What is the total course fee?

The original course fee is ₹1,25,000, but with a flat 25% discount, you can enroll at ₹94,999 (Inclusive of GST) if you opt for full payment mode.

Are EMI options available?

Yes! With a flat 25% discount, the EMI drops from ₹9,700 to ₹7,917/month (Inclusive of GST).

What are the payment options for enrolling in this course?

You can pay the full amount or choose EMI plans for flexible payment options.

Does the course fee cover all study materials and sessions?

Yes, the fee includes live expert-led sessions, self-paced modules, mentor support, and placement assistance.

Who are the mentors for the Zen Class Data Science Program?

Our mentors are industry experts from top companies with extensive experience in Data Science, AI, and Machine Learning. They provide hands-on guidance, real-world insights, and career support throughout the program.

How do mentors help during the course?

Mentors provide live interactive sessions, one-on-one doubt resolution, and project feedback to help you master complex concepts and build job-ready skills.

Will I have access to mentors after the course ends?

Yes! Even after course completion, you can seek mentor guidance through live Q&A sessions, alumni networking, and career support forums.

How can I interact with mentors?

You can connect with mentors through live sessions, doubt-solving forums, and one-on-one mentorship calls for personalized guidance.

Who is eligible to take up the Zen Class Data Science Program?

Anyone with a graduation degree and an interest in Data Science can enroll. This program is ideal for graduates, job seekers, and early professionals looking to switch careers.

What is the duration of the Zen Class Data Science Course?

The Zen Class Data Science Program offers two flexible options: a 3-month weekday batch for intensive learning and a 5-month weekend batch, which is suitable for working professionals or those with a busy schedule.

Do I need prior coding knowledge for this course?

No, prior coding experience is not mandatory. You can start from scratch and still master programming concepts relevant to Data Science.

Is this program conducted online or offline?

The Zen Class Data Science Program is 100% online, featuring live sessions by industry experts and self-paced modules for flexible learning.

4.5M+: Learners Upskilled
1000+: Hiring Partners

IITM Pravartak Certification

Data Science & Gen AI Program

Master Data Science, ML, Deep Learning & Gen AI, designed for professionals.

6 months
Online Classes
3 Languages: English, Tamil & Hindi

Hear from our CEO

Why Data Science & Gen AI in 2026?

Arunprakash M, CEO & Co-Founder of HCL GUVI — “Data Science isn’t just a technical skill—it’s a career advantage. We built this program to help you break into the field.”
Arunprakash M
Founder & CEO, HCL GUVI

Start your Data Science Career Today

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6 Months: Weekend & Weekday
1:1: Mentor Support
Placement Support: with mock interviews
10+: Projects

Transition Stories

Our Alumni Journeys

Mounica
BI AnalystJr. AI ML Engineer
Sutharsan C
Test ExecGen AI Developer
Mahaalakshmi B
TechJr. AI ML Engineer
Mohd Ishtiyaque
TeacherSenior Analyst
Teaching → Tech
Siranjeevi
FresherAI Engineer
Amruthavarshini M
FresherData Analyst
Karthikeyan
Mech EngineerNLP Engineer
5X Salary Growth

Top Companies

Our Students Work at

Program eligibility

Who is our Program for?

60%

of our alumni are from Non IT backgrounds

No Coding Background Needed: Start with the fundamentals and build your coding skills from the ground up.
Built for Career Switching: Gain job-ready skills, build real-world projects, and get 1-on-1 mentorship to transition into tech.

5X Salary Growth

Karthikeyan

Mech EngineerNLP Engineer

higher salary potential with Data Science upskilling

Expand Your Expertise: Build on your technical background with Machine Learning, Data Science, and GenAI.
Advance Your Career: Apply your skills to real-world projects with 1-on-1 mentorship and become ready for emerging tech roles.

Chinmay Manoj Bhatt

Low Growth IT RoleAssociate AI Engineer

8 LPA

average starting salary for freshers

Build a Strong Foundation: Learn Python, Data Science, and AI from the fundamentals.
Get Career-Ready: Apply your skills through real-world projects and build a portfolio that showcases your capabilities.

Chandreyi Ghosh

FresherAI ML Analyst

Curriculum

What’s Inside our Program?

