University of Wisconsin Data Science Degree

UW Data Science Professor Motivates Students to Look at Data Through Personal Lens

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When Abra Brisbin was earning her undergraduate mathematics degree from Carleton College, she wanted to apply math and data to areas that made an impact in the real world. To do that, she earned her Ph.D. in applied mathematics from Cornell University, where she focused on statistical genetics—understanding how genetic variations influence people’s health.

In the next two years, Abra completed a postdoc at Mayo Clinic in Rochester, Minnesota, and then moved into her current role as an associate professor in the mathematics department at the University of Wisconsin-Eau Claire. Additionally, she co-develops and teaches courses in the 100% online University of Wisconsin Master of Science in Data Science, including DS 710: Programming for Data Science and DS 740: Data Mining & Machine Learning.

In the following Q&A, Abra shares what drew her into the world of data science, what motivates her to be a teacher in the UW MSDS program, and how she helps her students gain the skills they need to be successful in the field.

Q: What Drew You Into the World of Data?

I think one of the great things about statistics and data science is that you can analyze data from a wide variety of different fields.

When you find an interesting data set, you can figure out what there is to learn from it. For example, I’ve worked with students on research projects involving crime rates in Eau Claire or students who have analyzed factors that influence housing prices in the city—which both have a personal importance beyond the numbers.

Data set from DS 740: Data Mining & Machine Learning

Q: Why Did You Become a Faculty Member of UW MSDS?

It was an opportunity that came up through my connection with Alex Smith—the chair of the mathematics department at UW-Eau Claire. He was getting involved in developing the UW MSDS curriculum and it was really interesting to me. It sounded like a way where I could have some influence over designing these new courses and to really focus on the things that I think are the most important about programming for data science and machine learning.

Q: What are those Important Aspects of Data Science, Machine Learning, and Programming?

I think the problem solving aspect is really important because it’s not just simply following a series of steps. It’s thinking where you use both logic and creativity to come to a solution.

The willingness to learn is also huge. As a professor, I can’t possibly teach all of the algorithms that students might need to know when they go out to do data science in their careers. I make it a point to demonstrate how I figure things out and learn more about how various data science methods work, so that students will be prepared to teach themselves in the future when they are out of a structured learning environment.

Q: What is Your Favorite Part of Teaching Your UW MSDS Courses?

The final project in the DS 740: Data Mining & Machine Learning course is really fun because the students can choose whatever topic they want to analyze. They start by choosing a data set from Kaggle—an online source for data science data sets, programming challenges, and data analysis challenges.

Then, they analyze the data using two of the methods that we cover throughout the course and they come up with their assessment of how the data addresses a question that would be of interest to their target audience and which of the data analysis methods they’d recommend.

This project is when students have a chance to branch out into the data set that’s interesting to them, which can show off their personality and learning style. It’s fun to grade, because I get to read about all of these different data sets that I may not be familiar with.

Data set example from DS 740: Data Mining & Machine Learning

Q: How Would You Describe Your Teaching Style When it Comes to Online Learning?

I’ve structured the courses I teach so that each lesson fits into one week of the semester (although the pace is faster in the summer). Most lessons have some reading and one or more short video lectures, where you can hear my voice or the voices of my co-instructors as we talk through slides or demonstrate an analysis on our computers. Additionally, lessons have some low-stakes practice problems where you can get hints and try them as many times as you want. Then, you have weekly homework, which gives you hands-on experience with implementing the methods discussed in that lesson.

The interactive part of the courses comes from our discussion board and online office hours. Our course discussion board is very active with students asking questions, helping to answer each other’s questions, and even discussing related topics, such as sharing interesting news articles they read about data science. I check the discussion board twice per day, so students get feedback quickly.

I typically have online office hours two or three times a week, once or twice during business hours, and once that’s either in the evening on a weekday or at some time on a Saturday. The goal is that as many students as possible will be able to attend at least one of those times. It can be a phone call or you have the option of sharing your webcam so we can see each other. There’s also a chat window where students can enter questions.

