Big data presents a big opportunity.

From marketing to accounting to biology, data analysis allows individuals to draw meaningful insights and devise solutions from complex and often disparate sources.

Emmanuel's minor in Data Analytics is designed to bring you into the already-arriving future where data-driven research and insights run nearly every facet of business and society. Across industries, data science practices are being integrated to power the next generation of workers, researchers, and leaders, with workplace roles changing fast and becoming more fluid—it's not just a role of the data analyst to provide insights anymore. Anyone from marketers to sales professionals in industries from retail and consumer goods to financial services and nonprofits are becoming more data savvy. Graduates with experience in data analytics will be sought after in any field where digital information is collected and analyzed to generate insights.

The Curriculum

View the 2023-2024 Academic Catalog to find course titles, numbers and descriptions.

Requirements for a minor in Data Analytics

  • IDDS1000 Digital Citizenship(SI)(SS)
  • IDDS1101 Introduction to Programming (QA)(QR)
  • IDDS2201 Data Analytics
  • IDDS2132 Practical Machine Learning
  • ART2132 Data Visualization(AI-A)(VCI)

Choose one elective:

  • BIOL3151 Exercise Physiology
  • CHEM2104 Analytical Chemistry
  • COMM2515 Research Methods for Communication & Media
  • COMM3708 Digital Culture and Social Media Promotion
  • IDDS2101 Programming II and Introduction to Computer Science 
  • MKTG3110 Marketing Research
  • PHIL1116 Ethics in Science (M) (ER)
  • PHIL2205 Ethics & Technology (ER) 
  • POLSC2701 Research Methods in Political Science (WI)
  • PSYCH2802 Methods & Statistics II (QA) (QR)
  • SOC2103 Qualitative Methods
  • SOC2104 Quantitative Methods (QR)
  • SOC4998 Community Action Research

Students minoring in Data Analytics will develop:

  1. Techniques for collecting, storing, cleaning, and processing data. 
  2. Mathematical and logical techniques for analyzing, modeling and exploring data.
  3. Hands-on experience interrogating large data sets.
  4. Experience developing and substantiating hypotheses using large data sets.
  5. Awareness of recent social, political and economic change due to the use of data-oriented technologies in nearly all facets of society.
  6. Understanding of how data science skills can be applid to their major discipline.
  7. Competency with R and JavaScript programming.
  8. Experience using machine learning and artifical intelligence to solve problems.

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