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Gen AI-powered Data Science with Machine Learning

Duration 6 Months
Scholarship Upto 50%*
For Enquiry 1800 210 2020

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The Complete Curriculum

Program Curriculum

Module1: Excel & GenAI for Analytics

Module 1
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Study

• Excel For Business Problem-solving (CRISP-DM).

• Advanced Formulas, Logical Functions & Analytics Tools.

• Goal Seek, Scenario Manager & Data Tables.

• GenAI For Formula Generation, KPI Explanation & Summaries.

Create

• Superstore Sales Dashboard With GPT

• Automated Reports Using VBA + Gen AI

• Real-world Demand Simulation On Kaggle Datasets

Attempt

• 50+ Excel Interview Questions

• Problem-solving & KPI Explanation Practice

• Scenario-based Excel Tests


Module 2: Power BI & Tableau

Module 2
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Study

• End-to-end ETL & Data Modeling.

• DAX Fundamentals to Advanced Use Cases.

• Power BI & Tableau Visual Analytics.

• Data Storytelling With Gen AI-assisted Narratives.

Create

• Home Loan Default Dashboard (DAX Case Study)

• Retail & Superstore Profitability Dashboards

• Dynamic Tableau Dashboards with Parameters & Joins

Attempt

• 100+ DAX & BI Questions

• Dashboard Critique & Storytelling Exercises

• BI Scenario-based Case Studies

• 4 Weekly Tests

Module 3: SQL (With Cloud Integration)

Module 3
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Study

• Relational Databases & ER Modeling.

• Advanced SQL: Joins, Subqueries, Window Functions.

• Query Optimization Using Gen AI.

• SQL + Azure Cloud Integration.

Create

• RSVP Movie Database

• Marketplace Demand-supply Analysis

• Cloud-connected Analytics Workflows

Attempt

• 200+ SQL Interview Questions

• Complex Joins & Case-based Problems

• 1 Employability Test

• 2 Weekly Tests

Module 4: Python For Data Analysis

Module 4
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Study

• Python Fundamentals, Logic & Data Structures.

• Functional Programming & OOP.

• Numpy, Pandas & Data Visualization.

• EDA Techniques with Genai Support.

Create

• Credit Risk Analysis

• Uber Trip Demand Analysis

• Stock Market Analysis Using Yfinance

Attempt

• 250+ Python Coding Questions

• OOP & EDA Interpretation Tests

• Leetcode & Real-dataset Challenges

• 1 Employability Test


Module 5: Statistics & Probability (AI-assisted)

Module 5
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Study

• Descriptive & Inferential Statistics.

• Hypothesis Testing, ANOVA & Chi-square.

• Statistical Interpretation Using AI Tools.

Create

• Customer Churn Distribution Analysis

• Bank Credit Scoring Statistical Report

Attempt

• Statistics Problem Sets

• Business Interpretation & Decision-based Tests


Module 6: AI & Machine Learning

Module 6
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Study

• 18+ ML Algorithms & ML Pipelines.

• Feature Engineering & Hyperparameter Tuning.

• Model Explainability (SHAP, LIME).

• Deep Learning: CNNS, RNNS, LSTMS.

• Generative AI, RAG & LLM Workflows.

• Prompt Engineering For NLP, Vision & Agents.

Create

• Credit Risk & Churn Prediction ML Models

• Demand Forecasting System

• LLM-powered Apps (Chatbots, Semantic Search)

• Model Deployment Using Flask, Streamlit & Gradio

Attempt

• ML & AI Case-study Questions

• Model Evaluation & Explainability Tests

• End-to-end Capstone Project


Get Future-Ready with the Latest Tools

Module 7
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  • Python
  • pandas
  • NumPy
  • matplotlib
  • seaborn
  • tableau
  • Plotly
  • Power BI
  • scikit-learn
  • Keras
  • TensorFlow
  • OpenAI
  • Excel
  • Azure
  • gradio
  • Lime
  • Flask
  • Hugging Face
  • Streamlit
  • MySQL
  • GitHub
  • SQL
  • kaggle
  • Shap


Learn From The Best

Mentored by Top Professionals

Faculty Members
A

Alok Chauhan

upGrad
school Data Science & AI
star Alok Chauhan, Instructor Alok Cha10+ years of experience in DA/DS, Ex-L&T, New Holland, Data Arc, has served on site for clients in Honkong, Nepal and Germany
LinkedIn Profile
S

Shalini Singh

upGrad
school Data Science & AI
star 12+ years of experience in data analytics, research, consultancy and academia, Ex-Deloitte having experience working with various ministries.
LinkedIn Profile
S

Sirisha Pamidipati

upGrad
school Data Science & AI
star Skilled in data analytics and data science. Previously worked as Sr. Faculty - Data Analytics Training in ExcelR Edtech Private Limited, Bengaluru. Ex - faculty of BITS – Pilani Hyderabad Campus
LinkedIn Profile
Certification: Your Credential

Certificate in Gen AI- Powered Data Science Program


Certificate
Is This Right For You?

Who is this program right for?



Industry Case Studies & Real Projects

Learn through real-life industry projects sponsored by top companies across industries

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Airbnb Case Study
Understand the factors that drive the Airbnb business and help the team leads tackle problems and bottlenecks through extensive data analysis on UI tools.
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Uber Trip Demand Analysis
Analyze Uber ride data to uncover demand patterns by time and location and build a model to forecast trip demand for smarter pricing and driver allocation.
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Movie Dataset from RSVP movies ( SQL Case Study)
In this assignment, you will work on a movies dataset using SQL to extract exciting insights about popular films and the factors that drive a film.
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Advanced ML Case Study - Telecom Churn
Telecom companies often face the problem of churning customers due to the competitive nature of the industry. Help a telecom company identify customers that are likely to churn and make data-driven strategies to retain them from the perspective of a data scientist.
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Got Questions?

Frequently Asked Questions

Who can apply for the Gen AI Powered Data Science Program? expand_more
Graduates from any science or technology stream (B.E., B.Tech, B.Sc., BCA, etc.) are eligible to apply. Students currently pursuing their graduation in these streams can also apply. No prior coding background is required.
What is the admission process? expand_more
The admissions process is completely online. The following are the key steps in the application process:

Step 1 - Fill Application form : Fill out an application giving your basic profile details.
Step 2 - Shortlisting and block payment: Once shortlisted, pay a block fee (Non-refundable)
Step 3 - Offer letter and payment: Balance to be closed within 7 days or batch start date whichever is sooner.
Do I need prior coding experience? expand_more
No prior programming background is required. The curriculum typically starts with foundations and gradually moves toward advanced analytics, machine learning, and real-world applications.
Is this program suitable for freshers? expand_more
Yes. Freshers looking to build strong, job-ready data skills can apply. Additional effort in practice and projects will help strengthen employability.

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