Certificate in Applied Data Science

The certificate offers a set of required courses to ensure that students completing it have a good understanding of key areas of modern data science.

Overview

One of the required courses is a capstone course, which provides the students with the opportunity of applying in practical scenarios the knowledge gained in the other courses. The certificate also offers a set of elective courses that allow the students to apply data science in a particular domain.

Eligibility

This certificate is available to all undergraduate students at the University of Alberta.

Requirements

To be awarded the Certificate in Applied Data Science, students must complete the following:

Required courses:

  • INT D 491 - Data Science Capstone

3 credits from:

  • CMPUT 191 - Introduction to Data Science
  • CMPUT 195 - Introduction to Principles and Techniques of Data Science

3 credits from:

  • CMPUT 200 - Ethics of Data Science and Artificial Intelligence
  • NS 115 - Indigenous Peoples and Technoscience
  • PHIL 385 - Ethics and Artificial Intelligence

9 credits (3 courses) from any of the following subject areas

(note a minimum of 3 credits are required at the 300- or 400 level)

Computing Science

  • CMPUT 267 - Basics of Machine Learning
  • CMPUT 291 - Introduction to File and Database Management
  • CMPUT 328 - Visual Recognition
  • CMPUT 361 - Introduction to Information Retrieval
  • CMPUT 367 - Intermediate Machine Learning
  • CMPUT 461 - Introduction to Natural Language Processing
  • CMPUT 466 - Machine Learning

Biological Sciences

  • BIOIN 301 - Bioinformatics I
  • BIOIN 401 - Bioinformatics II
  • BIOL 330 - Introduction to Biological Data
  • BIOL 331 - Population Ecology
  • BIOL 332 - Community Ecology
  • BIOL 380 - Genetic Analysis of Populations
  • BIOL 430 - Statistical Design and Analysis in Biology
  • BIOL 471 - Landscape Ecology
  • IMIN 410 - Bioinformatics for Molecular Biologists
  • MA SC 475 - Applied Data Analysis in Marine Science

Earth and Atmospheric Sciences

  • EAS 221 - Introduction to Geographical Information Systems and Remote Sensing
  • EAS 351 - Environmental Applications of Geographical Information Systems
  • EAS 364 - Basin Resources and Subsurface Methods
  • EAS 372 - Weather Analysis and Forecasting

Physics

  • PHYS 234 - Introductory Computational Physics
  • PHYS 295 - Experimental Physics I
  • PHYS 420 - Computational Physics
  • GEOPH 426 - Signal Analysis in Geophysics
  • GEOPH 431
  • GEOPH 438 - Seismic Data Processing

Statistics

  • STAT 441 - Statistical Methods for Learning and Data Mining
  • STAT 471 - Probability I
  • STAT 479 - Time Series Analysis

Agricultural, Life and Environmental Sciences

  • AREC 313 - Statistical Analysis
  • REN R 201 - Introduction to Geomatic Techniques in Natural Resource Management
  • REN R 426 - Geographical Information Systems Applications in Renewable Resources
  • REN R 480 - Applied Statistics for Environmental Sciences

Business

  • FIN 440 - Commodities Analytics and Trading
  • MARK 312 - Marketing Analytics
  • OM 420 - Predictive Business Analytics
  • SEM 330 - Exploring Innovation and Entrepreneurship

Learn more about the above requirements, approved courses, and other necessary information »

Program Contact

For more information, please contact emailaddress@ualberta.ca

Get Started

Complete this link to enrolment form to get started with the Certificate in Applied Data Science.