Data science in python (md)  

The key objectives of this module are 1) to provide students with an initial crash course in Python programming; 2) to familiarise students with a range of key topics in the emerging field of Data Science through the medium of Python. Students will start by exploring methods for collecting, storing, filtering, and analysing datasets. From there, the module will introduce core concepts from numerical computing, statistics, and machine learning, and demonstrate how these can be applied in practice using popular open source packages and tools. Additional topics that will be covered include data visualisation and working with textual data. This module has a strong practical programming focus and students will be expected to complete two detailed coursework assignments, each involving implementing a Python solution to a data analytics task. COMP47670 requires a reasonable level of mathematical ability, and students should have prior programming experience (but not necessarily in Python). This is a Mixed Delivery module with online lectures and face to face practicals/tutorials Learning Outcomes: On completion of this module, students will be able to: 1) Program competently using Python and be familiar with a range of Python packages for data science; 2) Collect, pre-process and filter datasets; 3) Apply and evaluate machine learning algorithms in Python; 4) Visualise and interpret the results of data analysis procedures..
Blended
English
Data science in python (md)
English

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or HaDEA. Neither the European Union nor the granting authority can be held responsible for them. The statements made herein do not necessarily have the consent or agreement of the ASTRAIOS Consortium. These represent the opinion and findings of the author(s).