Advanced Programming for Data Science
Objectives
This course aims the student to start, develop, maintain, collaborate, and deliver a small to medium analytics project as if it were a corporate environment.
General characterization
Code
2612
Credits
3.5
Responsible teacher
Luís Manuel Rodrigues Guimarãis
Hours
Weekly - Available soon
Total - Available soon
Teaching language
English
Prerequisites
n/a
Bibliography
The replication crisis
Slides and tutorials to complement following documentation of libraries and frameworks:
Pep8
Flake8
Sphinx
Git
Python Testing : pytest .
Pip
Conda
Virtualenv
Data Lifecycle Management
Time series analysis (Class Notebooks)
Apache Spark
Teaching method
Students are required to bring their laptops for classes. Lectures are to be the main conduit of information. The topics will be addressed with practical examples and demos. Class materials will be executed in Jupyter notebooks when possible. It is highly recommend students install Anaconda: https://www.anaconda.com/products/individual Due to a strong code developmental component in the Unit, command line interfacing (CLI) will be required
Evaluation method
Class participation through 3 quizzes (20%)
Group project (30%)
Final exam (50%)
Subject matter
Knowledge and Understanding: Programming concepts
Reliability
Resilience
Durability
Scale