DSM020 - Dr Sean McGrath
Structure
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1. Data structures
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2. Reading and writing data on the filesystem
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3. Retrieving data from the web
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4. Retrieving data from databases using query languages
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5. Cleaning and restructuring data, part 1
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6. Cleaning and restructuring data, part 2
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7. Data plotting
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8. Version control systems
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9. Unit tests
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10. Data processing pipelines
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Assessments
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Project Proposal (CW1) ●
Finished project (CW2)
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Exploratory data ●
Comprehensive data
analysis analysis
30% of your grade 70% of your grade
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Purpose
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Get you coding
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Get you up to speed with the technologies
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Give you a taste of what it means to do your
own data science project - albeit small scale
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Module design
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Activity driven - you learn to code by writing
code
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Lots of opportunities for peer review - no such
thing as a ‘one size fits all’ solution
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Expressive with opportunities to be creative and
innovate
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Be aware
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This is an MSc course, we move quickly!
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This module is perhaps the broadest in terms of
scope. Lots of learning opportunities.
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Students produce some exceptional work on
this course. See pinned discussion posts for
examples from this cohort.
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Challenges
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If you have not used Python before, it might be an
initially steep learning curve for you.
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The activities are the main source of learning. This
requires you to build confidence in exploring data.
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We do a lot of reading. Python for Data Analysis, 2e
(2017): Data Wrangling with Pandas, Numpy, and
Ipython is a good place to start.
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Outcomes
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Our students are (mostly) very happy with the
outcomes of the course.
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There are lots of opportunities to build a repository of
learning - particularly with the coursework assignments.
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We learn a lot of skills, from how websites and
databases to work to examples of good coding practice.
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Consider
Distinction (70-79%)
An answer falling into the mark range 70 to 79% demonstrates:
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a capacity to develop a sophisticated and intelligent argument;
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clear evidence of wide and relevant reading, referencing and an engagement with the conceptual
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issues;
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original thinking and a willingness to take risks;
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a significant ability to plan, organise and execute independently a research project, coursework
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assignment or examination question;
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rigorous use and a sophisticated understanding of relevant source materials, balancing
appropriately between factual detail and key theoretical issues. Materials are evaluated directly
and their assumptions and arguments challenged and/or appraised;
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significant ability to analyse data critically;
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correct referencing.
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Welcome to UOL!
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Most students say that they really enjoy this course
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We see lots of exceptional work from students with
zero programming experience when they arrive
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The forums (peer discussion) tutor forums (academic
support) and the activities are the core components in
this course. Use them wisely!
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