When I’m answering questions in office hours, I can share my screen and demonstrate examples of code or pull up slides from the lecture to show how a question connects with the material that was covered in the class that week. Students can chime in with follow-up questions or help answer each other’s questions. We record office hours and post links to them within the discussion board, so students who can’t attend office hours can still view what was discussed.

Q: What Advice Do You Have for Current and Prospective UW MSDS Students?

Be excited about problem solving and learning about all of the aspects of data science!

Also, be aware that master’s-level courses are challenging, even if they’re only three credits. Students who are working full-time jobs might be better served by taking just one course a semester. Some students who are very motivated can do more than that, but taking three courses in a semester while also working full-time is a very, very heavy load. It’s important to find that balance that works best for your life.

Q: Why Should Prospective Students Consider UW MSDS?

Our program offers a strong balance of the quantitative rigor that students will get from programming and data mining courses along with the business acumen that they get from courses such as DS 735: Communicating About Data and DS 760: Ethics of Data Science.

I think the fact that this program is online makes it really good for students who are currently working in a job that uses some data science and those who want to advance their careers by getting a degree. This program can help them get to the next career step they are aiming for.

Want to learn more about how expert faculty members, like Abra Brisbin, teach, connect, and prepare UW Master of Science in Data Science students for exciting careers in the field? Check out the program’s curriculum or contact an enrollment adviser at 1-877-UW-LEARN (895-3276) or learn@uwex.edu

6 Questions to Ask Before Pursuing a Master’s Degree in Data Science

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Face it, you’ve been on the fence about going back to school for a while now. After Googling master’s degree programs in data science here and there, you still feel overwhelmed about deciding if one is better than another. When there’s countless sources of information tugging you in every direction, it’s best to gather your bearings and figure out the most important details you need in order to guide you in the right direction.

Luckily, we’ve done the legwork. Below are the six most important questions to ask before you begin your application to a data science master’s degree program. Think of this as a mental checklist to help you cross off crucial considerations before taking on your educational future:

1. Do I have an interest in or want to strengthen my problem-solving, data management, and research skills?

When you have an interest in data science practices and want to grow your hard and soft skills, enrolling in a data science master’s degree program is a promising endeavor. In fact, 2019 Emsi research shows that data management, clinical research, and data collection skills are frequently listed in data science job postings, while management, problem-solving, and communications round out the preferred soft skills:

Employers want data science master’s degree graduates to be well-rounded professionals, capable of tapping into the technical side of a role while effectively understanding and communicating data to drive actionable insights. With this in mind, it’s to your advantage to find a master’s degree program that not only prioritizes the hard skills of data science, but also the soft skills. When researching program curricula, look for courses such as “Communicating about Data,” “Ethics of Data Science,” and “Data Science and Strategic Decision-Making,”—all of which expand on skills that are not only needed, but also demanded in today’s data science roles.

2. What are my career goals?

Venmathi Shanmugam, UW Data Science graduate

If you’re looking to be part of a dynamic team in charge of solving real-world problems, or if you want to efficiently draw conclusions from data to better inform actionable business strategies, a master’s degree in data science can set those career goals in motion.

Whether you strive to be a data analyst, database administrator, data architect, strategic business and technology intelligence consultant, or another data-focused professional, the impact of your work can be substantial. For example, Venmathi Shanmugam, a recent graduate of the University of Wisconsin Master of Science in Data Science online program, is the Modeling and Simulations Engineer at the Veterans Affairs office in Austin, Texas. In her role, she manages large amounts of government data pertaining to veterans healthcare and finance. She also holds responsibilities in the supply chain division of her department—using data to positively impact patient needs.

3. Who teaches the data science curriculum?

When enrolling in a graduate school program, you want to feel confident that you are learning from qualified experts in your desired field. A strong data science master’s program is rooted in an interdisciplinary approach, not siloed off to one academic school or department. Diversity in faculty expertise and perspectives is a critical component to consider before applying to a program. Don’t hesitate to research potential faculty members’ background, education, and recently published research studies.

