Applied AI & ML
for Business & Decision Analysis by
IIT Kanpur and SAS

Learn from the world's
finest experts in academia and industry presenting

A Certified data-driven decision maker
12-month hybrid program


About the Program

A well-crafted course to empower your career.
Presenting, Applied Artificial Intelligence & Machine Learning for Business & Decision Analysis - A Joint Certification Program by IIT Kanpur and SAS.

Artificial Intelligence (AI) and Machine Learning (ML) now predominates various industries, sectors, and businesses for developing effective data-driven decisions and insightful business strategies. AI has accelerated the adoption of advanced analytics. With an ever-growing demand for trained professionals, for numerous job profiles involving analysts and technologists, AI and ML are now must-have skills in their repertoire. If you want to make an entry in the field or start a career or want to add value to your current job role and organization, Applied Artificial Intelligence & Machine Learning (AIML) for Business & Decision Analysis - A Joint Certification Program by IIT Kanpur and SAS Institute, will provide you with the necessary knowledge and skills.

The program is designed to provide technical and application-oriented training to participant in the field of Artificial Intelligence, Machine Learning, Business and Decision Making. This course provides, a blended learning mode, case studies, projects and practice exams. You will be prepared for the world of Artificial Intelligence and Machine Learning with hands-on problem-solving-based learning and real-world case studies from well know academicians as well as industry practitioners.

Benefits of the Program

  1. A Joint Certificate: Earn a joint certificate from IIT Kanpur and SAS. A 400+ hours program spaced into 1 year with a blend of instructor led training, lab practice, & e-learning.
  2. Capstone Project: A detailed hands-on project to every participant will be provided by SAS. The project addresses key requirements of data analysis in an industry setting across various business domains.
  3. Instructors: The program is delivered through live interactive class mode by the best instructors (professors from IIT Kanpur and industry expert from SAS). All our instructors are combination of PhD in their subjects or active industry experts.
  4. Learning Management System: Participants have access to >190 hours of elearning and recorded sessions of 215 hours of live instructor led training, video tutorials and 24X7 access to virtual lab for one year period.
  5. Official Course Material: The program shall be supported by official course materials in soft copy format.

Placement Opportunities

The joint program, apart from enhancing the repertoire of skills amongst the participants, will also give them a definitive edge in the ever-growing job market in Data Analytics, Machine Learning and Artificial Intelligence. With an optimal blend of training comprising of rich academic knowledge and relevant industry case studies and discussions, imparted by renowned faculty members from IIT Kanpur and experts from SAS along with professional advice, candidates will find a bouquet of very lucrative and relevant jobs in their areas of interests.

Admission Process

Admission Eligibility criterion

Bachelor's or Master's degree (preferably in the area of business, science, technology, engineering, mathematics, statistics and economics), with at least one semester of college-level statistics or mathematics.

Selection Criterion/Selection Process

Skill Assessment: Interested candidates will be required to undertake a skill assessment test.

Curriculum Highlights

The course involves a logical flow of learning, delivered through a blend of IIT Kanpur and SAS faculty enabling a learning path that balances theory and practice.

Module 1 (105 Hours)


Data Prepration, Basic Statistics and Visual Analytics

Module 1: Section A
70 hours

Advance Statistics and Data Mining

Module 1: Section B
35 hours

Module 2 (110 Hours)

