Frequently Asked Questions

Most Frequently Asked Questions

The programme equips professionals with both academic, research insights coupled with practical knowledge and helps navigate the fast-evolving world of Data Science and allied areas. You will also earn an Executive Programme Certificate from IISc.
You will learn from the leading faculty of IISc and work on interesting use-cases and research projects.
Network and associate with current and future Data Science practitioners.

As an Institution of Eminence, IISc enjoys considerable autonomy. Certificate programs offered by the institution to working professionals, such as this program, are governed and fully approved by the IISc Centre for Continuing Education. The program complies with all the relevant regulations applicable.

COVID-19

You will need the following infrastructure to access our platform:

  1. Device: A Desktop/Laptop/Tablet/Smartphone with camera and mic.
  2. Internet: A regular broadband/wifi connection or a mobile 4G connection

Note: Proctored online assessments can be taken only on a Desktop/Laptop with a web camera and mic (not allowed on tablets/smartphones).

Groups can conveniently connect among themselves at an appointed time for group work, outside the online classes. This feature comes in handy during group activities and projects.
Students can also use the platform 24 x 7 to engage and learn from their peers using our interactive discussion forums available under each course of the programme.
Our platform also has the provision of group-specific discussion forums for offline discussion among the group members.

Our recorded videos have AI-generated Table of Content (TOC) to help easy and smart navigation within the videos. Students can click on the items under TOC to directly jump to the relevant section in a video. Video archives also have a Phrase Cloud of keywords/phrases used in the video. Students can click on a particular keyword/phrase to find yellow markers, indicating the points where the selected keyword/phrase was covered on the video timeline.

Selection Process

IISc conducts the selection process for the programme. Candidates will be selected based on the details of education, work experience and a statement of purpose submitted by you along with your application.

Candidates must have completed their graduation or post graduation with at least 50% marks and minimum of 1 year work experience. In addition, programming knowledge is required.

Programme Fee

Participants who are not holding an Indian Passport or are not residing in India will be considered as an International Participant.

Yes, the programme fee can be paid in interest-free instalments. Please reach out to your RM to know about the details of the schemes available.

The programme fee for PG Level Advanced Certification in Computational Data Science is ₹4,00,000 + GST. For EMI details, visit Fee Page.

No, the application fee is non-refundable.

No, the total programme fee is non-refundable.

Building deep-tech expertise is an absolute necessity for professionals in this fast-changing world that is constantly disrupted by technology.

Professionals have multiple options for funding.

  1. Sponsored by employer
  2. Self-funded

Based on our experience in enabling 3000 professionals who have participated in our executive programs, self-funding seemed to be the most preferred option with over 80% choosing this.

Three key reasons why professionals opt for it:

  1. Freedom: To opt for a program of their choice, at a time of their choice, with an institution of their choice and not be restrained by organisation’s policy.
  2. Flexibility: To pursue greater career opportunities well even beyond their current employer or to nurture their entrepreneurial ambitions.
  3. Funding: Access to flexible EMI schemes (Paying as low as Rs. 5,550 per lac per month).

We have also observed that the commitment levels were higher among self-funding participants.

