About DSA150

Course Description: Data Science is the study of the tools and processes used to extract knowledge from data. This course introduces students to this important, interdisciplinary field with applications in business, communication, healthcare, etc. Students learn the basics of data collection, data organization, packaging, and delivery. Simple algorithms and data mining techniques are introduced.

Required Texts and Materials: ENTER TEXT HERE

Contact Details

Stephanie Rosenthal
Chatham University
Falk 116C
Office Hours: by appointment

s.rosenthal@chatham.edu

Assignments

In this class, we will learn the data science process through experiencing it twice. First, you'll work through four assignments to create one data analytic. Then, you'll create your own analytic of your choice in your final project. All submitted code should be properly commented and should run immediately when opened. Include readme.txt files for how I should run your code.

Assignment 1

Data Collection: Out on 1/19, Due 1/26

Assignment 2

Exploratory Data Analysis and Cleaning: Out on 1/26, Due 2/2

Assignment 3

Data Visualization: Out 2/2, Due 2/16

Assignment 4

Data Analysis: Out 2/16, Due 3/2

Project

Out 3/12, Due 4/16

Schedule

Monday

Wednesday

Friday

1/1: No Class

1/3: What is Data Science?

1/5: Applications of Data Science

1/8: Review Probability

1/10: Research Methods

1/12: Data Science Process

1/15: No Class

1/17: Downloading Data

1/19: Daemons
Assignment 1 out

1/22: Data Summarization

1/24: Data Conversion

1/26: Data Cleaning 1
Assignment 1 due
Assignment 2 out

1/29: Data Cleaning 2

1/31: Parsing

2/2: Combining Features
Assignment 2 due
Assignment 3 out

2/5: Principles of Viz

2/7: Counts and Histograms

2/9: Tables, Charts, Graphs

2/12: Bayes Rule

2/14: Bayes and Analytics

2/16: Python SciKit-Learn
Assignment 3 due
Assignment 4 out

2/19: No Class

2/21: Machine Learning Classification

2/23: Machine Learning Regression

2/26: More Classification

2/28: More Classification

3/2: More Regression
Assignment 4 due
Project out

3/5: Spring Break

3/7: Spring Break

3/9: Spring Break

3/12: Neural Networks

3/14: Graphs

3/16: Recommender Systems
Proposal due

3/19: Boosting

3/21: Clustering

3/23: Big Data

3/26: Artificial Intelligence

3/28: Artificial Intelligence

3/30: Work in Class
Midpoint due

4/2: Security

4/4: Ethics

4/6: Work in Class

4/9: Speaker

4/11: Speaker

4/13: Final Exam Review

4/16: Presentations

4/18: Presentations

4/20: Presentations

Final Exam

Get In Touch.

Contact Details

Stephanie Rosenthal
Chatham University
Falk 116C
Office Hours: by appointment

s.rosenthal@chatham.edu