UW Data Science faculty members

The UW Data Science online program is a prime example of an interdisciplinary approach in action, where students learn from faculty members across six UW System campuses. With advanced degrees in mathematics, marketing, computer science, philosophy, management, statistics, and rhetoric and computer composition, graduate students receive the direct benefits of working and learning alongside UW faculty who are driven to grow and advance from every corner of the data science profession.

4. Does the degree program provide a networking community fueled by collaboration?

It’s important to consider how a data science master’s degree program sets you up to connect with industry leaders during your time as a student and after you graduate. Look for programs that feature an advisory board of data science professionals across business sectors. This collaboration of individuals shows that the program is supported by outside experts who can help you connect with future employers and/or mentors.

The UW Data Science online program boasts an impressive advisory board, where recognized data science leaders have the opportunity to shape the program. UW Data Science Advisory Board members can also sponsor capstone projects, plugging students into real-world data science settings where they draw upon their skills and grow from hands-on experiences. Currently, the UW Data Science Advisory Board includes data science professionals in the retail, banking, software programming, manufacturing, state government, insurance, transportation, staffing, and medical fields.

5. Do I have the time to earn a graduate degree?

For some working adults, it is too time consuming to earn a master’s degree through an on-campus program. Travelling to and from a campus throughout the week to sit in on hour-long lectures can complicate the balancing act of work and family responsibilities.

data science

If this is your reality, then pursuing an online graduate degree might be your best option. But, not all online degrees are the same. Make sure to thoroughly research an online degree’s requirements and consider how much flexibility you will need when it comes to lectures, readings, and coursework. 

UW Data Science is a smart choice for busy adults who want to advance their careers, or make a career change. Offered 100 percent online, you can study and complete coursework whenever and wherever you have an internet connection. Courses have no set meeting times, and you never need to come to campus.

6. Is the program accredited and respected?

When deciding to pursue a master’s in data science, you want to be sure that future employers will value the degree-granting institution you’ll graduate from. There’s no question that you can earn a graduate-level education from almost anywhere in the country and world, so how do you know which programs are worth your time and money? Look for degree programs that are accredited by regional and national accreditors, such as the Higher Learning Commission (HLC). 

According to the HLC website, in order to be accredited an educational institution must 1.) have a clear and publicly articulated mission, 2.) conduct actions responsibly, ethically, and with integrity, 3.) provide high-quality education, no matter where and how offerings are delivered, 4.) evaluate its student learning effectiveness and promote continuous improvement, and 5.) have resources, structures, and procedures that support the institution’s mission. 

The UW Data Science program is HLC accredited, signifying that its students receive a high-quality education led by faculty who are committed to staying up to date with the expanding data science field. Plus, UW is known and respected worldwide, helping graduates of the UW Data Science program stand out to employers. As a trusted and valued institution, a UW degree can help graduates accomplish their career and personal goals.

So, you’ve gone through all six questions, what have you found?

With an expert-led curriculum, a 100 percent online format, and a recognized and respected UW degree, now is the time to see where the UW Master of Science in Data Science online program can take you.

Have questions about courses, tuition, or how to apply? Talk with an enrollment adviser by emailing learn@uwex.edu or calling 1-877-895-3276.

From Dentistry to Data Science: A UW Grad’s Career Journey

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In May, Venmathi Shanmugam and her five-year-old daughter shared a special milestone.
They both received diplomas—one graduated from kindergarten while the other from the University of Wisconsin Master of Science in Data Science online degree program.

A couple days before crossing the stage at UW-Eau Claire, her home campus for the program, Venmathi reflected on the major accomplishment:

“When it comes to putting your heart and soul into something, you need to go for it,” she said. “People can say going back to school is impossible. I have a family and a busy, full-time job. If I can do it, anybody can do it.”

