L25005

Programme on Data Science & AI (DSAI) – Batch 3

Programme Dates Last Date to Apply Programme Fees

Venue

Start Date : 21 Feb 2025
End Date : 17 Jan 2026
15 Nov 2024

 Rs. 7,25,000/-
(Non-residential, Excluding GST)

IIMB Campus and Hybrid

 

Programme on Data Science & AI

Apply Now & Download Brochure

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Mode
Hybrid
Starting In
Jan-Mar
Level
Mid- Senior/Career
Duration
Long Duration
International Travel
No
Alumni Status
Yes

Artificial Intelligence, Machine Learning, Big Data and Natural Language Processing form the pillars of the emerging discipline of data science. Managers who lead data science teams are required to possess a sound understanding of the underlying technologies. More importantly, they must also be able to communicate the strategic benefits of their efforts to stakeholders. The field of information systems provides the appropriate frameworks to build the business case for data science initiatives, and to analyse the shifts brought about by its application.

The Programme on Data Science & AI from IIM Bangalore will empower managers and other professionals to draw from the frameworks of data science and information systems, and guide their organizations along a forward-looking trajectory.

Programme Objective

This certificate series in data science exposes the participants to a large set of frameworks and technologies, and prepare them for data-intensive roles in retail, healthcare, marketing, supply chain management, finance, insurance and other industry sectors. The modules in the programme are suitable for managers who wish to develop a programming-oriented appreciation for their individual domains. Projects drawn from their own workplace settings will help them with the assimilation of the topics. By attending and completing the requirements of the Programme on DS & AI, the participant will learn how to:

  • Develop a business perspective of the dynamic discipline of data science
  • Gain a foundational understanding of the four pillars of data science: AI, ML, Big Data and NLP
  • Solve computational problems using a personal laptop as well as a cluster
  • Construct a business proposal for a data science initiative
  • Identify ways in which organizations can inculcate a culture of data driven decision making

Key Benefits:

  • Develop a business perspective of the dynamic discipline of data science
  • Gain a foundational understanding of machine learning, big data and AI
  • Solve computational problems using a personal laptop as well as a cluster
  • Construct a business proposal for a data science initiative
  • Identify ways in which organizations can inculcate data-driven decisions
  • IIMB EEP Alumni Membership after successful completion of the programme

Programme Directors

Shankar Venkatagiri

Prof Shankar Venkatagiri has been a faculty in the Information Systems area at IIM Bangalore since 2002. Prior to joining IIMB, Prof Shankar worked in the IT industry around Cambridge, USA.  As the IT Chair during the pandemic, he helped repurpose IIMB classrooms to reach students everywhere. Prof Shankar is interested in data science, healthcare, and agile methods. He teaches courses in big data analytics and information systems management. He currently directs the DSAI program, which focuses on data science. He has created and directed the GMHE program, which is aimed at healthcare professionals.

Prof Shankar holds a doctorate in mathematics and a masters in computer science from Georgia Tech. He is also an alumnus of IIT Kharagpur and the University of Southern California.

Prof Soudeep Deb received his bachelor’s and master’s degree in Statistics from Indian Statistical Institute, Kolkata. Then, he completed his Ph.D. in Statistics from the University of Chicago. His primary field of work is related to forecasting, time series data, spatio-temporal modeling, inference for random processes, nonparametric methods, and their applications in various fields. He is also interested in sports analytics, especially problems related to soccer. Outside work, Soudeep takes keen interest in photography and blogging.

Highlights From The Previous Batch

Programme Plan

Participants Organisations

Participants Demographics

Target Audience

  • Participants should have a Bachelors degree (in any stream) with mathematics as one of the core subjects.
  • At least 3 years of work experience is preferred. Given that programming is critical to developing a working understanding of data science, we prefer participants with strong coding skills, who are willing to embrace a variety of languages and technology platforms.

