Graduate with a Degree from
University of London
Graduate Diploma in Data Science
Master data science and business knowledge with the Graduate Diploma in Data Science.
Academic Direction by
London School of Economics
Duration
1 Year
Program Highlights
Study an LSE Curriculum: Study the same curriculum that’s taught at LSE. Additionally, LSE faculty develops study material & sets examination papers for ISBF students.
Carve your Career Ahead: The GD serves as a perfect stepping stone for 1-year Master’s programmes at top universities & is also accepted as the 16th year of education by universities in USA & Canada
Placements in India & Abroad: Students have been placed with top companies like EY, KPMG, Accenture, Moody’s Analytics & more.
Hands-on Learning: Participate in capstone projects & attend skill workshops covering technical tools (Excel, Stata, R, Python).
International Work Permit: Get a 1-year international work placement in London and New York with leading investment banks.
Teaching Plan
The academic session for this programme will start with two weeks of Foundation Courses in Applied Mathematics, Logic and Statistics.
Highlights
Study a curriculum designed by LSE faculty
Get a 1-year work permit in London or New York
Get a chance to attend summer school at LSE
Attend guest lectures hosted by industry professionals
Machine Learning
1
Sampling and resampling
2
Classification
3
Nonlinear models – Gaussian process regression
4
Linear regression – high dimensions and regularisation
5
Bayesian inference
6
Support Vector Machines
7
Tree-based methods and Random Forests
8
Unsupervised learning – Principal Components Analysis and Clustering
Software: R. Python offered as optional learning
Business Analytics, Applied Modelling and Prediction
1
Decision-making under uncertainty
2
Univariate data visualisation
3
Probability distributions in business applications
4
Decision trees
5
Sampling and sampling distributions
6
Hypothesis testing
7
Regression analysis
8
Time series analysis and forecasting
9
Optimisation methods
10
Monte Carlo simulation models
Software- MS Excel, Tableau
Information Systems Management
1
Role of technology in organisations
2
IT and business strategies
3
Project management
4
Outsourcing
5
ICT governance
6
E-business
7
Enterprise Resource Planning (ERP) systems
8
Managing Business Intelligence and Big Data
9
Knowledge management
Elements of Econometrics
1
Classical regression model
2
Gauss-Markov conditions
3
Specification and transformation of variables
4
Heteroscedasticity
5
Simultaneous equations estimation
6
Binary choice models
7
Maximum likelihood estimation
8
Panel data
9
Time series regression
Software- STATA
Learn Business by Running Business
Apply your learnings to solve a multi-disciplinary problem and present your work.
Capstone Projects
Run an E-Commerce business, build a website & compete for
revenue to learn more about:
Skill-building Workshops
Learn tools like Excel, Stata, R and Python hands-on and get exposure to areas like policy-making, investing and entrepreneurship.
Research Cell
Students are trained in research skills and methodology, and also given an opportunity to work on research projects with faculty members.
Virtual Learning Environment (VLE)
Curated and updated continuously by LSE, this is a rich virtual repository of learning resources, course updates, discussion forums and also access to the online UOL Library.
Career Path after ISBF
After the programme, you can choose to study further or get work experience in your domain of choice
Postgraduation
With a well-rounded degree, you will have an edge over the others when applying for Masters’, internationally. You can pursue courses in the following domains:
Student Life at ISBF
Bombay Stock Exchange Bootcamp
Every year 2 students get an opportunity to attend a 2-day, on-site, specially curated Bootcamp at BSE in Mumbai.
Student Clubs & Societies
Become a part of student-run clubs & host activities across media, music, dance & more
Convocation in London
Being students of University of London, all ISBF students are invited to attend the UOL convocation in London.
Admission Process
Scholarships
The Aryabhatta Scholarship
Eligibility: Candidates with exceptional performance in iGDET & PI & financial need is assessed through last two year’s ITR.
Scholarship: 25% of the tuition fee
The Chanakaya Scholarship
Eligibility: Candidates with exceptional academic performance in their first year & who also have 95%+ in ICSE/CBSE Board exams or 40+ in the International Baccalaureate.
Scholarship: 20% of the tuition fee
The Vivekanand Scholarship
Eligibility: Candidates with exceptional academic performance in their first year & who also have at least 90% but <94.99% in ICSE/CBSE Board exams or min. 35 but <40 points in the International Baccalaureate.
Scholarship: 15% of the tuition fee
Is this programme right for me?
Talk to ISBF’s admissions’ team to understand if you are a good fit for this programme.
Frequently Asked Questions
What is the eligibility criteria to apply for the programme?
To pursue this programme, students must have completed an undergraduate degree, preferably in a quantitative discipline, and have had Mathematics in school up to Class XII. There is no other stream or subject-related eligibility criteria.
What is the admission process for the programme?
Admission to ISBF is a 3-step process. The first step is to fill out the application form with all the required details. Next, you have to appear for the ISBF Entrance Test (iGDET). Finally, the shortlisted students will have to appear for a Personal Interview.
Is it necessary to write the iGDET test?
Exemption for the iGDET can be on the basis of:
If a candidate has -
- 650 or above in GMAT, or
- 90%ile+ in CAT, or
- 300 or above in GRE
What all foundation courses are included in this programme?
Foundation courses such as R, Python and Statistics are included in the programme.