Venmathi is currently the Modeling and Simulations Engineer working at the Veterans Affairs office based in Austin, Texas. This dual role includes data engineering and data scientist responsibilities where she works with large amounts of government data pertaining to veterans healthcare, finance, as well as the supply chain division.

Being in the data analytic and data science profession for about seven years now, Venmathi has taken on previous positions in business and IT consulting, statistical data analytics, and clinical programming. But before diving into the data science world, she was on a different path.

“Ten years ago, I was practicing dentistry in India,” Venmathi said. “But the idea of expanding my scope was always at the back of my mind. As a healthcare professional, I needed to work with and understand data. When I reviewed my patients’ medical history before any treatment, I saw patterns in how oral health affected their overall personal health and started getting curious. It was during that time that I realized data science was something that would help me connect all the dots and was an area I didn’t want to miss out on exploring.”

 A Supported Online Degree Experience

After she moved to the U.S., Venmathi completed online certifications in statistics, healthcare informatics, programming, bioinformatics, and more to help bolster her knowledge as she gained experience in various data science roles.

Growing from one job to the next, Venmathi was always motivated to take on new challenges. Already comfortable with online education through her previous trainings and certifications, Venmathi decided that her next step was to get a formal data science degree.

“I took about six months doing course research on every single university that offered data science,” Venmathi said. “The UW Data Science curriculum had a little bit of everything, starting from the very basics and establishing a foundation to progressively dive into more deeper challenges like machine learning, robotics, advanced programming (Hadoop, Spark, AWS), and advanced statistics. When I learned about how the degree was flexible and online, I felt like it was meant to be!”

Venmathi has not forgotten how she felt at the beginning of the program. A feeling that she knows many prospective students might be dealing with.

“I was really worried about what I should expect and if I would even be prepared to go back to school,” she said.
“I was doubting myself and wondered how structured the courses would be. I wasn’t sure if I had the principle and drive to see a full degree through.”

Venmathi’s fears were quickly proven unfounded once she jumped in. She soon got into a routine, with readings, coursework, and other tasks due on the weekends. She loved having deadlines to work against. They were tough challenges with her busy life, but they also brought structure and fun into her learning experience. By having the flexibility to take lessons when her schedule allowed, Venmathi felt like she was accomplishing tasks and learning something new every week.

“In other online courses I didn’t connect with faculty unless it was for quarterly reviews,” Venmathi said. “When I started the UW data science program, I had a lot of questions, and I found that all my professors, my student success coach, Michael Paul, and my student advisor, Dr. Alex Smith, were always there for me. I should really thank all of them for making my time in the program so positive.”

Taking on a Challenging Capstone

Venmathi wanted her capstone to be the culmination of everything she learned. So, she decided to push past all of her comfort zones and pursue a challenging topic involving a combination of AI automatic speech recognition, voice analytics, facial recognition, Natural Language Processing (NLP), advanced Python, and deep learning techniques.

The result was a comparative case study and demo between an Automatic Speech Recognition System (ASR) technology—currently implemented in smart devices—and an Advanced Multimodal Automatic Emotion Recognition System that could potentially combine voice, face, and emotion.

Inspired by her successful projects in the
DS 740: Data Mining & Machine Learning that focused on the use of NLP, emotion recognition, and sentiment analysis from live social media posts, Venmathi began to research and experiment more on the futuristic topic.

“When a user talks to an AI product like Siri and says ‘I’ve had a long day,’ the AI either usually apologizes for not understanding or gives you search results on what that phrase means,” Venmathi said. “You get a little annoyed because the supposedly ‘smart’ device is not smart enough to capture your feelings or tone of voice, unless you spell it out. You keep repeating things, and there is always going to be problems with understanding different accents.”

With the right combination of voice, text, and facial recognition, Venmathi believes the AI could pick up on the stress in the user’s voice, see the frown on his or her face, and launch into a more helpful response.