- Learn Python fundamentals including variables, operators, loops, functions, and data structures
- Work with lists, tuples, sets, and dictionaries for data processing tasks
- Understand object-oriented programming concepts like classes, inheritance, and polymorphism
- Practice file handling, exception handling, and intermediate Python concepts
- Work with APIs and JSON data for real-world integrations
- Build coding confidence using Jupyter Notebook, VS Code, and Google Colab
- Develop strong programming foundations required for Data Science and AI workflows
- Understand database fundamentals including DBMS, RDBMS, tables, and schemas
- Learn SQL queries using SELECT, WHERE, ORDER BY, and DISTINCT operations
- Perform data manipulation using INSERT, UPDATE, DELETE, and aggregation functions
- Work with joins including INNER JOIN, LEFT JOIN, and RIGHT JOIN
- Understand subqueries, CTEs, and window functions for advanced analytics
- Explore structured vs unstructured data and modern data warehousing concepts
- Build practical database querying skills for analytics and reporting workflows
- Learn descriptive statistics including mean, median, mode, and standard deviation
- Understand probability concepts, random variables, and conditional probability
- Explore distributions including normal, binomial, and Poisson distributions
- Work with sampling techniques and confidence intervals
- Perform hypothesis testing for business decision-making
- Learn statistical techniques like T-test, Chi-square, and ANOVA
- Apply A/B testing concepts for real-world analytics scenarios
- Work with Pandas DataFrames for loading, filtering, and analyzing datasets
- Perform data cleaning including handling missing values, outliers, and duplicates
- Conduct univariate, bivariate, and multivariate exploratory data analysis
- Create visualizations using Matplotlib and Seaborn
- Build charts including histograms, boxplots, scatter plots, and line charts
- Learn feature engineering techniques like encoding and feature selection
- Prepare real-world datasets for machine learning workflows
- Understand supervised, unsupervised, and reinforcement learning fundamentals
- Build regression models for prediction and forecasting tasks
- Learn Logistic Regression for binary classification problems
- Evaluate models using metrics like Accuracy, Precision, Recall, and F1 Score
- Understand MAE, MSE, RMSE, and ROC-AUC evaluation techniques
- Learn overfitting, underfitting, and cross-validation concepts
- Build practical machine learning workflows using Scikit-learn
- Build Decision Tree and Random Forest models for predictive analytics
- Learn boosting algorithms including XGBoost, LightGBM, and CatBoost
- Work with KNN and Support Vector Machines for classification problems
- Understand ensemble learning and model optimization techniques
- Explore model explainability using SHAP, LIME, and feature importance methods
- Learn time series forecasting concepts including trend and seasonality analysis
- Build advanced machine learning models used in real-world business systems
- Learn clustering techniques including K-Means and Hierarchical Clustering
- Work with DBSCAN for density-based clustering applications
- Understand dimensionality reduction using PCA, t-SNE, and UMAP
- Build customer segmentation systems for marketing analytics
- Learn anomaly detection concepts for fraud and risk analysis
- Explore market basket analysis and pattern discovery techniques
- Analyze unlabeled datasets for business insights and decision-making
- Build recommendation engines using collaborative and content-based filtering
- Learn similarity measures including cosine similarity
- Work with matrix factorization and ALS recommendation techniques
- Understand embedding-based recommendation concepts
- Build production-ready machine learning pipelines using Scikit-learn
- Learn column transformers and end-to-end pipeline design
- Structure scalable ML workflows for real-world deployment scenarios
- Understand neural networks, perceptrons, and multi-layer architectures
- Learn activation functions including ReLU, Sigmoid, and Tanh
- Work with gradient descent optimization techniques
- Explore advanced optimizers like Adam and RMSProp
- Learn regularization techniques including dropout and early stopping
- Understand overfitting and model generalization concepts
- Build deep learning models using TensorFlow and PyTorch
- Learn text preprocessing and text cleaning workflows
- Understand tokenization, stemming, and lemmatization techniques
- Work with Bag of Words and TF-IDF text representation methods
- Build sentiment analysis applications using NLP techniques
- Create text classification systems for real-world use cases
- Understand foundational NLP concepts used in AI applications
- Build practical NLP workflows using machine learning approaches
- Understand transformer architecture and self-attention mechanisms
- Learn pre-trained language models like BERT and modern LLM concepts
- Build applications for text generation, summarization, and semantic search
- Explore embeddings and vector database workflows
- Understand Retrieval-Augmented Generation (RAG) systems
- Learn how to reduce hallucinations and improve AI response quality
- Work with Hugging Face and LangChain for modern AI applications
- Learn image processing fundamentals and image transformations
- Understand convolution operations and CNN architectures
- Work with pooling layers and feature extraction techniques
- Build image classification applications using deep learning
- Explore transfer learning concepts for computer vision workflows
- Learn practical computer vision pipelines using OpenCV
- Build visual intelligence applications using TensorFlow and PyTorch
- Understand ETL and ELT workflows used in modern data systems
- Learn batch processing and streaming data concepts
- Explore data lakes and data warehouse architectures
- Understand scalable data engineering workflows
- Learn industry tools including Apache Spark and Apache Airflow
- Explore cloud-based analytics systems like Snowflake and BigQuery
- Build awareness of production-grade data infrastructure systems
- Understand the end-to-end machine learning lifecycle
- Learn model deployment and production workflow concepts
- Work with experiment tracking and model versioning systems
- Build APIs for machine learning models using FastAPI
- Understand batch vs real-time prediction workflows
- Learn containerization concepts using Docker
- Build deployment-ready ML systems using modern MLOps practices
- Understand automated model selection workflows
- Learn hyperparameter tuning concepts for model optimization
- Explore AutoML platforms used in modern AI systems
- Work with cloud ML services for scalable AI workflows
- Learn AWS SageMaker for model training and deployment
- Understand cloud-native machine learning workflows for enterprises
- Learn prompt engineering techniques including zero-shot and few-shot prompting
- Build AI-powered analytics workflows using LLMs
- Generate SQL queries and automated insights using Generative AI
- Understand AI agents and workflow automation systems
- Build applications that can chat with CSVs and databases
- Develop practical Generative AI applications for real-world business use cases

