Skip to content

The DSA major develops a practical mix of technical skills and communication skills to thrive in an increasingly data-oriented world

DSA statistical analysis & visualization platforms
DSA students will learn how to leverage the latest data science & analytics platforms for statistical analysis and visualization
Digital Service Innovation
DSA students will learn how digital services and Artificial Intelligence are transforming the economy
Geospatial Visualization
DSA students will learn how to represent spatial relationships
Complex Networks
DSA students will learn how to represent and visualize systems featuring complex interactions

Why choose the DATA SCIENCE & ANALYTICS (DSA) major? 

The data science and analytics (DSA) major addresses the increasing demand for adept data analysts by combining coursework in applied data science with coursework in economics and cognitive, political and management science — areas where real-world problem solving increasingly relies on data-driven analysis to inform decision-making.

Data are generated everywhere, increasingly enveloping human experience by mediating our interactions with the natural, social and built world. Yet data often require refinement, reformatting and critical analysis before they can become usable information. To make data-informed decisions, such as raising or lowering taxes, hiring or dismissing an employee or investing or divesting in a business sector, for example, people need understand how to appropriately and ethically harness, classify and analyze data, along with methods for extracting actionable insights and effectively communicating results.

The DSA major provides students with courses across the entire data analytics pipeline with series of refinements including identifying and integrating appropriate data; understanding the strengths and weaknesses of data and its sources; extracting valuable insights by way of advanced visualization and inferential methods; and strategically communicating recommendations based upon analysis to maximally inspire persons and groups to take action.

Download a printable PDF flyer

A typical student's course schedule in first-year and second-year:

Fall / Y1

Math 011: Calculus 1

DSA 001: Foundations of DSA

DSA 002: Thinking like a progammer

SPARK General Educ.

Spring / Y1

Math 012: Calculus II

ECON 001: Intro Econ.

/ or /

COGS 001: Intro Cog. Sci.

WRI 010: College Reading and Composition

PHIL 002: Intro to Ethics

Fall / Y2

MIST 050: Intro to Entrepreneurship

GE or Elective

GE or Elective

GE or Elective

Spring / Y2

ECON 010: Statistical Inference

GE or Elective

GE or Elective

GE or Elective

Welcome to Data Science & Analytics @ UC Merced


Required Courses

  • DSA 001: Foundations of DSA
  • DSA 002: Thinking like a programmer
  • MIST 050: Intro to Entrepreneurship -or- MIST 070: Creativity & Innovation
  • ECON 010: Statistical Inference
  • ECON 110: Econometrics
  • MIST 130: Statistical Data Analysis in R for Decision Support -or- MIST 134: Methods of Data Science & Network Science
  • DSA 101: Machine Learning & Natural Langauge Processing -or- DSA 102: Interactive Data Vis. -or- MIST 135: Technical Commun. & Vis.
  • PHIL 123: Technology Ethics
  • DSA 120/121: Senior Year Capstone

Elective Courses

By strategically selecting coursework electives, students obtain an EMPHASIS TRACK that appears on the diploma and identifies your DSA specialization:

  • Business Analytics
  • Policy Analytics
  • Environmental and Sustainability Analytics
  • Behavioral Modeling Analytics
  • Default: Custom Emphasis Track 

DSA electives are offered by faculty from 4 different departments:

Cognitive and Information Sciences

  • COGS 103: Intro to Neural Networks in Cognitive Science
  • COGS 104: Complex Adaptive Systems
  • COGS 125: Intro to Artificial Intelligence
  • COGS 122: Modeling Social Behavior
  • COGS 128: Cognitive Engineering
  • COGS 170: Judgement and Decision Making


  • ECON 001: Introduction to Economics
  • ECON 120: Economics of the Environment and Public Policy
  • ECON 153: Judgement and Decision Making
  • ECON 171: Advanced Econometrics

Management of Complex Systems

  • MIST 118: Climate Change: Science & Solutions
  • MIST 132: Geographic Information Systems Analysis in Management
  • MIST 131: Data Governance for Analytics Projects
  • MIST 138: Systematic Financial Trading & Analysis
  • MIST 175: Information Systems for Management


Political Science

  • POLI 112: Public Policy: Analysis, Strategy and Impact
  • POLI 120: Voting Behavior, Campaigns and Elections
  • POLI 170: Theoretical Models of Politics
  • POLI 174: Data Science and Government Affairs
  • POLI 175: Advanced Analysis of Political Data