Introductory description

The objective of the module is to teach the students to develop a broad set of knowledge and skills for conducting data analytics using Python programming language.

Module web page

Module aims

Outline syllabus

This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.

1. Class and inheritance.
2. Basic structure of html webpage.
3. Data collection via web scraping.
4. Introduction to Pandas and Numpy.
5. Data cleaning and preparation.
6. Data wrangling: join, combine and reshape.
7. Introduction to Scikit-learn.
8. Data analysis with Python.
9. Introduction to machine learning with Keras and Tensorflow.
10. Data visualization with matplotlib.

Learning outcomes

By the end of the module, students should be able to:

• Demonstrate understanding of principles and processes to clean the data collected online.
• Demonstrate familiarity and understanding of the common models used in data analytics and their implementations using Python.
• Demonstrate familiarity and understanding of major Python libraries used in data science.
• Demonstrate capability to understand the problem and design and refine the solutions to the problem.
• Individually design and implement a functional computer programming solution written in Python, which can collect, analyse the data and present the result to solve business problems.

Indicative reading list

Reading lists can be found in Talis

Subject specific skills

Develop Python script to scrape data publicly available online.
Develop Python script to visualize analysis results.
Develop Python script to analyze the data.

Transferable skills

Numeracy and IT Skills.