MS Business Analytics (MSBA)

PROGRAM PROFILE

Pacing: Full-time
Program Length: 16 months
Format: In-Person
Class Schedule: Weekdays on campus.
Student Profile: Early-career professionals
STEM Designation: For international applicants, this program is eligible for the OPT-STEM extension

MSBA PROGRAM BENEFITS

TRANSFORMING STUDENTS TO BUSINESS PROFESSIONALS

Transitioning one’s mindset from an undergraduate student to a data professional is an important journey. When done well, as much as half of the learning process in a top graduate program happens outside the classroom and beyond the coursework. It is through workshops, industry events, social events, and other weekly opportunities that students build additional skills in the MSBA program. At Marshall, the journey each day is to prepare for greater career success.
REAL-WORLD EXPERIENCE THROUGH CASE COMPETITIONS

Our Marshall Case Competition Program ensures students have opportunities to be market ready with real-world project experience. Students combine what they are learning in the classroom with their industry interests and collaborate with diverse, cross-functional teams, making the case competition experience as valuable as an “internship in a week.” Real-world unstructured problems, real teams, real impact. Our opportunities are extensive and inclusive of all MS Business Analytics students, with a case team of over 200 data professionals.
The MSBA Marshall Global Case Competition program is founded on partnerships with professionals and mentorships for students. Why wait for summer to build a project portfolio? We bring market leading opportunities to you at Marshall.
UNIQUE, FUN & COLLABORATIVE CULTURE

The Business Analytics program fosters a culture where students work closely together and support each other. As the criteria of today's data science professionals is the ability to work in teams, the MSBA program provides students the ability to fine tune that skill set. Students are provided the tools and environment to build a strong team and collaborate on outcomes, allowing them to enhance their leadership skills and create the optimal career path.

MS BUSINESS ANALYTICS CURRICULUM

The Master of Science in Business Analytics (MSBA) degree requires 33 units, taken in 3 semesters (with the flexibility of extending to 4 semesters): Fall, Spring, and Fall. There are 21 units of required coursework, including an internship opportunity, plus 12 units of coursework chosen from a list of electives.

USC MSBA's Three Pillars: Computer Science; Statistics, Machine Learning, Optimization; and Business Strategy.

Actual schedules may differ between students for various reasons and will be determined with the guidance of the Academic Advisor.

First Semester (Fall)

GSBA 545: Data Driven Decision Making (1.5 units)

DSO 545: Statistical Computing and Data Visualization (3 units)

DSO 570: The Analytics Edge: Data, Models, and Effective Decisions (3 units)

DSO 552: SQL Databases for Business Analysts (1.5 units)

GSBA 542: Communication for Management (1.5 units)

Second Semester (Spring)

DSO 510: Business Analytics (1.5 units)

DSO 530: Applied Modern Statistical Learning Methods (3 units)

DSO 553: NoSQL Databases in Big Data (1.5 units)

Elective (3 units)

Elective (1.5 units)

Summer

DSO 595: Internship in Data Sciences or Operations (0-1.5 units)

Third Semester (Fall)

DSO 573*: Data Analytics Driven Dynamic Strategy & Execution (3 units)

Elective (3 units)

Elective (1.5-3 units)

*DSO 573 can be replaced with DSO 574 (Getting Ready for Big Data), which is offered in the Spring or DSO 556 Business Models for Digital Platforms

Programming:

Data Cleaning
Data Wrangling
Data Visualization
Web Scraping
Database Management
Python (Main Language of Study), R, SQL, NoSQL

Statistics + Machine Learning

Probability Distributions
Inferential Statistics
Supervised Learning Methods (linear regression, logistic regression, lasso, ridge regression, decision trees, LDA, QDA, KNN, PCR, neural networks, random forests, SVM)
Unsupervised Learning Methods (k-means, hierarchical clustering)
Deep learning (CNN, RNN, LSTM, GAN)
Simulation Models, Linear, Non-linear, Discrete, Dynamic Optimization

Business Strategy

Marketing Analytics, Fraud Analytics, Operations Analytics, Game Analytics, Time-Series Analytics, Healthcare Analytics, Supply Chain Analytics
Pricing Strategies
Text Analytics & Natural Language Processing
Business Communication
Dashboarding, Consultation, Collaboration, Strategy
Problem Solving, Problem Framing

APPLYING TO MSBA

APPLICATION DEADLINES

	Deadline
Round 1	November 15, 2023
Round 2	January 15, 2024
Round 3	March 15, 2024
Round 4	April 15, 2024
Round 5	Rolling Admissions until Fall 2024 Cohort is full, or the final deadline of May 15 passes**

It usually takes about 8 weeks for the admission decision to be released and sent via email, after each round of deadline.

No international student applications will be accepted after April 15, 2024, due to immigration requirements and timelines.

Applications will not be reviewed once the class is full. To be sure your application is reviewed, plan to apply by April 15, 2024

Important Dates:
Application opens: October 1, 2023
International Student Deadline: April 15, 2024
Welcome Week: August 16-23, 2024
Classes begin: August 26, 2024

REQUEST INFORMATION

For more information about this program, please fill out the form below. If you have further questions you may EMAIL the admissions team directly.

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STUDENT LIFE

Business Analytics Student Association

The Business Analytics Student Association (BASA) is a student-led organization dedicated to empowering MSBA students with the necessary networking and professional skills to succeed in their careers. Additionally, we aim to enrich the student experience and establish a strong community of business analytics professionals within USC and beyond. To achieve this, we offer a diverse range of opportunities including workshops, networking events, case competitions, social gatherings, and more.

VISIT THE BASA SITE Business Analytics Student Association

MSBA FACULTY

Dawn Porter
- Fubon Chair in Teaching Excellence
- Academic Director, MS Business Analytics
- Professor of Clinical Data Sciences and Operations
Dawn Porter is a statistician who has published in Management Science and is the coauthor of Basic Econometrics (fifth edition). Prior to joining USC, she served on the faculty at Georgetown University. Professor Porter has consulted for KPMG Consulting, Ginnie Mae, Inc., and Toys R Us.
Mohammed Alyakoob
- Assistant Professor of Data Sciences and Operations
Mohammed's research examines the economic and societal impact of digital marketplaces, with a focus on examining and measuring the role of traditional barriers, related to market structure, race, and expertise, among others, on limiting the equality of benefits derived from these platforms.
Arif Ansari
- Professor of Clinical Data Sciences and Operations
Arif Ansari is an expert in the area of data mining, business intelligence, data warehousing, and intelligent systems and technologies, a field in which he has fifteen years of research experience. He has published in IEEE Transactions on Systems and Man and Cybernetics.
Cosimo Arnesano
- Assistant Professor of Clinical Data Sciences and Operations
Cosimo Arnesano, Ph.D., MBA is a highly educated and experienced professional with a strong background in research services and business analytics implementation. With a Ph.D. in multiple fields and an MBA from the University of Southern California, Cosimo possesses a diverse skill set that includes fluorescence microscopy, biomedical engineering, Project/Operations Management, ML/AI, and more. His current interest focuses on how AI/ML can be applied to business processes, and their implications in the short and long run.