Online Bachelor's in Data Science

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Online Bachelor’s in Data Science Curriculum

In the modern business landscape, data drives strategy and informs almost every decision — from healthcare to marketing, from government to finance. And there’s more data being produced than ever.

Increasingly, organizations rely on data science experts to analyze this information and use it to make better decisions. By enrolling in a bachelor’s in data science program, your data science curriculum can help you build the in-demand skills and competencies to transform data into formats that future employers value.

With an in-depth understanding of how to organize and interpret data, you can enter a quickly growing, potentially lucrative field.

Maryville University Online BS in Data Science Curriculum

Maryville’s online Bachelor of Science in Data Science comprises 128 credit hours and includes coursework in general education, the data science major, general electives, and an optional concentration in actuarial science. With our online data science degree, you’ll do more than explore statistical theory, mathematical methods, and the latest data technologies. You’ll complete hands-on projects that allow you to see the practical application of your studies.

Data Science Courses

DSCI 200Foundations of Data Science3 Credits
DSCI 201Math Modeling – Excel3 Credits
MATH 251Calculus III3 Credits
DSCI 302Introduction to R3 Credits
DSCI 303Introduction to Python3 Credits
DSCI 304Introduction to SQL3 Credits
DSCI 307SAS Programming3 Credits
MATH 316Applied Linear Algebra3 Credits
DSCI 318Statistical Design3 Credits
MATH 370Probability I3 Credits
MATH 371Probability II3 Credits
MATH 372Mathematical Statistics3 Credits
MATH 405Statistical Modeling I3 Credits
DSCI 408Machine Learning3 Credits
DSCI 412Predictive Modeling3 Credits

Want to learn how to get started?

To ensure the best possible educational experience for our students, we may update our curriculum to reflect emerging and changing employer and industry trends.

What skills and competencies are taught in data science courses?

Most bachelor’s programs in data science equip students with foundational skills they can apply in a wide variety of fields. Whether you want to pursue a career in business, social science, engineering, computer science, or any number of industries, earning your bachelor’s in data science can help you learn the skills to contribute and lead in your organization.

Bachelor’s in data science programs cover topics like:

  • Data analysis. When presented with raw information, professionals trained in data science will know how to transform it into valuable insights that benefit businesses and organizations. Through these insights, data scientists can lead their teams toward efficiency improvements, increases in profit margins, quality advancements, enhancements in customer experience, and much more.
  • Programming. Big data requires advanced tools. For this reason, your data science curriculum will typically help you become proficient in several programming languages used to compile and synthesize data. Common programming languages of focus include Python, SQL, and R. These languages have many practical applications in computer science, and you can leverage them to advance your career across a variety of fields.
  • Predictive modeling. Throughout your data science bachelor’s program, you also can expect learn about the principles of predictive modeling. The skills you build in these courses can help you extrapolate information to discover insights and create intelligent forecasts.
  • Computer science, statistics, and economics. Data science is a unique field with application across disciplines. It stands at the intersection of business, statistics, artificial intelligence, machine learning, and more. So it’s paramount that data science courses prepare graduates with a breadth of knowledge in computer science, statistics, and economics.

What data science courses can I expect to take at the bachelor’s level?

The curriculum for data science degrees varies from university to university, but programs tend to feature a heavy focus on topics like programming, modeling, mathematics, and computer science. Here are some of the courses you can expect to take in your data science curriculum:

  • Data Science. Develop your foundation in the core concepts of data science by manipulating real-world data and models. Enhance your skills in areas such as statistical inference and computational techniques. Then, apply these skills in your advanced coursework or your career.
  • Probability. In your probability courses, you’ll have the chance to study important mathematical concepts like conditional probability, percentiles, distributions, and a number of applicable theorems. Coursework in probability typically builds on knowledge gained in required mathematics classes.
  • Experimental Design. Develop your comprehensive understanding of experimental design, an important skill for all scientific fields. You’ll have the opportunity to explore topics like types of designs, sample size, model comparison, and survey data analysis. This course also features an experiential element that incorporates project-based learning, so you can enhance your problem-solving and collaboration skills.
  • Predictive Modeling. Learn to apply your knowledge to real-world business problems through predictive modeling. Topics you’ll have the opportunity to study in this course include types of models and principal components analysis. Discover how to build predictive models and effectively communicate your findings.
  • Mathematics and Modeling. A comprehensive understanding of data science requires a strong foundation in mathematics. In this course, you’ll have the chance to build your skills in math modeling by using database programs such as Microsoft Excel, advanced calculus, and applied linear algebra. Learn how to leverage databases for graphical output, and discover applications for partial derivatives and multiple integrals. Plus, you can study linear algebra topics such as vector spaces and subspaces, matrix algebra, and linear transformations.
  • Statistics. If you want to excel as a data scientist, you’ll need to be proficient in mathematical statistics and statistical modeling concepts. In mathematical statistics courses, instructors convey the concepts of inference, statistics, and the primary methods of estimation — and how data scientists can apply each in real-world settings. In this course, you can discover how to develop and interpret statistical models, as well as recognize and understand assumptions. Topics covered include hypothesis and model testing, estimation, data forecasting, and confidence intervals.
  • Machine Learning. At Maryville, our undergraduate data science curriculum includes this course covering the hot topic of machine learning. Here, you can discover how to develop smart algorithms that can automate complex processes by analyzing large volumes of data. Topics include regression splines, generalized additive models, tree-based models, support vector machines, principal components analysis, and clustering methods. And project-based learning can help you develop effective problem-solving skills and become a better collaborator in your organization.

Learn more about the B.S. in Data Science curriculum.

Are you interested in expanding your technical expertise in the fast-growing field of data science? Start here. At Maryville, we designed our online B.S. in Data Science to help you build your understanding of data analysis, programming, predictive modeling, and other skills.

When you earn your online data science degree, you can expand your digital and analytical technical expertise. Discover how our online degree program can help prepare you for the process of pursuing a career in data science.