With Performance-Based Admissions, Mattison Hineline Can Earn a Master’s and Pursue a New Career in Data Science - Coursera Blog
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Home » Explore by role » Data Science & Analytics Roles » With Performance-Based Admissions, Mattison Hineline Can Earn a Master’s and Pursue a New Career in Data Science
With Performance-Based Admissions, Mattison Hineline Can Earn a Master’s and Pursue a New Career in Data Science
May 4, 2022
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After graduating with her bachelor’s in psychology, Mattison Hineline moved to Málaga, Spain, to teach English. During the pandemic, she started taking programming classes online and became increasingly intrigued by the stats and graphs being used to track COVID-19’s impact. As her interest in data and programming grew, Mattison began to think about the possibilities of a career in data science.
She determined that she wanted to earn her master’s, but was concerned about cost, her lack of data science experience, and the challenges of relocating back to the US from Spain. So she began to look at online options. 
Mattison was familiar with Coursera already, having taken the Introduction to Calculus course. After two months of research, she concluded that the Master of Science in Data Science (MS-DS) program from the University of Colorado Boulder on Coursera offered the right opportunity for her.
The program was flexible, affordable, and the performance-based admissions structure meant she didn’t have to worry about things like transcripts, GPA, or GRE scores–she’d just need to demonstrate she could do the work, and she’d be accepted. Determined to pursue a new career in data science, she successfully enrolled in the Master of Science in Data Science (MS-DS) program from the University of Colorado Boulder on Coursera!
“I would not have had an opportunity to get my data science master’s if I didn’t find the MS-DS program on Coursera.”
After having had initial reservations about her lack of experience, she found she was able to get the support she needed whenever she ran into obstacles:
“I struggled with my second statistics course and went to office hours a lot. The course facilitator really helped explain the material and make sure I wasn’t just passing the class but understanding the concepts. The information you learn is important to your future projects, courses, and jobs. Understanding the content is just as important as passing the course.”
Mattison has also been able to network with other students. She and her fellow learners connect via a shared Slack channel, and students even organize remote study groups to talk through coursework. Recently, she secured her first data science internship, and she’s currently planning to graduate in 2023 and move right into a data science role—ideally at a startup.
Her biggest tip for new students? Start with a non-credit course first to get used to the course material and online learning format. She also recommends being active on Slack, attending office hours, and reaching out to peers. “Being communicative,” she says, “equals success!”
If you’re interested in pursuing a data science career and want to follow Mattison’s advice and try a course yourself, we recommend the Vital Skills for Data Science Specialization as a great starting point for beginners. It’s a great way to master data science fundamentals, and once you’ve completed the non-credit version of the course, you can transfer your work into the paid, for-credit version that will count towards your degree.
This fully online Master of Science in Data Science (MS-DS) from the University of Colorado Boulder is an ideal choice for career-focused learners eager to benefit from a comprehensive, multi-disciplinary approach. This program leverages unparalleled faculty expertise across statistics, data science, computer science, natural language processing, information science, and more.
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