Programme Content

Module Zero: Foundations (7 weeks)
 
A strong knowledge of statistics is considered foundational to Data Science. Completing Module 0 is a prerequisite to proceed to any of the other modules. It is designed to strengthen the participant’s foundations in statistics, linear algebra and programming. Participants will first be brought up to speed on Python programming with the help of extensive tutorials.
To kick off the programme, we invite the participants to IIMB’s digital classroom for 3 days, followed by two Massive Open Online Courses (MOOCs) for 3 weeks and the last 3 days for case-based learning.
  • Python tutorial
  • Descriptive statistics – variables and their visualisation, probability
  • Random variables, binomial, Poisson and normal distributions
  • Sampling, confidence intervals and parameter estimation
  • Statistics for Business 1 – spreadsheet-driven elaboration of descriptive     statistics and probability; decision-making with Bayesian logic
  • Statistics for Business 2 – R programming with a business use case, random variables, binomial, Poisson and normal distributions
  • Inferential statistics – hypothesis testing framework, ANOVA, chi-squared tests
  • Forecasting with time series
  • Linear algebra and geometry
The final stage is an online assessment, covering the two MOOC courses and other topics of Module Zero. Depending on the outcome, suggestions will be made regarding areas of improvement.
 
Module One: Machine Learning (9 weeks)
  • The machine learning landscape
  • Machine learning in practice
  • Supervised models: Regression and classification
  • Decision trees and random forests
  • Support vector machines
  • Dimension reduction and PCA
  • Unsupervised models: clustering
  • Machine learning at scale
  • Cases: Mission Hospital (IIMB), Lead Generation at Eureka Forbes, Commonwealth Bank
  • Industry Talks: Entrepreneurs who have built ML firms
Module Two: Big Data (9 weeks)
  • Tectonic movements in the landscape of data
  • Volume: Structured data, Big Query, cloud computing
  • The MapReduce construct, Hadoop
  • Spark with Scala and Python – business applications
  • Variety: Network analysis
  • Velocity: Streaming applications
  • Operational excellence, supply chain management
  • The IoT movement, Industry 4.0
  • Veracity: The case of Cambridge Analytica
  • Cases: Customer Analytics at BigBasket (IIMB), 1920 Evil Returns (IIMB), Fiesta Gifts
  • Industry Talks: Speakers from Amazon, Google & Microsoft, Target, etc.
  • Industry Talks: Big data in Government, Healthcare, Marketing
Module Three: AI & Deep Learning (9 weeks)
  • The AI Landscape
  • Biological origins
  • Historical perspective
  • Optimisation and search
  • Single and multi-layer networks
  • The TensorFlow platform
  • CNNs and RNNs
  • Natural language processing
  • Generative Adversarial Networks
  • Reinforcement learning
  • Genetic algorithms, ant colony optimisation
  • Artificial life systems
  • The Future of AI
  • Cases: Tailored Brands, Intenseye, Distinct Software, Picking the Best Path, Edge Networks (IIMB)
  • Industry Talk: Speakers from AIndra, Google and Microsoft
 Module Four: Natural Processing Language (7 weeks)
  • The NLP Landscape
  • NLTK and spaCy libraries
  • Language models
  • Sentence Classification
  • Word & document embedding
  • Information extraction
  • Chatbots
  • Social Media
  • Applications to E-Commerce & Retail
  • Applications to Healthcare, Finance & Law
  • Attention, transformers, BERT
  • NLP at scale with Spark
  • Industry speakers from Healthcare
  • Cases: Cogent Labs
Project (3 weeks)
Upon successful completion of all 4 modules, the participants can work on a live project. Please see the brochure for more details.

Programme Schedule & Payment Schedule

Programme Schedule

NoteThe programme will be delivered in Hybrid mode with the choice of mode of attendance to be decided by the participant.
 
Payment Schedule
 

How To Apply for the Programme


You are required to upload your Resume and Graduation Certificate in the online application portal.

