Data Science, Data Engineering Concentration, MS

Print Degree Planner (opens a new window) |

The MS in Data Science and Data Engineering concentration is dedicated to fostering the development of highly skilled data scientists, engineers, and MLOps professionals, equipped with a comprehensive theoretical and technical understanding of statistical analysis, machine learning, and systems to deploy and maintain a life cycle of data and models. Our program curriculum is designed to offer a well-rounded education in data science, supplemented by specialized courses in data science, data engineering and MLOps. This also empowers our students to leverage modern data infrastructures and platforms to tackle real-world challenges and achieve success in their professional endeavors.

Program Learning Outcomes

Students will:

Possess a theoretical understanding of classical statistical models (e.g., generalized linear models, linear time series models, etc.), as well as the ability to apply those models effectively
Possess a theoretical understanding of machine learning techniques (e.g., random forests, neural networks, naive Bayes, k-means, etc.), as well as the ability to apply those techniques effectively to data and maintain its life cycle
Effectively use modern programming languages (e.g., R, Python, SQL, etc.), technologies (Cloud Computing, AWS, GCP, etc.), and Distributed Systems (Hive, Spark, Hadoop, Airflow, etc.) to scrape, clean, organize, query, summarize, visualize, and model large volumes and varieties of data
Prepared for careers as data scientists and engineers by solving real-world, data-driven business problems with other data scientists and engineers in an ethical and responsible way
Develop professional communication skills (e.g., presentations, interviews, email etiquette, etc.), and begin integrating with the Bay Area data science community

Major Requirements (43 units)

Linear Algebra Exam

All students must pass a linear algebra exam by the beginning of the Fall semester in order to demonstrate competency in this subject. Students have two attempts to pass this exam. Students are provided with ten hours of video resources as well as practice questions and TA support to aid them in their attempts.

Required Data Science Courses (35 units)

Complete the Following Seminars:

Required Data Engineering Concentration Courses (8 units)

10 Hours of Interview Skills

10 hours of required interview skills training to be completed outside of class time. Trainings to be provided by the Data Science program and may include but are not limited to: workshops, mock interviews, resume editing and guest lecturers.