Overview
Enrolling in the Computational Data Science (Mathematics) B.Sc. programme at Indiana University Indianapolis presents an exceptional opportunity for students to engage with cutting-edge data science methodologies. This degree is structured to equip learners with essential skills in both mathematics and computational techniques, ensuring they are well-prepared for the evolving demands of the data-driven world.
Why Computational Data Science (Mathematics) at Indiana University Indianapolis?Indiana University Indianapolis is renowned for its commitment to academic excellence and innovative research. The university boasts a strong reputation for its data science programmes, supported by state-of-the-art facilities and a collaborative environment. Students benefit from partnerships with industry leaders, providing them with insights and opportunities that enhance their learning experience.
Tuition Fee BreakdownThe tuition fees for the Computational Data Science (Mathematics) B.Sc. programme are as follows:
- International Students: USD 1,131 per credit
- National Students: USD 1,131 per credit
- Local Students: USD 400 per credit
Visit the Fees and Funding section for a breakdown in your local currency.
SyllabusThe curriculum for the Computational Data Science (Mathematics) B.Sc. programme is meticulously designed to cover a range of essential topics, including:
- Mathematical Foundations of Data Science
- Statistical Methods for Data Analysis
- Computational Techniques and Algorithms
- Data Visualisation and Interpretation
- Machine Learning Principles
- Big Data Technologies
- Ethics in Data Science
This structured approach ensures that students gain a comprehensive understanding of both theoretical and practical aspects of data science, preparing them for various career paths in the industry.
Careers with Computational Data Science (Mathematics)Graduates of the Computational Data Science (Mathematics) programme are well-equipped to pursue diverse career opportunities. Alumni have successfully secured positions in various sectors, including technology, finance, healthcare, and research. Job roles often include data analyst, data scientist, and computational mathematician, where they apply their expertise to solve complex data challenges and drive decision-making processes.
Programme Structure
Courses included:
- Machine Learning
- Computational Linguistics
- Cyber Security
- Data Information
- Calculus
- Applied Mathematics
- Information Science
- Data Analytics
Key information
Duration
- Full-time
- 24 months
Start dates & application deadlines
- StartingApplication deadline not specified.
- StartingApplication deadline not specified.
Language
Prepare for Your English Test
AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Credits
Delivered
Campus Location
- Indianapolis, United States
Disciplines
Computer Sciences Data Science & Big Data Computational Mathematics View 461 other Masters in Data Science & Big Data in United StatesWhat students do after studying
Academic requirements
English requirements
Prepare for Your English Test
AI-powered IELTS feedback. Clear, actionable, and tailored to boost your writing & speaking score. No credit card or upfront payment required.
- Trusted by 300k learners
- 98 accuracy using real exam data
- 4.9/5 student rating
Other requirements
General requirements
- The applicant to the graduate program must have a four-year bachelor’s degree or equivalent.
- The applicant’s record should demonstrate strong individual accomplishments, include recommendations from independent references and exhibit outstanding achievement as indicated by the grade point average for each degree over his or her entire academic record. An applicant is expected to have a GPA of at least a 3.0 on a scale of 4.0.
- GRE required
All applicants should have a background in the following core areas of computer science:
- software development experience in a high-level language
- data structures and algorithms
- systems (operating systems, compilers, and programming languages)
- theory (discrete math and theory of computation)
- hardware (computer architecture)
In addition, applicants should have a strong background in mathematics, including calculus, linear algebra, and numerical computations
Tuition Fees
-
International Applies to you
Applies to youNon-residents18015 USD / year≈ 18015 USD / year - Out-of-State18015 USD / year≈ 18015 USD / year
-
Domestic
Applies to youIn-State6450 USD / year≈ 6450 USD / year
Living costs
Indianapolis
The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.
Financing
Interested in financing your studies? Find a student loan that works for you.
Get the funding you need to study in the U.S. or Canada - with a process that's fast, simple, and built for international students.
- Flexible loans from US$2,001 to US$100,000
- Fixed interest rates -- no inflation surprises
- No upfront fees or prepayment penalties
- Accepted at 500+ universities across the U.S. & Canada
- 100% online application -- instant conditional offer
- Free visa & career support through our Path2Success program
Funding
In order for us to give you accurate scholarship information, we ask that you please confirm a few details and create an account with us.
Scholarships Information
Below you will find Master's scholarship opportunities for Computational Data Science (Mathematics).
Available Scholarships
You are eligible to apply for these scholarships but a selection process will still be applied by the provider.
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility
Read more about eligibility