program Benefits

Strong DS foundations: Python, NumPy, Pandas, statistics, and visualization.

Advanced AI: deep learning, NLP, and intelligent agents with TensorFlow/PyTorch & Hugging Face.

MLOps skills: MLflow, Kubeflow, FastAPI, Docker for deploying reliable AI services.

Cloud experience on AWS & Azure for scalable, production-ready ML pipelines.

Capstone + Demo Day: ship a production AI microservice with monitoring and present to industry.