Data Science

The Indiana University Bloomington Bachelor of Science in Data Science program offers students a comprehensive education in the rapidly evolving field of data analysis, computation, and statistical modeling. Designed to equip graduates with the skills necessary to analyze large datasets, develop predictive models, and communicate insights effectively, this program integrates coursework from computer science, mathematics, and statistics. Students will gain hands-on experience with industry-standard tools and programming languages such as Python, R, and SQL, preparing them for careers in data analysis, data engineering, machine learning, and artificial intelligence. The curriculum emphasizes both theoretical foundations and practical applications, enabling students to solve complex real-world problems across diverse sectors including healthcare, finance, technology, government, and more. In addition to technical skills, the program fosters critical thinking, problem-solving, and ethical considerations related to data privacy and security. Students have opportunities for internships, research projects, and collaboration with industry partners, providing valuable professional experience before graduation. The program also encourages interdisciplinary learning, allowing students to tailor their education according to their career interests through specialized electives and minors. Graduates of the Data Science program at Indiana University Bloomington are well-prepared to pursue advanced degrees or enter the workforce as skilled data scientists, analysts, or data engineers. With a strong foundation in quantitative reasoning and computational methods, graduates are equipped to interpret data, develop innovative solutions, and contribute meaningfully to data-driven decision-making processes across various fields and organizations. The program's faculty are recognized experts in data science and related disciplines, committed to providing a rigorous and engaging educational experience that prepares students for success in the dynamic world of data analytics.

Core Courses (12 cr.)

Data Analysis and Statistics (3 cr.)

Complete one course from the following:

• CSCI-B 503 Algorithms Design and Analysis
• CSCI-B 553 Neural and Genetic Approaches to Artificial Intelligence
• CSCI-B 565 Data Mining
• CSCI-B 652 Computer Models of Symbolic Learning
• CSCI-B 659 Topic: Information Theory and Inference
• INFO-I 573 Programming for Chemical & Life Science Informatics
• INFO-I 590 Topic: Visual Analytics
• INFO-I 590 Topic: Relational Probablisitic Models
• ILS-Z 534 Search
• ILS-Z 604 Topic: Big Data Analysis for Web and Text
• ILS-Z 637 Information Visualization - offered online
• STAT-S 520 Introduction to Statistics
• STAT - any course that is 600 level and above

Data Lifecycle (3 cr.)

Complete one course from the following:

• CSCI-B 551 Elements of Artificial Intelligence
• CSCI-B 555 Machine Learning
• INFO-I 535 Management, Access, and Use of Big and Complex Data - offered online
• INFO-I 590 Topic: Applied Machine Learning
• INFO-I 590 Topic: Complex Systerms
• ILS-Z 604 Topic: Scholarly Communication
• ILS-Z 604 Topic: Data Curation
• ILS-Z 636 Data Semantics - offered online
• ILS-Z 652 Digital Libraries

Data Management and Infrastructure (3 cr.)

Complete one course from the following:

• CSCI-B 534 Distributed Systems
• CSCI-B 552 Knowledge Based Artificial Intelligence
• CSCI-B 561 Advanced Database Concepts
• CSCI-B 649 Topic: Cloud Computing - offered online
• CSCI-B 649 Topic: Advanced Topics in Privacy
• CSCI-B 649 Topic: Cloud Computing for Data Intensive Sciences - offered online
• CSCI-B 661 Database Theory and Systems
• CSCI-B 662 Database Systems and Internal Design
• CSCI-B 669 Topic: Scientific Data Management and Preservation
• CSCI-P 536 Advanced Operating Systems
• CSCI-P 538 Computer Networks
• INFO-I 520 Security for Networked Systems
• INFO-I 524 Big Data Software and Projects - offered online
• INFO-I 525 Organizational Informatics and Economics Security
• INFO-I 590 Topic: Complex Networks and their Applications
• ILS-Z 511 Database Design

Domain/Application Area (3 cr.)

Select from one of these areas: business analytics, science analytics, web science, social data analytics, and health analytics.