Venmathi faced a lot of road bumps with the computing and deep learning aspects of her capstone. As she wrapped up her project, she knew there was a lot more research and testing to be done—especially with model tuning and improving fusion accuracy. However, she was happy with how she was able to successfully prove her target goal: that a multimodal emotion recognition system would add measurable improvement to the accuracy rate of the current ASR system.

“Professor Ethan Christensen, who reviewed the capstone project, really appreciated me,” she said. “He was a huge encouragement and recommended that I publish my capstone as a research paper. I am planning on making that happen.”

From One Accomplishment to the Next

Even before graduation, Venmathi could put her data science coursework into action.

“I have a brand new portfolio, including knowledge and skillset on all cutting-edge technologies and tools like NLP, deep learning, AI, Hadoop, Python, R, SQL, Spark, Pig, Scala, and Java, and I find myself becoming useful to my team more and more from everything I learned from the UW courses,” Venmathi said. “It’s a really good feeling when you actually apply your learned skills at work and know that your project can get you a lot more than good grades.”

Now that she has obtained a master’s degree in data science—graduating with a 4.0 GPA—Venmathi feels that she can understand, communicate, and execute on all levels in her data science and data engineering roles— effectively coordinating business, tech, and engineering needs.

Next up, Venmathi has her eyes set on an executive doctoral program in health informatics and leadership and is excited to move from one successful educational experience to another. But for people who are still wondering, like she did, if the
UW online master’s in data science is worth the leap, Venmathi hopes readers take the following words to heart:

“Encouragement or discouragement comes from within ourselves,” she said. “Life and big decisions, like going back to school, are always going to be a challenge—whether it’s today or tomorrow. You will be able to do this, whatever the case may be.”

Start exploring how the UW Master of Science in Data Science online degree program can push you to new career heights. Have questions about the courses, tuition, or how to apply? Talk with an enrollment adviser by emailing learn@uwex.edu or calling 1-877-895-3276.

UW Master of Science in Data Science is a collaboration of several UW System campuses. Venmathi earned her degree from UW-Eau Claire.

6 Surprising Degrees That Set You Up for Data Science Success

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Right brain v. left brain—which one do you prefer? It’s a common assumption that more left-brain professionals are taking the lead in science and math dominated fields. Comfortable with flexing their analytic muscles, pursuing a data science career—the No.1 job in America according to Glassdoor—seems like well, a no brainer.

But what does this mean for the traditionally right-brain folks? Those who find strength in creativity, imagination, and intuition, shouldn’t write off a data science career so quickly. Having a non-technical undergraduate degree can actually complement a master’s degree in data science. Although data scientists do rely on math, programming, and more technical skill sets, a data science career isn’t all about numbers. Often, data is gathered from human behavior. As a result, coming into the data science field with little-to-no prior STEM education can give you a more holistic view of how data can evolve and expand into the future.

The need for data scientists reaches into virtually every industry, providing numerous career opportunities. The following undergrad degrees might seem as right-brain areas of studies. However, they could set you up for data science success:

Sociology
Psychology
Public Policy
Philosophy & Ethics
Journalism
Marketing & Business

Sociology

What is it?
Defined as the scientific study of human groups, a sociology degree focuses on understanding how a society functions through the lens of social constructs that affect individuals and entire populations. Sociology has many branches including education, crime, family life, organizations, race, social class, and more. The common goal of sociology is to see the world differently and understand that not everything is what it seems.

How does it relate to data science?
Data is the result of asking questions, and sociology majors are no strangers to examining why something occurs. If you have a goal of advancing contemporary humanity and have an itch to use data as a tool in the process, sociology and data science can be an advantageous coupling of what may otherwise appear as dissimilar interests. By collecting survey data, sociology-driven data scientists seek to study social phenomena, allowing space for both numbers and creative questions to lead their research. The expansion of Big Data is promising for new areas of social research, such as digital behaviors, longitudinal analyses, and network analysis beyond household connections.

