2nd Major in Data Science and Analytics
What Can This Second Major Do for You?
DSA enables you to:
- Turn Data into Insights
Companies are collecting more data than ever. The most successful ones are those that can extract value from it. As a result, data scientists and analysts are in high demand. - Learn Essential Data Skills in Industry-Relevant Languages
Gain hands-on experience in Python, R, and SQL. Learn how to query databases, build data pipelines, create interactive visualizations using JavaScript libraries, and more. - Explore Statistical Learning
Training and testing statistical models that describe and generalize datasets is a powerful tool. Learn how to apply statistical models and machine learning algorithms to generate predictions and uncover insights. - Sharpen Your Competitive Edge
Acquire in-demand data science and analytics skills, including big data and big compute technologies such as Apache Cassandra and Apache Spark. - Apply Your Skills in Real-World Projects
Develop your ability to communicate analysis results to stakeholders. Share your thought process using GitHub and GitHub Pages. Build a portfolio of projects to showcase in internship and job interviews. - Join a Vibrant Community
As a DSA Second Major student, you will be supported by the DSA Society at SMU, a network of peers passionate about data science.
Structure & Curriculum
To fulfil the requirements of the DSA major, students must complete the following:
Probability Theory and Applications (STAT201)
Statistical Inference for Data Science (DSA201)
Statistical Learning with R (DSA211) *
Data Analytics with R (DSA212)
Computational Thinking and Programming (COR-IS1704) **
* Statistical Learning with R is mutually exclusive with Statistical Programming, which is a compulsory Accounting Core course for BAcc students. BAcc students can therefore take Statistical Programming instead of Statistical Learning with R to fulfil the requirements.
** Computational Thinking and Programming is also a Core Curriculum course under the Capabilities (Modes of Thinking) basket. Students may not double count this course towards both the Core Curriculum and the DSA Second Major. Therefore, students must complete (a) an alternative course to fulfil the Capabilities (Modes of Thinking) basket requirement of the Core Curriculum or (b) an extra DSA Second Major Elective. As Computational Thinking and Programming is a compulsory Core Curriculum course under the Capabilities (Modes of Thinking) basket for BSc (CL), BSc (IS) and BSc (SE) students, these students are required to complete 5 CUs of DSA Second Major Electives instead of 4 CUs.
Choose any four courses in the Data Analysis (DA) List and Computing Technology (CT) List, with at least one course in each list.
DA List
Time Series Data Analysis (DSA301) or Economic Forecasting (ECON233)
Spatial Data Analysis – SMU-X (DSA303)
Panel Data Analysis (DSA305)
Big Data Analytics (DSA306) or Big Data Analytics with Spark (DSA307)
Applied Healthcare Analytics (ECON245)
Marketing Analytics (MKTG228) or Service and Operations Analytics (OPIM326) or Forecasting and Forensic Analytics (ACCT420)
SQL and NoSQL Databases (DSA308)
Machine Learning with Applications in Economics (DSA311)
Data Science with Python (DSA312)
CT List
Modeling and Data Analytics (COR1305) or Data Management (IS112) or Business Data Management (IS105)
Visual Analytics for Business Intelligence (IS428) or Geospatial Analytics and Applications (IS415)
Introduction to Artificial Intelligence (CS420)
Principles of Machine Learning (CS421) or Machine Learning and Applications (IS460)
Data Mining and Business Analytics (IS424) or Data Warehousing and Business Analytics (IS417)
Text Mining and Language Processing (IS450)
Reinforcement Learning in Portfolio Optimisation (QF210)
Related Materials
Alumni Testimonials
"Pursuing DSA as my second major was one of the best decisions for my career. The major is incredibly relevant to the industry, with teaching materials constantly updated to keep pace with evolving industry standards. What stood out to me the most was the professors’ ability to bridge the gap between theory and practice. Their hands-on approach made complex concepts practical and actionable, equipping me with skills that are immediately applicable in real-world scenarios. This major has truly prepared me to thrive in the fast-paced, data-driven world we live in today."
Chua Ting Lin Collin
BSc (Econ), second major in Data Science and Analytics, Class of 2023
Data Scientist, DBS
"DSA was pivotal in helping me secure 2 internships, 3 research assistantships, and my current role at Goldman Sachs. The major's keys strengths are its focus on application alongside the theory and its vast selection of electives. Almost every module has a project component, helping you shape your interests and develop a portfolio for employers. Its flexibility lets you dive into interesting subfields including statistical models, algorithms, machine learning, or big data infrastructure. If you enjoy statistics and programming (and don't want to hyperspecialize in QF), this major's right for you."
Bharat Gangwani
BSc (Econ), second major in Data Science and Analytics, Class of 2024
Risk Engineer, Goldman Sachs
"The DSA Second Major equips students with important fundamental skills in statistics and programming through its core offerings. These skills form the foundation for a successful career within the data industry. Furthermore, the DSA programme provides students with the autonomy to personalise their course of study through a wide array of elective courses. The programme's flexibility allows students to personalise their learning journey and tailor their skillset to their specific career aspirations within the data domain, whether it be as a Data Analyst, Data Scientist or even a Data Engineer."
Xavier Hau Qian Rui
BSc (Econ), second major in Data Science and Analytics, Class of 2023
Data Scientist, Ubisoft Singapore
"It's difficult to think of a field or role that doesn't require working with large amounts of data to drive decision making or achieve results. The DSA Second Major has honed my analytical mindset and equipped me with computational abilities which I have used across various roles in my career. What I like most about the curriculum are the projects which have helped me build my portfolio and allowed me to apply my learnings to tackle real world problems."
Bryan Lum Jin Yoong
BSc (Econ), second major in Data Science and Analytics, Class of 2022
AVP, Credit Underwriter, Citi Private Bank
