Master of Science in Data Science for Learning Applications

The Master of Science in Data Science for Learning Applications (DSLA) online program, offered jointly by the USC Rossier School of Education and the USC Viterbi School of Engineering, empowers professionals to harness data science and learning theory to design equitable, data-informed educational solutions for diverse learning environments.

The DSLA online program prepares professionals to lead innovation in educational technology, analytics and instructional design. This fully online program blends learning theory, data science and motivation research to address complex challenges in education and workforce training.

Students gain hands-on experience in programming, analytics and machine learning to design, evaluate and improve learning systems. The curriculum emphasizes real-world application through projects and a final capstone focused on solving practical educational challenges.

Key benefits of the program include:

  • Earning a USC master’s degree jointly offered by the USC Rossier School of Education and the USC Viterbi School of Engineering.
  • Continuing to work full time while taking flexible, fully online courses.
  • Developing skills in programming, analytics and machine learning.
  • Applying learning science to improve engagement and equity.
  • Building a professional network spanning education, technology and data fields.

Earn your Master of Science in Data Science for Learning Applications online. Request more information now.

Career Opportunities

Graduates from our program will be able to pursue various career pathways at the intersection of education, technology, and analytics, including:

  • Learning analytics specialist
  • Data analyst or LMS analyst
  • Educational technology consultant
  • Instructional designer (analytics focus)
  • Performance and learning analyst
  • Training and development manager

Program Curriculum

The DSLA program offers an interdisciplinary curriculum integrating data science and learning theory.

Students will:

  • Apply learning science and motivation principles to instructional design.
  • Select and implement data science methods to analyze performance and engagement.
  • Design evaluation strategies using analytics to measure instructional impact and promote equity.

The program culminates in a Capstone Project where students design a data-informed learning solution that demonstrates mastery of theory, research, and practice.