Advanced Certification in Data Science and Decision Science

Certificate Program in Applied Blockchain

Institute: IIT Delhi
Programme Start Date: 9th July 2022
Admission: Closed
Batch Number: 01
Deadline To Apply: 15th June 2022
Programme Type: MDP
Class Timings: Saturday or Sunday: 10:00 a.m. to 5:00 p.m.

Course Overview


The 21st century is ruled by data. The science of data has become indispensable for businesses, as it helps enhance efficiency in understanding their customers and decision-making. Businesses are increasingly relying on data/decision sciences for strategic decision-making. Hence, the role of both Data Scientists and Decision Scientists, are important for business growth.

Programme Overview

IIT Delhi’s Advanced Certification in Data Science and Decision Science is specifically designed to equip professionals with expertise in both the verticals of Data Sciences and Decision Sciences. The objective of the programme is to impart expertise in data handling, analytics, cognitive sciences, and relevant analytical tools and techniques. The advanced curriculum will gear you up for an analytics career that will bring a positive shift in your career graph.


Programme Highlights

  • A programme from IIT Delhi, #5 in NIRF Rankings 2021 in ‘Engineering’ category; and among top 2 Indian Institutes as per QS World University Rankings 2022
  • Contemporary concepts and tools of data & decision sciences
  • Holistic understanding with capstone project implementation
  • Certification from CEP, IIT Delhi

Programme Detail


Live Lectures | Tutorials | Lab Sessions | Guest Lectures

Key Learning Outcomes

After the completion of the programme, the candidate is expected to meet the following objectives:

1. Have a good understanding of business analytics as an overall domain with greater focus on the complex methods of analytics involving data science and decision science.
2. Develop an acumen towards problem solving and implementation of mathematical concepts for complex data analysis.
3. Develop an acumen to understand and analyse datasets with descriptive, predictive, prescriptive and cognitive science algorithms.
4. Enable problem solving ability through hands on exercises and capstone projects.
5. Gear up for a transition towards an analytics career whereby the shift may happen within the organisation or in a new organisation.

Programme Delivery

Live online sessions (Direct-to-Device)

Who Should Attend?

  • Professionals aspiring to gain a foothold in the data sciences and analytics domain
  • Data science professionals seeking to gain in-depth knowledge of the key aspects of analytics and decision sciences
  • Experienced leaders willing to deep dive into decision sciences to gain assistance in their decision-making

Eligibility Criteria

  • Bachelor’s degree with minimum 50% marks
  • Understanding of 10+2 level maths
  • Selection based on application and personal interview
    Please note: Internships and Training Experiences will not be considered in full time work-experience

Admission Criteria

Applications will be reviewed based on eligibility and subsequent shortlisting process as laid down by the Programme Coordinator.

Assessment and Certification


  • Each vertical (Data Science and Decision Science) will have equal weightage of 100% each.
  • 40% – Two examinations for each vertical i.e., Data Science and Decision Science
  • 40% – Capstone Project Implementation
  • 20% – Case studies, in-class assessments, and data/mathematical modelling problems

Attendance Criteria

Minimum 50% attendance in both, lectures and labs.


Candidates who successfully complete the programme and meet the attendance requirements will receive a Certificate of Completion from Continuing Education Programme (CEP), IIT Delhi.
*Only e-certificates will be issued by CEP IIT Delhi

Sample Certificate


Date and Fees

Programme Fee: ₹1,75,000 + 18% GST


• All fees should be submitted in the IITD CEP Account only, and the details will be shared post-selection.
• All invoicing and payment terms, infrastructure, delivery services, and other terms shall be governed as per the agreement/programme description sheet.

Instalment Schedule

Instalment IInstalment IIInstalment III  Instalment IV   
DateTo be paid within 7 days of offer rollout30th August, 202230th October, 202230th December, 2022
Amount (in ₹)*43,75043,75043,75043,750

* GST @18% will be charged extra in addition to the fee

Programme Timelines

Application Closure Date15th June, 2022
Interview Dates18th and 19th June, 2022
Offer Roll out Date23rd June, 2022
Programme Start Date9th July, 2022
Programme End Date25th June, 2023

Programme Content

Module I: Governance of Enterprise Analytics Systems

• Introduction to management of systems in enterprises and industries

• Types and Levels of Analytics Systems

• Understanding the evolution of SMAC era for enterprise systems

• Challenges of managing Artificial Intelligence and Machine Learning Projects

• Technology Alignment and Governance issues in Digital Transformation using Machine Learning.

Module II: Inferential Analytics

• Statistics 101 and Descriptive Analytics using MS Excel and SPSS/PSPP

• Data Visualisation

• Python programming for data management

• Python for descriptive, diagnostic and inferential statistics

• Prescriptive Analytics using MCDM/AHP

Module III: Predictive Analytics and Machine Learning

• Data Mining approaches for predictive analytics

• Supervised and Unsupervised learning

• Regression and Multivariate analysis using SPSS/PSPP

• Data Multidimensionality

• Data model building for Big Data applications

• Machine Learning using Artificial Neural Networks

• Deep learning

• Fuzzy set theory

• Machine learning using KNN, Kmeans, Random Forest, Support Vector Machine, etc.

Module IV: Cognitive Science and Big Data Analytics

• Big Data Applications

• Understanding Natural Language Processing Applications (e.g. Search Engines and Social Media)

• Web Analytics (Google)

• Machine Learning Applications and Chatbots

• Social Media Analytics

• Advanced Text Mining like sentiment analysis, topic modelling and text summarisation

• Advanced Network Science and Applications

Module V: Tools for Data Science

• Hands on exercises with Machine Learning for Supervised and Unsupervised learning

• User Interface driven Python applications (Orange)

• Python programming for big data and machine learning applications

• Text mining using Orange

Module I: Overview on Analytics for business decisions

• Understanding of main pillars of business decision analytics

• Introduction to Heuristics/Meta-Heuristics/Hyper-Heuristics/AI

• Application of decision-making models

Module II: Prescriptive Analytics

• Understanding Quantitative Data Analysis and Prescriptive Analytics

• Linear Programming (Single Objective) using Excel/LINGO

• Non-Linear Programming (Single Objective) using Excel / LINGO

• Linear Programming (Multiple Conflicting Objectives)

• Goal Programming using Excel / LINGO

• Applications of Linear Programming/Non Linear Programming in business

• Predictive Analytics using EXCEL/R

Module III: Business Simulation

• Introduction to basic statistics such as population and sample

• Measure of central tendency, dispersion and association

• Simulation modelling and analysis using Excel

• Application of simulation in business decisions

• Demand forecasting in business decisions

• R for predictive analytics (demand forecasting)

• Applying AI (Genetic Algorithm) in business decisions using Excel

Module IV: Descriptive and Qualitative Data Analytics

• Understanding Qualitative Data Analysis and Descriptive Analytics

• Introduction to Multi Criteria Decision Making

• Group Decision Making


• Hybridisation of MCDM such as IRP-AHP, ISM-AHP, AHP-TOPSIS

• Qualitative data analysis from Most Likely, Pessimistic and Optimistic Algorithms

• Aggregation of ranking variations using MILP in Excel/LINGO

Module V: Decision Science Tools and Case Studies

• Case study discussions from several domains of businesses viz. marketing, production, human resource, finance, & strategy using Excel/LINGO.

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Duration: 12 Months
Lectures: 10

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