Psychology

What is it?
Simply put, psychology is the study of the mind and behavior. A common assumption of a psychology career focuses on professional therapists who work with a rotation of patients with different needs. However, psychology is a diverse field that touches human development, sports, health, social behavior, cognitive processes, and more. Would you be surprised to learn that data plays an integral part in psychology? Similar to sociology, psychology research aims to answer complex questions regarding human behavior.

How does it relate to data science?
Data science skills, such as research methods and statistics, can help professional psychologists understand data findings and turn them around to drive positive change in patients’ lives. Additionally, by developing evidence-based strategies, those with a psychology background can advance best practices for individuals with learning disabilities. The possibilities of a psychology and data science pairing are expansive and have the potential of truly changing lives.

Public Policy

What is it?
Highlighting social science fields such as economics, public management, and sociology, an undergraduate degree in public policy examines issues within governmental administrations and operations. Adapting theories, research, and models to practice, public policy focuses on how cultural norms, circumstance, and other human differentials affect policy making.

How does it relate to data science?
Research data heavily influences public policy models, which can impact hundreds of thousands of constituent lives. In some states, city government has expanded to include data teams that use civic data to serve communities more effectively. Major questions that a public policy and data science approach can begin to answer include: Can we target outreach and intervention to those at risk of poor health outcomes? Where are there unreported incidents of food poisoning? How can we predict major bridge problems before they happen? How can social media data help identify public safety issues?

Philosophy & Ethics

What is it?
With a degree in philosophy and ethics, graduates become well versed in considering the fundamental questions about who we are. By examining historical and present-day philosophical thought, this area of study strengthens critical thinking, persuasive writing, and effective arguing. Subjects such as political philosophy, metaphysics, logic, philosophy of mind, and more are common in coursework, preparing graduates for careers that value strong communication and problem-solving.

How does it relate to data science?
Although philosophy is a humanities degree, its approach and skills can easily transfer into a data science role. One data science manager who first earned an undergrad degree in philosophy, notes that his philosophy studies prepared him for the hypothesis-driven, logical practice of data science. A philosophy-data science path also spotlights the timely issue of data use and security. As more companies come under fire for data breaches and misuse, data scientists are tasked with an ethical burden of how to handle data. Having a philosophy background can better position data science professionals to be more involved in ethically sourcing, securing, and verifying complete and accurate data.

Journalism

What is it?
The world of journalism is no stranger to change. With the decline of traditional print newspapers and magazines and the swift pivot to digital and social media as main sources of breaking news, reporters now need to be at least 10 steps ahead. Dwindling attention spans mean audiences are distracted, requiring journalists to think outside the box to bolster engagement. While the core principles of journalism stay true: serve the public with fact-checked, credible, objective information—the delivery has changed. And, that is where data journalism steps in.

How does it relate to data science?
Journalism, digital media, and data science are all connected. As Big Data evolves in languages and processes, data scientists must understand digital media technologies that provide a platform for their work. Next, it’s critical for journalists to stay abreast of data security, collection, and usage issues that affect the public—knowledgeable reporting comes from plugging in and understanding the ins and outs of the data science world. As a result, journalists with their drive to learn, understand, and inform, can bring all of those skills into a data science role. In effect, having a journalist’s mindset in a data-fueled world can help piece together the bigger picture of how data touches nearly every part of our lives.

Marketing & Business

What is it?
Advertising, promotion, marketing communications, research, targeting, consumer behavior, and other courses prepare a marketing graduate to land a variety of roles. Marketing and business degrees often cross paths, because having a successful business means also maintaining a strong marketing presence. However, the two disciplines cannot be nearly as impactful without understanding data, often in the form of ROI or digital analytics, such as tracking visits, clicks, and conversions on websites and social pages.

How does it relate to data science?
Human behavior, which can be recorded and interpreted through data, is a critical driving factor behind why a marketing or business endeavor flies or flops. In turn, data companies rely on marketers and business professionals to invest in their tools and services, creating a symbiotic relationship flowing with information. Earning a data science graduate degree benefits marketing and business analysts who are looking to take a deeper dive into how data can better inform and predict their brand strategy and campaigns. Having the ability to review and understand data and then the creativity to turn those insights into an optimized branding push, is an invaluable skill. The CEO of SuperDataScience puts it best: “There’s a science behind analytics; however, communicating insights is an art.”

