Fall 2016
Professor: Dr. Eloi Puertas
Dates:
Monday : 17h - 19h
Friday: 15h - 17h
Location: B1 classroom.
Email: epuertas@ub.edu
Tutorial times: On demand.
Lab Instructor: TBA
Teaching Assistant: TBA
Some programming experience in Python
1) Learn about agile methodologies for software developing.
2) Learn about what it’s like to be a data scientist.
3) Learn about infrastructures for data science.
4) Learn about ethics and data privacy.
Software Development Methodologies
(Brief intro to Data Engineering)
The first 4 weeks I will teach the basic concepts about data science and agile methodologies to build up sufficient background and foundation.
After that, we will go through a Data Science project, following each step of the data science workflow. The project will be the same for all the class. The classes will be divided into two parts: (1) Review of previous material and introduction of any new material necessary to solve the current step in the project. (2) Work in team for solving and implement a solution for the current step in the project.
Finally, the last 4 weeks we will see fundamental aspects from Ethics and Data Privacy in the data sicence context.
| Weeks | Topic |
|---|---|
| 1 | Introduction to Data Science |
| 2 - 4 | Software Development Methodologies |
| 5 | Data Science Workflow: Breaking down a Data Science Problem |
| 6 | Data Science Workflow: Setting up Data Science Infrastructure |
| 7-8 | Data Science Workflow: Data Preparation |
| 9 | Data Science Workflow: Analysis |
| 10 | Data Science Workflow: Dissemination and Deployment |
| 11-14 | Ethics and data privacity |
| 50 % | In Class Project |
| 40 % | Final In Class Exam |
| 10 % | Attendance / Participation |
The in class project will be a typical datascience problem with real data. You will form teams and work together. The project starts on the end of October and the deadline will be in December. More details to come in October.
Most of my instruction will involve Python and Python Bindings.