Advanced Data Analytics in Management
Features
Programme Overview
The Advanced Data Analytics in Management certificate programme by the Continuing Education Programme (CEP) at IIT Delhi is a comprehensive 6-month course designed to help professionals master data-driven decision-making and lead organisational transformation. Spanning 103 learning hours across 8 core modules, this rigorous program bridges academic excellence with practical industry applications. Offered by one of India's premier research institutions—ranked #2 in the NIRF Engineering Rankings 2025 and 1st in India in the QS World University Rankings: Southern Asia 2027—this course awards a prestigious CEP, IIT Delhi certification upon successful completion.
₹ 1,45,000 + 18 % GST
Class Schedule
Every Saturday: 10:00 AM – 1:00 PM (subject to change)
Eligibility Criteria
Graduation in any discipline.
Programme Highlights
CEP, IIT Delhi Credential
End-to-End Analytics Stack
Working-Professional Friendly
AI And Gen AI Integration
Real-World Capstone Project
Management-First Design
Programme Modules
Understanding Data and Decision Making
Data Science vs. Data Analytics vs. Business Analytics
Descriptive, Predictive and Prescriptive Analytics
Data Measurement and Data Cleaning
Descriptive Analytics
Data Visualization
Data Mining
Exploratory Data Analysis (EDA)
Predictive Analytics Overview
Supervised vs. Unsupervised Machine Learning
ANOVA Models
Inferential Data Analysis & Hypothesis Testing
Regression vs. Classification vs. Clustering
Regression Analysis & Logistic Regression
K-Means Clustering & Hierarchical Clustering
Principal Component Analysis (PCA)
Market Basket Analysis
Prescriptive Analytics
Optimization Models
Monte Carlo Simulation
Multi-Criteria Decision Making (MCDM)
Introduction to Artificial Intelligence in Business
Machine Learning Lifecycle in Organisations
Generative AI (ChatGPT, LLMs and Business Applications)
Prompt Engineering for Analytics Tasks
AI-Powered Analytics Automation (Insight Generation, Reporting)
AI Agents and Workflow Automation in Business
Marketing Analytics: Customer Segmentation, Campaign Performance, CLV, Personalisation & Recommendation Systems
Financial Analytics: Risk-Return Analysis, Forecasting, Fraud Detection and Credit Analytics
Operations Analytics: Demand Forecasting, Inventory Optimisation, Process Analytics, Supply Chain Analytics with AI
HR Analytics: Attrition Prediction, Workforce Planning, Performance Analytics, AI in Hiring & Talent Analytics
Big Data Concepts (Volume, Velocity, Variety)
Hadoop and Spark Ecosystem
Data Lakes vs. Data Warehouses
Cloud Platforms Overview (AWS / GCP / Azure)
Modern Data Stack (Snowflake, BigQuery)
Real-Time Analytics and Streaming Basics
Industry-based dataset and problem statement
Domain-specific tracks: Marketing / Finance / Operations / HR
End-to-end flow: Problem Identification > Data Preparation > Modelling > Insights > Recommendations
Domain-specific tracks: Marketing / Finance / Operations / HR
PROGRAMMING & DATA MANIPULATION
Python 3.x
Jupyter
Google Colab
NumPy
Pandas
Scikit-learn
MACHINE LEARNING
LightGBM
XGBoost
Scikit-learn
DEV & COLLABORATION
VS Code
GitHub
PuLP
Kaggle Notebooks
OR-Tools
AI & GENAI
OpenAI API
ChatGPT
Prompt Engineering
Hugging Face
PRESCRIPTIVE / OPTIMISATION
Prescriptive / Optimisation
OR-Tools (Google, free)
DATA VISUALISATION
Power BI
Tableau Public
Matplotlib
Seaborn
Plotly
CLOUD & BIG DATA
BigQuery
Snowflake
Databricks
AWS Free Tier
GCP
Apache Spark
*Disclaimer - "The list of tools and topics mentioned is indicative and may be modified as per programme requirements and at the discretion of the Programme Coordinator."
Learning Outcomes
Prepare and clean any business dataset; build impactful dashboards and conduct exploratory analysis to surface patterns and anomalies with confidence.
Build and evaluate regression, classification, and clustering models; perform statistical inference using hypothesis testing, ANOVA, and PCA.
Formulate optimization problems, run Monte Carlo simulations for risk analysis, and apply MCDM frameworks to complex multi-objective business decisions.
Leverage GenAI tools (LLMs, ChatGPT) for analytics automation, use prompt engineering for data tasks, and identify AI-driven opportunities in your organization.
Apply analytics across your functional domain — build customer segmentation models, CLV analyses, fraud detection pipelines, and workforce attrition predictors.
Navigate cloud analytics platforms, understand big data architecture, and independently solve a real business problem with a full analytical pipeline and professional deliverables.
Tools
Python
Jupyter
Git Hub
AWS
Scikit-learn
Tableau
Hugging Face
Matplotlib
Pandas
Programme Coordinator
Professor Seema Sharma
Professor
Department of Management Studies
Indian Institute of Technology Delhi
Professor Sharma is a distinguished academic in Economics at IIT Delhi's Department of Management Studies, with research spanning Sustainable Development, Productivity Analysis, Policy Research, and Socio-economic Studies. Her publications appear in top journals by Springer, Elsevier, Taylor & Francis, Sage, and Emerald. She has presented research internationally across the USA, Japan, Australia, Thailand, Indonesia, and Czech Republic, and teaches Managerial Economics, Statistical Analysis, and Advanced Data Analysis to MBA and PhD students at IIT Delhi.
Author of Statistics for Business and Economics — published by Wiley (global academic publisher)
Outstanding Young Faculty Fellowship Award, Teaching Excellence Award by IIT Delhi
Best Professor in Economics — Hindustan Unilever-BSA-Dewang Mehta Business School Award, 2012
Research funded by the Corporate & Various government agencies like ICSSR, Ministry of Consumer A Ministry of Environment, Ministry of Agriculture, & Consumer Khadi & Village Industries Commission.
Leading Rural Entrepreneurship mission if government of India under UNNAT Bharat Abhiyan
Programme Sample Certificate
Candidates must score at least 40% score to get Successful Completion Certificate
Minimum attendance of 50% is required for the Participation Certificate
e-Certificate issued by CEP, IIT Delhi on successful completion
The organizing department of this programme is the Department of Management Studies, IIT Delhi
Installment Schedule
Programme Fee INR 1,45,000 + 18% GST
Instalment | Date | Amount (₹)** |
Application Fee | Application Fee | 1,000 + 18 % GST |
1st Instalment | Within 4 days of offer letter rollout | 50,000 + 18 % GST |
2nd Instalment | 6th November, 2026 | 50,000 + 18 % GST |
3rd Instalment | 6th January, 2027 | 45,000 + 18 % GST |
Note:
*GST @ 18% will be charged extra in addition to the fees
The application fee of INR 1,000/- + 18% GST is non-refundable and non-transferable. This fee is in addition to the programme fee and will not be adjusted against the total programme fee.
Refund Policy
Candidates can withdraw within 15 days from the programme start date. A total of 80% of the total fee received will be refunded. However, the applicable tax amount paid will not be refunded on the paid amount.
Candidates withdrawing after 15 days from the start of the programme session will not be eligible for any refund.
If you wish to withdraw from the programme, you must email cepaccounts@admin.iitd.ac.in and icare@timespro.com, stating your intent to withdraw. The refund, if applicable, will be processed within 30 working days from the date of receiving the withdrawal request