What’s Next?

Do you have a degree in sociology, psychology, public policy, philosophy, journalism, marketing, or business and intrigued in how data science can expand your professional future? The UW Masters of Science in Data Science online degree can be the bridge between your non-technical education and your next career move.

Earning a master’s degree in data science opens the door to diverse and exciting work with Big Data, and a promising career outlook.

Contact an enrollment adviser to learn about transferable work experience, recent prerequisite coursework, and other admission requirements. Call 1-877-895-3276 or email learn@uwex.edu.

UW Graduate Focuses Capstone On Improving Pneumonia Detection

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Years ago, if you asked Lucas Newkirk about pursuing a graduate-level data science degree, the idea wouldn’t have been on his radar. From college athlete to detecting pneumonia in chest radiographs, Lucas’ educational and career journey took a few turns in order to get to where he is today: A December 2018 graduate of the online University of Wisconsin Master of Science in Data Science program. The following is Lucas’ story of finding his way into the data science field.

After high school, Lucas’ dream was to play football at UW-Lacrosse. However, after sustaining an injury, he switched gears to focus on his education, transferring to UW-Madison his junior year and changing his major to business management and applied economics.

Lucas dove into programming and model building, which led to his first job as a forecasting analyst with Assurant, a small health insurance agency. Seven months into the job, he found himself looking for another, after the company went out of business. Luckily, it wasn’t long before he landed a compliance analyst position at GE Healthcare.

“When I got to GE, I felt I couldn’t advance my day-to-day work to a more senior role if I didn’t pursue another degree,” Lucas said. “I remember back when I worked at Assurant I had looked up data science programs in Wisconsin and the UW Master of Science in Data Science online program caught my eye.”

One of the biggest barriers in taking the next step in his education was affordability. About a year into his role at GE, Lucas learned that his employer provided tuition reimbursement, and Lucas knew exactly where to enroll.

A Data Science and Healthcare Inspired Capstone

Motivated by his drive to earn a data science degree and to advance in his role at GE, Lucas decided to focus on a healthcare industry need for his capstone project. His final capstone paper was “Classification of Pneumonia X-rays Using Mask R-CNN and Transfer Learning.” In layperson’s terms, Lucas programmed a virtual machine on Google Cloud to increase the efficiency and accuracy of pneumonia detections in chest radiographs.

“I wanted to complete a capstone project focused on healthcare because I figured having the experience in my portfolio would help qualify me when pursuing a higher-level healthcare job,” Lucas said. “This was the first time I ever took a crack at deep learning, and now I know I want to keep studying it because I have the tools to do so.”

Lucas credits the capstone project idea to a competition hosted on Kaggle, an online community comprised of machine learners and data scientists who set out to create data sets and build models for data science-related challenges. Proposed by the Radiological Society of North America (RSNA), the original RSNA Pneumonia Detection Challenge on Kaggle asked participants to “build an algorithm to detect a visual signal for pneumonia in medical images. Specifically, your algorithm needs to automatically locate lung opacities on chest radiographs.”

The Kaggle challenge further states that the current approach to detecting pneumonia relies on highly trained specialists who are faced with reading large volumes of images, which often complicates efficiency and diagnostic accuracy. Internationally, pneumonia is among the top five leading causes of death for children under the age of 5 years old. The obvious need in the healthcare community, paired with the challenge of flexing his data science skills, inspired Lucas to use the Kaggle competition as the basis for his capstone.

Finding Success Through Data Science Skills

“I really just wanted to get this one small win in my book and keep going with it,” Lucas said about his capstone. “At the end of the project, I didn’t have winning results, but I did end up getting pneumonia predictions in the 80-percent range.”

