Greetings and Salutations
Welcome to CICS 397A! We are excited to have you enrolled for the coming semester, and we hope to create a learning environment where each individual feels recognized, supported, and celebrated. Please know that regardless of your background, age, race, ethnicity, geographical origin, citizenship status, language, sex, gender or gender identity,sexual orientation, disability, family status, religion, political views, military experience, socioeconomic status, or education, you are welcome in this class! Furthermore, the ideas and experiences that each one of you brings to our (virtual) classroom are crucial to our success. Thank you for being here.
Below you'll find details on the course organization, along with policies on conduct, grading, and communication. Please read it over in its entirety, and let us know if anything is unclear.
[ Last updated: 22 August 2020 ]
The goal of this course is to familiarize participants with some of the most commonly used data analytics techniques, including methods for reducing data to informative statistics, predictive modeling, and cluster analysis. Students in this course will learn and use the Python programming language, creating scripts from the ground up to collect, manipulate, and analyze data sets. We will learn to ask and answer questions from data, and will cover all phases of the analytics process, from basic data wrangling and transformation to communicating through visualization.
The course schedule can be found here.
Course PoliciesGeneral Code of Conduct
The course Code of Conduct can be found here. Learn it, know it, live it.
All assignments should be submitted through Gradescope. You may submit one assignment up to 3 days late without penalty. After that, any assignments submitted late will be subject to a 15% penalty per day (e.g., an assignment submitted 26 hours late will have its final score reduced by 30%). No assignments will be accepted more than 3 days late. You may request extensions due to serious and documented medical or family emergencies.Homework Bug Bounties
As unimagineable as it may seem, homework assignments may occasionally contain errors or bugs in the supplied code. The first person to identify an error or bug in the code and post about it to the class forum will receive a +5% bonus for their grade on that assigment. The first person to post an elegant fix to the problem will receive +1-10% bonus (depending on the difficulty of crafting the solution or workaround).Academic Honesty and Collaboration Policy
You are encouraged to discuss the programming projects with your peers, and may optionally partner with one other person to code/write up your solutions. Both students are expected to be equal contributors, and are responsible for writing, understanding, and/or testing your solution. For coding projects, I highly recommend pair programming.In addition, we follow the University's Academic Honesty Policy and Procedures. In particular, the following are prohibited:
All of the above is subject to change.