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 ºÚÁϲ»´òìÈ.

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

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.