|Lecture||Sec 1: TF 9:50-10:55am. BK 010.
Sec 2: TF 1:35-2:40pm. RI 236.
|Practicum (DS2001)||CS Practicum 1. W 11:45am-1:25pm. WVH 212.
CS Practicum 2. W 2:50-4:30pm. WVH 210.
Science/Math Practicum 1. W 2:50-4:30pm. WVH 212.
Science/Math Practicum 2. W 4:40-6:20pm. WVH 212.
Social Science Practicum. W 11:45am-1:25pm. WVH 210.
Health Practicum. T 3:25-5:05pm. RY 128.
|Office Hours||W 12:45pm - 2:30pm
Introduces programming for data and information science through case studies in business, sports, education, social science, economics, and the natural world. Presents key concepts in programming, data structures, and data analysis through Python and Excel. Integrates the use of data analytics libraries and tools. Surveys techniques for acquiring and programmatically integrating data from different sources. Explains the data analytics pipeline and how to apply programming at each stage. Discusses the programmatic retrieval of data from application programming interfaces (APIs) and from databases. Introduces predictive analytics for forecasting and classification. Demonstrates the limitations of statistical techniques.
No prior programming experience is assumed; therefore, this course is suitable for students with little or no computer science background.
|Lectures||will focus on developing a conceptual understanding of programming and algorithmic thinking.|
|Homework||will apply conceptual knowledge via problems and Python implementation.|
|Practicum||will apply programming through case studies.|
|Project||will analyze & visualize a dataset programmatically.|
The final grade for this course will be weighted as follows.
At the conclusion of the class you will submit your Python code along with any datasets you used in the project. Additionally, you will present your work during the last week of class.
In my classroom, please ask questions, and answer questions! In computer science, we seldom get anything right on the first try. We see how an attempt turned out, and we try again. I like our classroom to reflect that approach as well; so please answer a question that's been posed, even if you're not sure of the answer.
To create and preserve a classroom atmosphere that optimizes teaching and learning, all participants share a responsibility in creating a civil and non-disruptive forum for the discussion of ideas.
Students are expected to conduct themselves at all times in a manner that does not disrupt teaching or learning. Your comments to others should be constructive and free from harassing statements.
When you come to class, I ask that you be fully present. No phones are permitted in the classroom. If you use a laptop, use it only to take notes. Please be respectful of your fellow students and me by participating attentively and non-disruptively.