For any queries related to the programme, please contact Ms. Mohsina Jabeen on Phone no. +91-80-28993563; +91-78999 91516 or Email ID at mohsina.eep@iimb.ac.in

Certificate Sample

A part time programme certificate of completion will be awarded by IIMB to participants upon successful completion of the programme and satisfying programme requirements.

Sample Certificate:

Note: Certificate image is for reference to potential participants only and may change at the discretion of Executive Education Programmes Office

Contact Us

Ms. Aditi Chaturvedi
Landline No.: +91-80-26993380
Mobile No. +91-89512 81611
Email: aditi.chaturvedi@iimb.ac.in

Award of Certificate

A part time programme certificate of completion will be awarded by IIMB to participants upon successful completion of the programme and satisfying programme requirements.

IIMB EEP Alumni Membership

The participants become IIMB EEP alumni on successful completion of the programme and thereby gain access to the alumni network across various industry sectors.

Testimonials

  • AI (including ML) and Big Data are vast subjects. This course ensured a strong foundation specially in statistics, enabled a good grasp of various techniques and provided sufficient knowhow to explore further in each area. Even though advanced modules are technical in nature and require hands on coding, the case studies discussed provided valuable insights into real challenges faced by businesses. Personally, it felt great to be back in a classroom environment after many years and the experience elevated more so being taught by distinguished faculty from IIMB. Guest lectures were conducted by experts from various business domains and provided in-depth insight on how technology was implemented to solve problems. I am eternally grateful to IIMB for hybrid structure of the course which allowed me to participate from a different continent and time zone but allowed gave me the opportunity to visit the campus.

    Amit Rao
    Technical Architect, E-Automation Ltd, Manchester, United Kingdom
  • IIMB’s MPDS is a well-structured course for anyone looking to have a solid foundation in Data Science. I experimented with few MOOCs on Data Science an year before joining this course but struggled with maintaining rigor required for this field. Also, for many of the concepts, I felt the need to have a mentor to answer my queries. This program was a solution to my learning challenges. It provided a solid understanding of different pillars and tools of data science starting from statistics to AI to Big Data. Opportunity to ask queries in class, group discussions with a diverse cohort while working on carefully curated assignments helped in cementing the concepts well. There was a balanced focus on the mathematics and logic of ML algorithms along with applications that helped in building a holistic understating. Guest lectures from experts gave an industry perspective. I will strongly recommend this program to anyone looking to build a solid foundation in Data Science.

    Chetna Parihar
    Senior Delivery Manager, Sun Life Financial, Jalandhar
  • I found this program extremely useful in terms of skill and knowledge gaining, the program went right from Basics of statistics, Mathematics from R, Python, Machine learning, Big data, and AI. The course curriculum helped me understand the concepts in depth which , otherwise, would have been very difficult to cope up. Special thanks to Prof Shankar and Prof Rahul for extending support throughout the program.

    Venkat Manjunath.B.S
    Assistant Manager-Ops, Big basket, Bangalore
  • At my day job I got an opportunity to work on a project based on AI Tech, which meant that I had to upskill in AI. I applied at multiple institutes, but IIMB was my first choice, i.e. if IIMB chose me; I had always aspired to study here. The IIMB journey phenomenal which started back in September 2022. IIMB taught us to never doubt our capabilities. I want to thank the course Directors Professor Shankar Venkatagiri & Professor Rahul De for their unwavering support throughout the course. By the end of the course, we got an opportunity to work with an NGO on an NLP based project which deals with Social Emotional Learning of Students. We were able to make a positive impact on the Indian Education System. The content of this course is carefully curated to meet the global standards. It dives deep into the mathematical fundamentals of the subject, which I think is the most important aspect in AI.

    While at work, my activities are now focused only on Data & AI driven projects, which are familiar territories now. I have gained a perspective towards data driven decision making & IIMB has given me a lot more confidence in tackling business challenges through data. After this course, my approach to problem solving is a lot more practical, wholistic and mature.

    Nishant Kumar
    Lead Software Developer - JLL Technologies
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