Data & Methods Concentration
(Applied Data Science)
What is the Data & Methods (Applied Data Science) concentration?
Students in this concentration learn a multidisciplinary field that applies data analysis methods and models to real-world problems to generate insights and support decision-making.
MSBA students learn a range of skills including:
Machine Learning (Supervised & Unsupervised)
Neural Networks
Gen AI for Business Analytics
Applied Data Optimization
Big Data Concepts & Usage
and much more…
Elective Courses
Advanced Analytics 1 (Intro to Neural Networks)
Big Data Analytics for Business
Advanced Analytics 2 (Applied Optimization)
Tools for Data Science
Professor Elhamod teaches courses like Neural Networks, Unsupervised Learning, and Gen-AI (with LLMs), while currently coordinating the Data & Methods Concentration for MSBA. He has his PhD in Computer Science and was a software developer at Microsoft.
Teaching Faculty
Select names to view LinkedIn profiles:
Gordon Burtch - Advanced Analytics 1 (Intro to Neural Networks)
Mohammad Soltanieh-ha - Big Data Analytics for Business
Fang Wan - Advanced Analytics 2 (Applied Optimization)
Ziba Cranmer - Tools for Data Science
MSBA students are prepared for a variety of applied data science careers. See below to learn more about current and former students in the data & methods concentration.
Featured Alum - Stella Vardanega
Senior AI Data Scientist @ Beckman Coulter Diagnostics
Other MSBA Alumni Working in Applied Data Science Careers
Select link in their position to view LinkedIn profiles!
Aash Gohil - Data Science Associate @ Amazon
Ruchika Venkat - VP of Lead Data Scientist @ Citi
Sherry Zuo - Data/AI Engineer @ Assette
Siyu Liu - Manager Analytics Engineer @ Spotter
Geech Huot - Data Engineer Specialist @ Havas Media
Amber Wu - Business Reporting Analyst @ Apple
Meet current students who have applied data science experience
and/or are concentrating in Data & Methods
Call to Action
Reach out to MSBA Director of Industry Relations, Ashley Mahanama, for more information
Mentor/Teach
Guest lecture in a class
Provide career guidance, i.e., mock interviews or resume feedback
Offer an action learning experience
Hackathon project
Internship or co-op
Recruit
Host an in-person or virtual employer spotlight
Attend our analytics career fair
Share JDs and receive selected strong fit resumes
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