Lucas knew he didn’t have much of a chance to compete as an one-man team against big companies in the Kaggle competition. Realistically, his main goal was to figure out how to program the virtual machine with a working algorithm that led to positive pneumonia detection results.

The biggest success for Lucas was getting his virtual computer model to train to his algorithm. Figuring out the coding and using a variety of installation packages pushed his problem-solving skills to new heights. Relying on a paper published by Facebook AI titled “Mask R-CNN”, Lucas learned how to segment images, teaching his virtual machine to identify objects in chest radiographs through focused outlining. This outlining method steered away from the traditional use of bounding boxes that simply draw a square around an area of interest. The outlining algorithm provided a more vivid and accurate detection of hazy sections that could be diagnosed as pneumonia.

Lucas with Dr. Jeffrey Baggett at graduation in December 2018.

Using the data science skills that he learned in the UW Master of Science in Data Science curriculum helped Lucas navigate through the roadblocks and challenges of his capstone. Lucas credits the DS 700: Foundations of Data Science course for teaching him how to investigate, analyze, and complete complex data science class projects. DS 710: Programming for Data Science gave him the coding skills to get started and inspired him to continue learning Python, which turned out to be the language he used for his capstone. DS 745: Visualization and Unstructured Data Analysis helped Lucas learn critical presentation skills to display data in a graphical way, which he applied to the charts and data featured in his capstone.

The Benefits of an UW Online Degree Program

Flexibility in class schedule and assignments was a must for Lucas. He couldn’t travel outside of Milwaukee because of his work commitments, and he didn’t want his contribution at GE to suffer from being spread too thin. The UW Master of Science in Data Science online program afforded Lucas to work at his own pace and provided access to professors and faculty members outside of typical 9-to-5 work hours.

“One concern I had when starting the degree program was how much communication I would have with the professors and faculty members,” Lucas said. “I figured online degree programs would be less involved, or the instructors would be less available, but it actually turned out to be the opposite.”

Lucas admits he worried that online class sizes would be infinite, since anyone could log onto a computer at anytime. However, his classes were not too large to manage, because UW Extended Campus tracks average enrollments per course section and caps enrollments for any course at 30 students. When needed, additional sections are available for courses that exceed the 30 student maximum, ensuring access to all students while maintaining an optimal learning outcome. Students participate in projects and discussions in smaller groups within each course section. Online student resource lounges also help students stay engaged through peer interaction.

“I still talk to one of my class partners I had in my DS 735: Communicating About Data course,” Lucas said. “I was ahead of him in the program, and we message each other to see how we each are doing, or he asks me what he should expect in certain classes.”

From Capstone to Career and Beyond

With the capstone project and an UW Master of Science in Data Science degree added to his résumé, Lucas is excited to dive into another Kaggle competition, continue to collaborate with colleagues and other data science peers, and to focus on using his experience in the degree program to hone his skills.

At GE, colleagues outside of Lucas’ department have noticed and now rely on his data science capabilities. “At work, I just competed in a coding competition with a goal to simplify sales processes,” Lucas said. “I was the only person from the compliance department in the group, and I ended up taking second place. It radiates throughout the company when people know you have skills that can help streamline their workflows.”

For individuals considering how a data science degree can help them with their career aspirations, Lucas is quick to encourage them that now is a great time to dive in. If he had known the experiences he’d gain and skills he’d acquire in the UW Master of Science in Data Science online degree program, he would have enrolled sooner.

“Data science is ever evolving and it’s never going to get simpler,” Lucas said. “You want to jump in now. I have no regrets that I jumped, and now I am looking forward to where this degree continues to take me.”

What’s Next?

Start exploring how the UW Master of Science in Data Science online degree program can push you to new career heights. Have questions about the courses, tuition, or how to apply? Talk with an enrollment adviser by emailing learn@uwex.edu or calling 1-877-895-3276.

UW Master of Science in Data Science is a collaboration of UW System campuses. Lucas earned his degree from UW-La Crosse.

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