Content

Module 0: Bridge Module
  • Python
  • Pandas, Seaborn, Data Munging
  • Variables, Matrices, Functions, Derivatives
  • sklearn
  • TF2, keras
  • Google Data Studio
  • Mini-Projects in Data Cleaning, Handing, Python
Module 1: Foundations of Data Science
  • Probabilistic Description of Events and Data: Probability Axioms, Random Variables, PDF, PMF, Conditional Probabilty, Independence, Expectation, Variance
  • Statistical Learning, Experiment Design, Confidence Interval and Hypothesis Testing
  • Bayesian Learning
  • Univariate and Multivariate Calculus, Norms of Vectors and Functions
  • Taylor's theorem and Automatic Differentiation
  • Fundamentals of Linear Algebra Spaces
  • Machine Learning Tools
  • Mini-Project in Foundations of Data Science (Bayesian Learning, Data Handling, Probability)
Module 2: Machine Learning
  • The ML Process: Problem Formulation to Solution
  • Linear Regression, Bias/Variance, Regularization, Stochastic Gradient Descent
  • Linear Classification: Logistic Regression, Linear SVM, Classification Metrics (Confusion Matrix)
  • Nonlinear SVM, Decision Tree
  • Ensemble Methods: Random Forest, Gradient Boosting
  • Unsupervised Learning: Clustering, Anomaly Detection
  • Mini-Projects in Machine Learning Algorithms in Multiple Domains (Rental Business, Healthcare, Banking, NLP, Customer Segmentation)
Module 3: MLOps at Scale
  • Object-oriented programming (OOP):
    1. Inheritance
    2. Encapsulation
    3. Abstraction
    4. Polymorphism
    5. OOPs in C++ and Python
    6. Applications of OOPs in Data Science
  • Parallel Architectures: Fundamentals of Parallel computer Memory Architecture, Parallel programming with MPI
  • Parallel Computing with Accelerators: Parallel programming with OpenMP, Accelerated computing using GPU
  • Scalable Computing with Python: Numba:
    1. Just-In-Time (JIT) compiler for Python
    2. Thread and multiprocessing in python Dask for NumPy
    3. Pandas and Scikit-Learn
    4. Parallel computing with TensorFlow
  • Introduction to MLOps, Foundations, MLOps for containers, Continuous Integration, Continuous Deployment for ML models, Monitoring and Feedback.
  • Mini-Projects in Computing for AI/ML (Writing ML packages from scratch, Using OpenMP/MPI)
Module 4: Neural Networks
  • Fundamentals of Deep Learning
  • Multi Layer Perceptron - Deep Neural Networks
  • Training a MLP - Backprop, Optimization Methods, Rules of Thumb
  • Convolutional Neural Network for Computer Vision
  • Recurrent Neural Network for Sequential Modeling
  • Dimensionality Reduction (PCA, SNE), Generative Models (GANs, VAE)
  • Reinforcement Learning
  • Mini-Projects in Neural Networks (Computer Vision, Image Analytics, Video Analytics, Financial Analytics, NLP, Reinforcement Learning Stock Trader)
Module 5: Data Engineering
  • Introduction to Big Data storage systems
  • Introduction to Big Data processing platforms
  • Deep Dive into Spark: RDD, Narrow, Wide Transformations
  • Deep Dive into Spark: Designing, implementing, evaluation and validating computational and analytics application using Spark
  • Fast Data Processing Platforms: Apache Storm
  • Mini-Projects in Data Engineering (Process Movie Data using NoSQL Cassandra, Complex Analytics on network intrusion using PySpark, End-to-end, PySpark Analytics on Tweets Data, ML on cloud)
Module 6: Business Analytics: Data Science in Practice
  • Time Series Models: Time Series for Business and Financial Data
  • Market Basket Analysis
  • Portfolio Optimization
  • Customer Churn Analysis
  • Data Analytics in Infectious Disease Spread
  • Mini-Projects in Business Analytics (Market Basket Analysis, Bitcoin Forecasting, Air Quality Forecasting, Customer Churn Analysis)
All modules have colab-based experiments with coding exercises (both full code along and no-hints version)

Schedule and Details

The online sessions will be held during the weekends, Saturdays & Sundays.

The programme will be delivered through faculty-led interactive live sessions on TalentSprint’s ipearl.ai

All reading material (pre/post session) will be shared regularly through the Online Learning Management System.

Programme will commence in September 2022.

The total duration of the programme is 12 months.

A certificate of successful completion is provided upon completion of all requirements of the programme. All examinations and evaluations related to the certification are carried out by IISc Bangalore.

The batch will consist of 100 participants.

All sessions are conducted by IISc Bangalore faculty. Industry experts may be invited for sharing their valuable experience.

About the Platform

Do not worry. In case you miss a session, you will be given access to view the recorded version of the session within a specified timeframe.

Yes, minimum 75% attendance is mandatory for the programme. To complete the programme you need to complete and submit all program submissions that may be due at your end.

  • An internet-connected device, Computer/Laptop/Tablet/Smartphone, is enough to access the platform.
  • Web-camera and Mic with necessary power backup will be needed for proctored online assessments.

All participants are required to execute, before the start of the program, an agreement that consists of the standard Program Terms and Conditions. It has the following components:

  • Part A: Etiquette and Platform Rights
    • Classroom Etiquette & General Policy Guidelines
    • Tools and Platforms in Use
    • Tools and Platforms: Terms of Use
  • Part B: Honor Code
  • Part C: Certification
  • Part D: Program Fee, Refund and Termination Policy

Others

IISc (Indian Institute of Science) is India's foremost academic institution for the pursuit of excellence in higher education & research. It offers world-class education in science, engineering, design, and management. IISc became a deemed university in 1958. It is one of the first six institutes to be awarded the Institute of Eminence status. The alumni of this Institute hold significant academic and industry positions around the globe. For more information visit iisc.ac.in

  •  10 Years of Excellence
  •  200K Empowered Professionals
  •  95% Completion Rate
  •  85 Net Promoter Score
  • ‘Winner’ - Indian Achievers Award 2022 

Established in 2010, TalentSprint is a part of the NSE group and a global edtech company that brings transformational high-end and deep-tech learning programs to young and experienced professionals. The company’s digital learning platform ipearl.ai offers a hybrid onsite/online experience to seekers of deep technology expertise. TalentSprint partners with top academic institutions and global corporations to create and deliver world-class programs, certifications, and outcomes. Its programs have consistently seen a high engagement rate and customer delight. It is a leading Innovation Partner for the National Skill Development Corporation, an arm of the Ministry of Skill Development and Entrepreneurship, Government of India. A recipient of various prestigious accolades, TalentSprint was recently honoured with the Indian Achievers Award 2022, constituted by the Indian Achievers Forum for its excellence in building deeptech talent in India. For more information about TalentSprint, visit our website.