• CSCI-B 656 Web Mining
• CSCI-B 679 Topic: High Performance Computing
• INFO-I 519 Introduction to Bioinformatics
• INFO-I 523 Big Data Applications and Analytics - offered online
• INFO-I 529 Machine Learning Bioinformatics
• INFO-I 533 Systems and Protocol Security and Information Assurance
• INFO-I 590 Topic: Big Data in Drug Discovery, Health and Translational Medicine - offered online
• ILS-Z 605 Internship

Electives (18 cr.)

Select from the Domain/Application Areas list, the Core Courses list, or the M.S. in Data Science - general - Approved Courses list.  Electives provide an opportunity to make the program your own.  Advising tracks and recommendations from your faculty advisors can help. Be creative in your course strategies.

Requirements

1. Completed application forms (online).
2. Three letters of recommendation that address the applicant’s academic and professional capabilities. It is the applicant’s responsibility to ensure that letters of recommendation reach the Admissions Office by deadline dates.
3. Current resume or CV
4. A personal essay explaining academic and career objectives (minimum 500 words).
5. Official transcripts from each college attended (except IU transcripts, which the department can obtain from the IU Registrar’s online system). From all other colleges and universities, applicants should arrange to have transcripts sent directly to the ILS Admissions Office.
6. Graduate Record Examination (GRE) General Test scores are required of all doctoral program applicants. Master’s program applicants whose grade point average (GPA) in undergraduate college course work is below a 3.0 on a 4.0 scale, or whose GPA on course work completed for a previous graduate degree is not 3.2 or higher, must submit GRE scores in support of their applications. GRE minimum scores are 153 verbal, 144 quantitative, and 4.0 analytical writing.  GRE scores, if provided, will be taken into account in the competitive admissions process and in the awarding of departmental financial aid. The test must be taken within three years of application.  GMAT scores may be submitted for GRE scores for ILS master's degree applicants (minimum of 31 in each area).
7. An application fee. Online applications require payment by credit card.
8. All international applicants for any ILS degree program must submit a recent official Graduate Record Examination (GRE) General Test score report from the Educational Testing Service. The test must have been taken within three years of application.  Scores on all three sections (verbal, quantitative, and analytical) will be considered.  GRE minimum scores of 153 verbal, 144 quantitative, and 4.0 analytical writing are required.  GMAT scores may be submitted for GRE scores for ILS master's degree applicants (a minimum score of 31 in each area is required).
9. Students whose first language is not English must submit recent official scores from the Test of English as a Foreign Language (TOEFL). A minimum TOEFL score of 100 (or 600 on the paper test) is required for admission to ILS graduate programs.

Scholarships

• Merit-based Graduate Assistantships
• Global Education
• Need-based scholarships

The Indiana University Bloomington offers a Bachelor of Science in Data Science designed to prepare students for a wide range of careers in data analysis, data engineering, machine learning, and artificial intelligence. The program provides students with a strong foundation in computer science, mathematics, statistics, and domain-specific knowledge, enabling them to analyze complex data sets and extract meaningful insights. Coursework typically includes programming languages such as Python and R, data management and database systems, statistical analysis, data visualization, and data ethics. Students are also encouraged to develop skills in machine learning algorithms, data mining techniques, and cloud computing platforms. The program emphasizes practical experience through projects, internships, and collaboration with industry partners, ensuring graduates are workforce-ready. Students have access to state-of-the-art facilities and resources, including dedicated labs and computational tools. The faculty comprises experts in computer science, statistics, and related fields who are committed to research and teaching excellence. The program aims to foster critical thinking, problem-solving, and communication skills essential for success in data-driven roles. Graduates of the Data Science program at Indiana University Bloomington often pursue careers in technology companies, healthcare, finance, government agencies, and academia. The program also provides a solid foundation for students interested in graduate studies in data science, computer science, or statistics. Overall, the program's multidisciplinary approach and emphasis on experiential learning prepare students to meet the growing demand for experts capable of addressing complex data challenges in various sectors.