Gain skills that are invaluable in today’s world. Prepare to enter one of the most rapidly growing fields with a Master’s in Data Science program.
Master's
Graduate
36
12 months
Salem, Portland
As a high school math teacher, Colleen Smyth MS '21 put knowledge into action immediately -- by taking what she learned in her data science classes and using it to help her students succeed.
For her capstone project, Colleen examined data based on three years of graduates in an attempt to discover predictive factors of on-time graduation. She created a classification model that allowed her to identify patterns in GPA and course history. Colleen identified areas her school could focus on and shared her findings with the principal.
Alumni of the MSDS program are making their mark and emerging as leaders in many tech-related fields. They are pursuing opportunities with some of the world’s most innovative companies and helping organizations maximize their potential. From major brands and government offices to non-profits and start-ups, find out more about the impact of Willamette alumni.
From Willamette to Microsoft
Just weeks after graduating from Willamette's MS in Data Science program, Cameron Bayer landed a role on Microsoft’s Azure Edge Observability and AI team, where he helps monitor and improve one of the world’s largest cloud platforms.
Turning Data Into Better Healthcare Access
Maile Sakamoto MS’24, an Informaticist at Humana, uses data to help improve medication access and affordability for Medicare and Medicaid members, turning her passion for healthcare into meaningful, community-focused work.
The MSDS faculty is made up of industry experts who have experience applying the latest technology to modern challenges. They have used their skills to elevate the enterprises of organizations across many sectors. By acting as mentors, they offer students one-on-one career advice and personalized guidance.
Professor Gore brings extensive experience from her tenure at HP Inc., where she led statistical data strategies and quality systems for advanced technology platforms. In addition, she has a passion for STEM outreach, serving as a LEGO robotics volunteer. Her academic interests include Industry 4.0, statistical engineering, survival analysis, and environmental statistics.
Professor Brown teaches computer science, specializing in computer graphics, vision science, and human perception. Her interest in vision science began in college when she recovered her stereo vision through therapy after realizing she was stereo-blind. Prior to Willamette, she worked at Adobe and NVIDIA.
Professor Kitada Smalley, Willamette’s Albaugh Assistant Professor of Statistics and Data Science, is an applied statistician with expertise in survey methodology and data visualization using R. Her work has been recognized nationally, and her research explores bias estimation in public opinion surveys, experimental design, and educational research.
The Data Science program uses a curriculum that incorporates the most current industry insights and technology. Students will complete eight courses with a culminating capstone class which includes a group project using real data.
Students will cover topics including programming with R and Python, data engineering with SQL, data visualization, and machine learning (AI), while also exploring the critical ethical questions facing data professionals today.
Willamette’s School of Computing and Information Sciences prioritizes industry collaboration, and curriculum is frequently updated to ensure relevance to the modern tech landscape.
Explore the legal, policy, and ethical implications of data. Examine the issues that arise at each stage of the data science workflow including data collection, storage, processing, analysis and use. Students are confronted with topics including privacy, surveillance, security, classification, discrimination, decisional-autonomy, and duties to warn or act. The course addresses real-world problems in areas like criminal justice, national security, health, marketing and politics.
Machine learning is becoming a core component of many modern organizational processes. It is a growing field at the intersection of computer science and statistics focused on finding patterns in data. Prominent applications include personalized recommendations, image processing and speech recognition. This course will focus on the application of existing machine learning libraries to practical problems faced by organizations. Students will learn how to use machine learning to solve real world problems, run evaluations, and interpret their results.
Willamette University
Ecotrust Building
721 NW 9th Ave
Portland
Oregon
97209
U.S.A.