STAT40800 Data Prog with Python (online)

Academic Year 2020/2021

In this module students will learn how to manipulate data and perform simple statistical calculations using Python. Students will learn how to use numPy and the Pandas library to load in, manipulate and analyse data. This module covers the structure of the language, how to deal with large data sets, produce plots, perform statistical modelling and access APIs to obtain data from the web.

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Curricular information is subject to change

Learning Outcomes:

By the end of the module, students should be able to:
- Manipulate and analyse large data sets using the Pandas library
- Create and interpret graphical representations of data
- Use the scikit-learn library to preform machine-learning tasks
- Obtain data over the web from APIs and analyse it using simple statistical methods

Student Effort Hours: 
Student Effort Type Hours
Specified Learning Activities

24

Autonomous Student Learning

75

Online Learning

24

Total

123

Approaches to Teaching and Learning:
Video lectures and practice problem sets with solutions posted to the VLE each week. Coding tasks with solutions will also be provided. 
Requirements, Exclusions and Recommendations
Learning Requirements:

Students should have completed an introductory level statistics course and have a general understanding of calculus.


Module Requisites and Incompatibles
Incompatibles:
COMP30760 - Data Science in Python - DS, COMP41680 - Data Science in Python, COMP47670 - Data Science in Python (MD)


 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Continuous Assessment: Weekly programming exercises Throughout the Trimester n/a Standard conversion grade scale 40% No

50

Project: Data analysis project Throughout the Trimester n/a Standard conversion grade scale 40% No

50


Carry forward of passed components
No
 
Resit In Terminal Exam
Spring Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment
• Online automated feedback

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