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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery	Frequency Of Classes
English	Self Study, Virtual Classroom, Campus Based/Physical Classroom	Video and Text Based	Weekends

Course Overview

World Economic Forum predicted that by 2022, the world’s top emerging roles will be Data Analysts and Data Scientists. The Bureau of Labor Statistics predicts that by 2026, Data science requirements will lead to approximately 11.5 million jobs. There is no doubt these sectors will have significant growth in the future. The Advanced Programme in Computational Data Science course will provide professionals with the hands-on practical experience they need to make their mark in this growing industry.

TalentSprint has collaborated with the Indian Institute of Science, India’s No. 1 institute by NIRF, to create the Advanced Programme in Computational Data Science certification course. The IISc faculty will deliver the curriculum which meets the various target groups’ requirements, be it research scientists, R&D professionals, engineers, etc. It will enable them to grow into competent managers in hyper data-driven and technologically advanced society.

The Advanced Programme in Computational Data Science training by TalentSprint is a ten-month online course, including a three-day visit to the IISc campus in Bengaluru. The programme includes faculty-led interactive sessions, a convenient schedule for working professionals, multiple learning methods, and even mentorship for potential entrepreneurs who want to build a career through start-ups.

The Highlights

Ten Months Course
Online training
Learning on TalentSprint’s Pracademic Platform
Three Day IISc campus visit
Career Accelerator
Collaboration with Indian Institute of Science
Programme Certificate
Industry-leading faculty from IISc
Start-up Mentorship
Interactive Sessions
Convenient Schedule
Group Activities
Online Assessment and Quizzes
Experiments
Hackathons
Capstone projects
A Community of Deep-Tech experts
Personal project option available
360-degree learning
1:1 Mentoring
Data Stories
Self-paced learning

Programme Offerings

Ten Months Course
Online training
Three Day IISc campus visit
Collaboration with Indian Institute of Science
programme certificate
Top-notch faculty from IISc
Start-up Mentorship

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	IISc Bangalore

Advanced Programme in Computational Data Science online course has a course fee of Rs. 4,00,000 for domestic participants and $ 6,500 for international learners.
Besides, the expenses incurred during the campus visit will also be borne by the participants.
Upon selection, an application fee of Rs. 2,000 for domestic participants and $30 for international participants will be adjusted with the programme fee.
Domestic students can also opt for an 18-month long interest-free EMI option with a monthly payment of Rs. 19,667.

Advanced Programme in Computational Data Science fee structure

Course Name	Fee	Discounted Fee
Advanced Programme in Computational Data Science (Domestic Participants)	Rs. 4,00,000	Rs. 3,00,000
Advanced Programme in Computational Data Science (International Participants)	$ 6,000	$ 4,500

Eligibility Criteria

To apply for TalentSprint’s Advanced Programme in Computational Data Science online course, candidates must possess a four-year or an equivalent Masters/Bachelors Degree in Engineering, Management, or Science. Moreover, they should also have a minimum work experience of one year. Programming knowledge in coding is also a necessity to join this course.

What you will learn

Machine learningData science knowledgeBusiness analytics knowledge

The online certification Advanced Programme in Computational Data Science by TalentSprint provides immense fluency in core topics upon completion, such as:

Neural Network and their applications
Machine Learning
Data Engineering
The mathematics involved in Data science
Business Analytics and forecasting
Various practices in computational data science.

Who it is for

Data AnalystData ScientistBusiness Analyst

The Advanced Programme in Computational Data Science Certification Programme is beneficial for anyone who wants to pursue a data-driven profession, such as:

Business Analyst
Data Analyst
Data Engineers
Database Administrator
Data Scientist
Data Architect
Data and Analytics Manager
Business Intelligence Developer
Machine Learning Engineer

Admission Details

Step 1: If you have qualified the eligibility criteria, you can apply for the course by visiting https://iisc.talentsprint.com/cds/.

Step 2: Once you have downloaded the brochure (if required) and gone through the programme details, there is a dialogue box wherein you need to provide your contact information, details of your work experience, and your knowledge in coding. Then click on 'Apply Now.'

Step 3: Once the initial information is given, you will have to provide the required documents such as your identity proof, proof of education, work experience proof, etc.

Step 4: Once you have applied for the course, IISc will select the applicants based on their education, work experience, and motivation. If you are selected, you will have to pay the fee, selecting the most suitable option. Once the programme fee is paid, you can join the programme.

Application Details

The Application form for TalentSprint's Advanced Programme in Computational Data Science training is based on your education, work experience, and coding skills. The application form will need your contact details, your educational degree, and details of your work experience along with documental proof.

However, this alone will not grant you access to the programme. IISc will select participants for the programme strictly based on merit, that is the details given by the participants and their motivation. You can join the programme only after passing the selection process.

The Syllabus

Python Pandas
Seaborn
Data Munging Variables
Matrices
Functions
Derivativessklearn TF2
keras Google Data Studio

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 Differntiation
Fundamentals of Linear Algebra Spaces
Machine Learning Tools

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

Object-oriented programming (OOP):
- Inheritance
- Encapsulation
- Abstraction
- Polymorphism
- OOPs in C++ and Python
- 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:
- Just-In-Time (JIT) compiler for Python
- Thread and multiprocessing in python Dask for NumPy
- Pandas and Scikit-Learn
- 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)

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
Natural Language Processing (NLP)

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

Time Series Models: Time Series for Business and Financial Data
Market Basket Analysis
Portfolio Optimization
Customer Churn Analysis
Data Analytics in Infectious Disease Spread

Instructors

IISc Bangalore Frequently Asked Questions (FAQ's)

1: Is this Advanced Programme in Computational Data Science an Online Course?

Yes, Advanced Programme in Computational Data Science is an online course. However, this 10 months course also includes a 3-day visit to the Indian Institute of Science, Bengaluru.

2: How long is this training programme for?

The total programme duration is ten months.

3: Who are the programme instructors?

The programme educators are the expert and experienced faculty of the Indian Institute of Science.

4: Will i receive certificate ?

All candidates who participate in the Advanced Programme in Computational Data Science will receive a digital certificate from TalentSprint and IISc after they complete the entire programme curriculum.