“Using data science to an extent in my position, I became curious as to how it could be more applicable to what I do. I wanted to learn more tools to apply data science practices to our company and better understand our customers. DataScience@SMU utilizes the most relevant tools that a data scientist would need to get the job done. SMU’s curriculum also combines statistics with programming better than other programs that seem to focus on one discipline over the other.”

“DataScience@SMU has prepared me to support some of the initiatives my company is focused on. From concepts such as NoSQL to visualization, I am able to build dashboards to visualize data for end users to make informed decisions. I am determining how my company can leverage key data science concepts such as machine learning and cloud computing to operate efficiently. Learning these tools helps position me for a more impactful role with my company.”

“With a need for in-depth analytics in my current company and a growing need for professional data scientists, I thought this would be a great investment in my career.”

“Really get to know your classmates. Develop relationships outside of class. Everyone brings different career expertise into the program, and that is part of what makes the DataScience@SMU experience so unique. I was in class with people who had backgrounds in marketing, energy, journalism, technology and finance. My background and career focus is in cybersecurity. We were all looking to learn and apply data science skills to our specific domain of expertise.”

“Having a Master of Science in Data Science has provided me with a tremendous depth of knowledge in the field of data science. The multidisciplinary approach of the DataScience@SMU curriculum contributed to the development of my skills in coding, statistics and data visualization.”

“Since completing the DataScience@SMUE program, I have continued to apply the data science skills I have learned in the program to my current job. While I was in the program, I was promoted to my current role as an integrated operations data science analyst. Also, I work as a machine learning teaching assistant for SMU teaching Master of Science in Data Science students Python machine learning skills and related concepts.”

“The program includes a good mixture of programming and theory, providing a broader view of the skills learned. I appreciate how programming reinforces theory and theory informs programming throughout the curriculum. As you might expect, there is an abundance of data to review at NASA. Recently, my group has discussed bringing me into that part of that process.”

“After graduating from the DataScience@SMU program my role in my company has moved more in the direction of developing complex solutions to internal problems and away from our everyday analysis problems, which has made my work more fulfilling.”

“Professionally, I have leveraged much of the content I learned in the DataScience@SMU program by implementing transformational strategies in the fields of advanced machine learning and predictive analysis.”

“One of the biggest takeaways from the program was learning where and how to apply specific statistical techniques. I have been able to apply this knowledge in my current role, and it has led to meaningful results.”

“I have used everything in this degree. While developing an API, I used the principles of databases, data transfer, data structures and networking. Post development, I have used the components of data visualization to improve our monitoring graphics so we can quickly communicate our systems health. I have been able to use statistical and analysis and data mining to pull information about my service to improve and place priority on my most in-demand features.”

“The fundamentals of programming was the most valuable thing I learned in the DataScience@SMU program. Thankfully, I learned multiple languages during my schooling, and as a result, I learned how the fundamentals of programming can cross over to different languages.”