10+ Projects

Industry-Ready Projects

Smart Movie Recommendation System
Build recommendation engines using collaborative and content-based filtering techniques to improve personalization.
Crop Disease Detection System
Build computer vision applications that identify crop diseases from leaf images using CNNs and image classification models
AI-Powered Data Analysis
Develop intelligent analytics applications that can chat with CSV files and databases, automate insight generation.
Retail Sales Analysis & Business Insights System
Build data-driven analytics systems to identify revenue trends, customer behavior, and actionable business insights using real-world retail datasets.
Customer Churn Prediction System
Develop machine learning models that predict customer drop-offs and improve retention strategies using classification algorithms and feature engineering.
Customer Segmentation Engine
Create intelligent customer segmentation systems using clustering techniques for personalized marketing and targeted campaigns.
AI-Powered Sentiment Analysis System
Analyze customer reviews and social media conversations using NLP techniques, TF-IDF, and machine learning models.
Disease Prediction Using Deep Learning
Develop deep learning models that assist in disease prediction and healthcare analytics using neural networks and structured medical data.
Fraud Detection & Risk Scoring System
Create fraud detection pipelines using anomaly detection, machine learning, and real-time prediction systems for FinTech applications.
RAG-Based Document Intelligence Assistant
Build document intelligence systems that retrieve relevant information from PDFs and reports using RAG pipelines and vector databases.
End-to-End AI Decision Intelligence Platform
Create a complete AI-powered decision support platform combining analytics, machine learning, and Generative AI workflows across multiple domains.

Your Tech Stack

Tools you’ll Master

Python
NumPy
Pandas
Seaborn
AWS
Docker
Airflow
LangChain
OpenAI
n8n
MySQL
Gemini

Session Preview

Take a Peek at a Real Live Session

Watch a class preview and experience learning with HCL GUVI.

