Syllabus

Course Description

• Provide an introduction to data science. Cover a wide range of topics with the goal of providing an overview of the use of data in different fields.
• Provide hands-on practice with basic tools and methods of data analysis.
• Prepare students to use data in their field of study and in their work.

 

Learning Outcomes

1. discuss how data is used in a wide range of fields including those that are traditional liberal arts ones.
2. identify and apply appropriate data analysis techniques in Python to a problem
   1. identify and convert relevant information to a form that can be used in analysis
   2. calculate probability of basic events in real data
   3. calculate descriptive statistics on data from a variety of disciplines
   4. perform basic classification and clustering of datasets.
3. effectively communicate the results of data analysis
   1. demonstrate effective use of data visualization to support an argument
   2. demonstrate the ability to present data analysis results both in written and oral communication.
4. critically evaluate the results of data analysis
   1. identify the hidden assumptions of research involving data analysis.
   2. calculate and interpret the accuracy of analysis techniques.

 

Requirements

Laptops

I am assuming that nearly everyone has a laptop. You will be working with your laptop during a large percentage of our class. It doesn’t matter if your laptop runs Microsoft Windows, is a Mac, or an Ubuntu machine.

Account on Datacamp

You will need an account (free) on Datacamp. Here is a registration link (please use your umw.edu email address)

 

Grading

The rough description:  You do stuff, you get points (XP).  As you gain XP you move up in levels. The level you are at the end of the semester determines your final grade.

 

Grading is based on a method developed by Professor Lee Sheldon at Indiana University. It is based on obtaining experience points (XP). The number of XP determines what level you are at. You start the class at Level Zero and with 0 XP. The level you obtain at the end of the semester determines your final grade. Here is the chart:

 

There is a total of at least 110,000 points.

Here is how you earn points:

Earn DataCamp XP: 38,000xp

As you work through the DataCamp Courses you earn XP.

Complete a DataCamp Course – 7,000xp

When you complete a DataCamp course by the deadline you earn 1,200xp. Completing after the deadline is worth 1,000xp 

DataCamp Practice Your Skills  10,000xp

After you complete each DataCamp course, you have the opportunity to practice the skills you learned by coding 5 short examples. Each practice session is worth 250xp and you can repeat these practice sessions.

Labs – 48,000xp

After each DataCamp course there is an associated lab that may be partner based or team based. There are 8 labs and each is worth 6,000xp.

random in-class challenges  – ~5,000xp

Throughout the semester the instructor may present very short in-class challenges.

Code of Conduct

Accommodations for students with special needs

Any student with a documented disability may receive a special accommodation to complete any requirements of this course. If you are have a disability or believe you have one you may wish to self-identify. You may do so by providing documentation to the Office of Disability Services located in Room 203 of George Washington Hall (Phone: Voice 540-654-1266, Fax: 540-654-1163). Appropriate accommodations may then be provided for you. If you have a condition that may affect your ability to exit the premises in an emergency or that may cause an emergency during class, you are encouraged to discuss this in confidence with me and/or anyone at the Office of Disability Services. This office can also answer any questions you have about the Americans with Disabilities Act (ADA).

Academic Integrity

I assume you are an ethical student and a person with integrity. I expect that you will follow the university honor code (see http://rosemary.umw.edu/CSHonorCode.html). Please use common sense and ask yourself what would a person with integrity do?

Class participation

I expect students to attend classes regularly. Since you will be spending the majority of class time working on projects, if you miss a class you will miss the opportunity to earn XP. That said, attendance is not taken and no XP will be awarded based directly on attendance.  If you are going to miss a class, please be courteous and inform me and your teammates.

General Education Student Learning Outcomes

• Students will demonstrate an ability to interpret quantitative/symbolic information..
• Students will have the ability to convert relevant information into various mathematical/analytical forms.
• Students will be able to apply analytical techniques or rules to solve problems in a variety of contexts.
• Students will gain an appreciation for how analytical techniques or rules are used to address real-world problems across multiple disciplines