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, Amazon Web Services), 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
DS 740: Data Mining 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.wisconsin.edu or calling 608-800-6762.
UW Master of Science in Data Science is a collaboration of several UW System campuses. Venmathi earned her degree from UW-Eau Claire.