Mentors

Top 1% Industry Experts Teach You

Anamika Chhabra
Lead AI and DS Instructor
Poonam Adhikari
Instructor
Abhishek S R
Senior Engineer Consultant
Shashank S
Assistant Professor
Sruthi Baskar
Senior Lead Data Scientist
Ashish Tiwari
Lead Data Scientist
Jasmine Jennifer J
Data Scientist
Rohit Ranjan Srivastava
Consultant
Ajay Shukla
Data Scientist
Mohammad Afsar
AI/ML Computational Science Specialist
Parthiban Jayachandran
AI Architect
Aishwarya S
Data Engineer

Gen AI Integration

Learn Data Science for the AI Era

GenAI Tools Built In

Master ChatGPT, Copilot, and LLMs alongside Python and SQL to code faster and analyze smarter.

Next-Gen Projects

Build end-to-end Machine Learning, NLP, and Generative AI applications for your portfolio.

Modern Tech Stack

Learn prompt engineering, vector databases, and fine-tuning—the exact skills 2026 tech employers demand.

Placement Assistance

Dedicated Placement Support

Mock Interviews

Practice personalized interview scenarios

Resume Review

Expert feedback on resumes.

1:1 Mentorship

Direct guidance from mentors

Job Referrals

Direct hiring opportunity access

Dual Certification

A Certificate that Opens Doors

IITM Pravartak Certification

A premier Technology Innovation Hub under India's DST & NM-ICPS mission.

HCL GUVI Certification

An HCL Group company, incubated by IIT Madras and IIM Ahmedabad.

Trusted by your favourite creators

Recommended by your Fav Creators & Influencers

Open Letter

1.3 M+ Subscribers

Theneer Idaivelai

3.7 M+ Subscribers

Testimonials

Success Stories of Our Learners

“After 8 years in teaching, switching careers felt impossible. HCL GUVI’s 1:1 Industry expert mentorship helped me acquire practical analytics skills”
Mohd Ishtiyaque
TeacherSenior Analyst
“Getting my dream tech role became possible with consistent placement support, resume & interview prep guidance from HCL GUVI.”
Chandru G
Ops LeadTechnical Lead

EMI Options Available

Pricing

EMI Starts at

₹4799^*/ month

Full Payment ₹99,999 ~~₹1,24,999~~

IITM Pravartak Certification
Online Live Classes
1:1 Mentor Support
Available in English, Tamil & Hindi
6 Months for Weekday & Weekend
10+ Future Ready Projects
Build Real AI Experience
16 Industry Grade Modules

Connect with our Program Counselor+91- 9736097320

FAQ

Answers for your Questions

How does HCL GUVI assist with job placements?

Our placement support includes mock interviews, resume building, and mentorship sessions with industry experts. You also gain access to HyreNet, our AI-powered job portal, to explore job opportunities.

How many students have been placed through the support offered by HCL GUVI's Zen Class Data Science Program?

Over 10,000+ learners have successfully transitioned into Data Science careers with our placement guidance and expert mentorship.

Will I be connected to hiring partners after completing the course?

Yes! You'll be connected with our 1000+ hiring partners and gain better access to networking opportunities for exploring potential job openings.

What if I don't get placed immediately?

Through HCL GUVI's hiring platform, HyreNet, you can continue to access new job opportunities, resume reviews, and interview preparation as part of our placement network.

Data Science & Gen AI Program

Why Data Science & Gen AI in 2026?

Start your Data Science Career Today

Our Alumni Journeys

Our Students Work at

Who is our Program for?

What’s Inside our Program?

Industry-Ready Projects

Smart Movie Recommendation System

Crop Disease Detection System

AI-Powered Data Analysis

Retail Sales Analysis & Business Insights System

Customer Churn Prediction System

Customer Segmentation Engine

AI-Powered Sentiment Analysis System

Disease Prediction Using Deep Learning

Fraud Detection & Risk Scoring System

RAG-Based Document Intelligence Assistant

End-to-End AI Decision Intelligence Platform

Tools you’ll Master

Take a Peek at a Real Live Session

Top 1% Industry Experts Teach You

Learn Data Science for the AI Era

GenAI Tools Built In

Next-Gen Projects

Modern Tech Stack

Dedicated Placement Support

Mock Interviews

Resume Review

1:1 Mentorship

Job Referrals

Trust of HCL Group

A Certificate that Opens Doors

IITM Pravartak Certification

HCL GUVI Certification

Recommended by your Fav Creators & Influencers

Success Stories of Our Learners

Pricing

Answers for your Questions