This program is available to current Michigan Tech undergrads as an accelerated master's degree.
A multidisciplinary program that couples computer science, business, engineering, and mathematical sciences to create logical and innovative solutions for data producers. Less than five percent of available data is currently mined effectively; the Data Science program positions graduates to enter the job market in high demand.
What you'll work on
Data Science is a flexible program allowing students to explore and develop their own interests in a rapidly expanding field. Data scientists occupy a unique niche in a variety of industries, from retail to finance to healthcare. At Michigan Tech, you can research sensors, develop pattern recognition algorithms, engineer intelligent machines, interpret medical data to determine risk, make predictions using data to improve the power grid, and more.
Sample Areas of Interest
- Sensor Networks
Who you'll work with
Work with interdisciplinary faculty to develop your career path. The program is designed for people with diverse backgrounds but allows for specialization. Whether researching machine learning, designing algorithms for forestry, or conducting computational social science, a Data Science degree is an investment in the future.
"It’s 80 percent and 20 percent."
Big Data is a big deal, and data mining depends on the skills of computer scientists. While 80 percent of our time is juggling this data, it’s what we learn in that other 20 percent that makes all the difference. Brown and her colleagues work with the 80 to push what’s possible in that 20.
Where you'll work
The options are limitless. Producers of big data include, but are not limited to: social media corporations, e-health networks, telemetry devices and sensors, e-retailers, environmental agencies, and information security agencies. Data scientists frequently interact with stakeholders and decision makers to properly present the information produced with data science algorithms. A core skill is the ability to convey a challenging concept to someone who doesn’t necessarily understand data science.