Data Science Degree Curriculum | Courses & Specializations

Data science has several facets, but overall, it deals with the study of data. A data science degree can help you land a job in numerous fields and roles, from computer science to engineering.

In a data science degree program, you'll learn the basic concepts and progress to understand more advanced concepts of the field. Keep reading for a deep dive into what you can expect in a data science degree curriculum.

What Is Data Science?

Data science is a broad field that, at its core, is about the various facets involved with studying data. This includes gathering data, analyzing data, drawing conclusions from data, and communicating that data.

It also includes building and maintaining the systems that do this work, meaning it is a field heavily steeped in computer science and information technology. Data science is used in many industries, including business, finance, healthcare, and politics.

Core Components of a Data Science Degree

If you're earning a bachelor's degree in data science, your program will likely be broken up into two sections. The first two years will be focused on completing your general education courses. Usually, this includes various liberal arts courses and a handful of science, technology, engineering, and math (STEM) courses.

When these prerequisites are complete, you'll start the coursework for your data science major. These include the fundamental data science courses required by your university, plus any concentration courses or elective courses needed to meet the minimum credit requirement.

If you're earning an online data science master's degree, you won't need to worry about the general education courses. All your coursework will be focused on your major.

Areas of Study

Your data science curriculum will vary by institution, but there are common topics that all data science majors generally teach. These include:

• Statistics and probability: Developing statistical models is core to what data scientists do, and these courses will cover topics like statistical inference and linear regression.
• Programming and software development: Students learn multiple programming languages in their data science degree, including Python, R, and SQL.
• Data analysis and visualization: Your degree program will also cover the fundamentals of analyzing data and presenting your findings in a visual format that's easy to understand.
• Machine learning and artificial intelligence: Data scientists use machine learning models to develop algorithms for data processing, so students learn how to build and tweak these models.
• Database management and big data technologies: Big data refers to particularly large data sets, and this type of course covers how to build and use data structures to manage this data.

Common Courses in a Data Science Major

Again, the specific courses you take will depend on your school's data science curriculum. However, common courses include:

• Introduction to Data Science: This course covers the foundational aspects of data science and the role that data science plays in the real world.
• Statistical Methods and Data Analysis: This type of course covers the basic statistical concepts of data science, including forecasting, Bayesian approaches to inference, and data reduction.
• Programming for Data Science: Programming courses cover the different programming languages used in data science, including Python and R.
• Machine Learning and Predictive Modeling: These courses cover machine learning basics, including supervised and unsupervised learning, neural networks, and deep learning, as well as how machine learning can be used to uncover complex data structures.
• Data Mining and Big Data Analytics: These courses describe how to manage and process big data sets, primarily for business purposes.
• Data Visualization and Communication: In a data visualization and communication course, you'll learn how to communicate your findings in an easy-to-understand format to help solve real-world problems.
• Database Systems and SQL: These courses focus on developing and managing database systems, including data modeling, SQL, and cybersecurity.
• Capstone Project or Internship: Most programs conclude with a capstone project or internship, in which you can showcase the skills you've developed.

If you've chosen a concentration, your remaining courses will be focused on that particular area of data science. Otherwise, you'll have the opportunity to choose electives that will propel you toward your chosen career path in data science.

Learn more: What Can I Do With a Data Science Degree?

Key Skills Developed in a Data Science Program

Data science programs help students develop numerous skills that will carry them through to success in the data science field. These include:

• Analytical and problem-solving skills: Data science degrees train students to not only analyze data but to solve problems as they arise.
• Proficiency in programming languages: Data scientists need to be proficient in multiple programming languages, and your degree will train you in core languages like Python and R.
• Knowledge of machine learning algorithms and their applications: There are various machine learning and natural language processing tools; data science students learn how to best utilize these tools to manage and process data.
• Ability to work with large datasets and database systems: Working with big data can be a challenge, but your program will teach you how to best build and manage database systems for large datasets.
• Data visualization and storytelling techniques: All the insights you gather from data are useless if you can't properly communicate them, and your program will teach you the best ways to communicate your results, like graphs and charts.

Specializations Within a Data Science Major

Often, Bachelor of Science and Master of Science in data science (MSDS) degree programs offer concentrations or specializations. These allow students to focus on a particular aspect of data science. Common specializations include:

• Machine learning and artificial intelligence: Artificial intelligence has several uses within data science, and machine learning focuses on using data analysis to automate various processes. These specializations are great for those interested in robotics, deep learning, recommender systems, and reinforcement learning methods.
• Business analytics and data-driven decision-making: Business analytics focuses on the use of data to make business decisions. This field requires strong statistical analysis, database management, and regression modeling skills.
• Big data and cloud computing: As we mentioned, big data refers to large datasets, primarily gathered from marketing analytics. Cloud computing is a way to store this data over the internet, and students in this specialization will focus on the optimization and analysis of business data.
• Health informatics: In the healthcare setting, data science is used to improve patient outcomes, manage public health, and uncover trends in healthcare and biology.
• Computational social science: Computational data science is a field that uses data and computational methods to better understand people and society. This is a great choice for those who want their science with a side of humanities.
• Data engineering: Data engineers are responsible for creating and maintaining database systems and data warehouses. Those in this specialization will take extra courses in programming languages, optimization, and data visualization.

Earn Your Data Science Degree Today

If you're interested in a data science degree, check out the accredited data science programs listed on Learn.org. Reach out to individual programs today to start your career path in data science.