Class Description

The workshop will focus on knowledge extraction and discovery from data, using statistical tools and machine learning algorithms. The students will be required to design and implement such systems and present their results in class.

Meeting Schedule

# Date Class Details Lecturer Files
1 07/03/2018 Introduction: Intro to data science, project details, important Dates Daniel Deutch Slides
2 14/03/2018 Hands-On Data Science in Python : iPython,Jupyter Notebook, Numpy, Scipy, Scikit-Learn, Pandas Amit Somech Slides
Material (Notebook, data files)
3 11/04/2018 Student Presentations #1: 5 minutes, 5 slides - Dataset description and initial analysis, project problem formulation
4 16/05/2018 Student Presentations #2: 5 minutes, 5 slides - Presentation of initials results
5 14/06/2018 Final Project presentations (Thursday, 5-8PM): Final presentations: Problem, model, techniques, results
6 20/07/2018 Projects Submission Deadline

Notifications

Date Notification
07/03/2018 Final project guidelines: here (PDF)
07/03/2018 Final project (empty) grading sheet: here (PDF)

Course Grading

Resources

Resource URL
A list of tutorials collected by Kaggle https://www.kaggle.com/wiki/Tutorials
The official Kaggel DIY tutorial in Excel, Python and R https://www.kaggle.com/c/titanic
World Data Bank http://datacatalog.worldbank.org
A github account collected many resources regrding data science https://github.com/justmarkham/DAT4/blob/master/resources.md