Machine Learning & Deep Learning

Module-2: Section A
40 hours

Forecasting and Optimization Analytics

Module-2: Section B
40 hours

Natural Langauage Processing

Module-2: Section C
10 hours

Multi criterion Decison Making

Supply Chain Management

Module-2: Section D
20 hours

Courses Overview
Sr.No. Course Name Skills Imparted
Module 1- Section A Foundation: Data Preparation, Basic Statistics and Visual Analytics
1 Self-Service Data Preparation
    Capabilities include bringing data in from a variety of sources, preparing and cleansing data to be fit for purpose, analyzing it for better understanding and governance, and sharing it with others to promote collaboration and operational use.
2 Probability and Statistics: An Introduction
  • Equips participants with fundamental and advanced tools of data preprocessing and fitting.
  • Adequately trains participants in different inference techniques and use of different statistical tables for data analysis.
3 Visual Analytics
  • Apply powerful data visualization techniques to data of any size and create compelling stories and dashboards for various stakeholders of an organization.
Module 1-Section B - Advanced Statistics and Data Mining
4 Multivariate Techniques: MLR, FA, DA
  • Gears participants to masters advanced methods in prediction.
  • Trains students in different categorization and discriminant techniques.
5 Forecasting, Time Series and Data Mining
  • Helps participants master fundamentals of forecasting and time series for better prediction.
  • Equips students to analyze data when multiple variables may be needed for data fitting and data analysis.
Module 2: Section A - Machine Learning & Deep Learning
6 Machine Learning
  • Get familiar with the fundamentals of Machine Learning. Learn about the overall ML set-up and how it could be applied to a problem at hand. Learn how to use ML libraries and implement ML models and tune them for solving a problem.
7 Deep Learning
  • Learn about deep learning, different neural architectures and how to implement different neural network architectures using PyTorch library
  • Learn how to train a neural network
8 Supervised Machine Learning Pipelines
  • Learn the ability to apply, validate and deploy basic and advanced machine learning techniques using a customized or predefined pipeline based template approach.
Module 2: Section B - Forecasting and Optimization Analytics
9 Forecasting Using Model Studio
  • Learn to create pipelines to generate forecasts and select champion pipelines – and ability to incorporate large-scale forecasting practices. These include the creation of data hierarchies, forecast reconciliation, overrides and forecast model selection best practices.
10 Operations Research: Basics and Advanced Topics
  • Helps participants appreciate the fundamentals of optimization techniques with an emphasis on duality, shadow prices, marginal costs, etc.
  • Aids students to appreciate the interesting application areas of NP, MILP in data sciences and data analytics.
11 Optimization Concepts for Data Science and Artificial Intelligence
  • Learn to apply linear, nonlinear and mixed-integer linear optimization concepts. Ability to formulate optimization problems and make formulations efficient by using index sets and arrays.
Module 2: Section C -Natural Language Processing
12 Natural Language Processing (NLP)
  • Learn about the fundamentals of Natural Language Processing, different types of NLP models including structure prediction models, deep learning-based models and transformer-based models. Learn how to process text using the NLP pipeline.
Module 2: Section D -Multi criterion Decision Making, Supply Chain Management
13 Fundamental of Multi-Criteria Decision Making
  • Train participants to learn fundamental ideas of utility theory, stochastic dominance and Pareto optimality, which forms the bedrock for multi-criteria decision making
  • Help participants grasp the use of parametric and non-parametric MCDM techniques in decisions where both attributes and quantitative variables are important.
14 Supply Chain Management (SCM)
  • Provides participants with fundamentals of operations and supply chain management for better performance of businesses in the uncertain world.
  • Helps the participants to understand demand and supply management, supply chainnetwork design, production planning, inventory management, contracts and sustainability.

Weekend Classes


IIT Kanpur

Prof. Raghu Nandan Sengupta
Exp: 18 Years
PhD, Operations Management
Prof. Vipin B
Exp: 4 Years
PhD, Operations and Supply Chain Management
Prof. Amit Mitra
Exp: 25 Years
PhD in Statistics
Prof. Subhajit Dutta
Exp: 8 Years
PhD in Statistics
Prof. Ashutosh Modi
Exp: 10 Years
PhD, Computer Science


Dr. Manoj Singh
Exp: 21 Years
M.Sc. in Statistics
John Coutinho
Exp: 22 Years
Diploma in Computer Software
Dr. Sharad Saxena
Exp: 14 Years
PhD, Statistics
Dr. Sunil Bhardwaj
Exp: 19 Years
PhD, Engineering
Akshay Dixit
Exp: 14 Years
Master's in Economics
Mahesh Dubey
Exp: 21 Years
Master's in Computer Application
How to Apply

01) Please be ready with the following:

  • Amount paid via NEFT
  • Bank details from where NEFT payment has been made
  • NEFT payment ID
  • NEFT payment date
  • Passport size photograph (.jpg format)
  • ID/bona fide letter of institute/university/organization

02) NEFT payment details

Relevant Payment Details
Bank A/c 00398640000113
Bank Branch and Address 9/2 Kalpataru Gardens, Boat Club Road, Pune-411001
Branch Code 39
IFS Code HDFC0000039
MICR Code 411240004

03) Installment Dates

Round of acceptance/notification Deadline Fees (GST included)
1st installment (after payment/form is received) 15-Mar-2022 INR 249,999.5
2nd installment (after payment/form is received) 15-Apr-2022 INR 249,999.5