Brief introduction to the University of British Columbia's Master's of Data Science Program presented at the Cold Spring Harbor Biological Data Science Meeting (Oct 2016)

1. http://masterdatascience.science.ubc.ca/
• Joint venture between the Departments of Statistics & Computer Science
at the University of British Columbia (Vancouver, Canada )
• First cohort started Sept. 2016
• Teaching Data science with modern practices & methods:

2. (I) 2 weeks
DSCI 511:
Programming
for Data Science
DSCI 521:
Computing
Platforms for
Data Science
(II) 4 weeks
DSCI 522: Data
Science Workflows
DSCI 523:
Data Wrangling
DSCI 512:
Algorithms and
Data Structures
DSCI 551:
Exploratory Data
Analysis for Data
Science
(III) 2 weeks
DSCI 513:
Databases and
Data Retrieval
DSCI 552:
Statistical
Inference and
Computation I
(IV) 4 weeks
DSCI 531:
Data Visualization
I
DSCI 524:
Collaborative
Software
Development
DSCI 553:
Statistical
Inference and
Computation II
DSCI 561:
Regression I
(V) 4 weeks
DSCI 525: Web
and Cloud
Computing
DSCI 542:
Communication
and
Argumentation
DSCI 562:
Regression II
DSCI 571:
Supervised
Learning I
(VI) 5 weeks
(4 weeks + midterm break)
DSCI 541:
Privacy, Ethics,
and Security
DSCI 563:
Unsupervised
Learning
DSCI 572:
Supervised
Learning II
DSCI 573:
Feature and
Model Selection
(VIII) 8 weeks
DSCI 591:
Capstone Project
(VII) 4 weeks
DSCI 532:
Data
Visualization II
DSCI 554:
Experimentation
and Causal
Inference
DSCI 574:
Spatial and
Temporal
Models
DSCI 575:
Advanced
Machine
Learning
10 month
MDS
Program
Each course:
• 8 lectures
• 4 hands-on labs
• assessed via 2 quizzes
& 4 assignments
Student support per course:
• Instructor
• Teaching Fellow
• Teaching Assistant
Capstone project:
• 2 months long
• groups of ~4 students
• opportunities to work
with partners in academia, not-for-profit
& industry

3. Public course descriptions and learning objectives:
https://ubc-mds.github.io/descriptions/