This course is intended to provide an introduction into the field of Data Science. Students will develop skills in appropriate technology and basic statistical methods by completing hands-on projects focused on real-world data and addresses the social consequences of data analysis and application.
|Bhavana Burell||Fort Valley State Universityemail@example.com|
|David Cook||Kennesaw State Universityfirstname.lastname@example.org|
|Vijay Kunwar||Albany State Universityemail@example.com|
|Alison Montanye||University of North Georgiafirstname.lastname@example.org|
|Nicolas Perez||Georgia Institute of Technologyemail@example.com|
|Edward Redmond||University of North Georgiafirstname.lastname@example.org|
|Lila Roberts||Clayton State Universityemail@example.com|
|Ngoc Vo||University of West Georgiafirstname.lastname@example.org|
|Fang Xie||East Georgia State Collegeemail@example.com|
|Yinning Zhang||University of West Georgiafirstname.lastname@example.org|
After completing this course, you will be able to:
Additional optional learning objectives:
Your final grade will be based on the following breakdown. Please note that each instructor may choose to make modifications.
In this course you will be using Python programing language. You will need to download Anaconda and Jupyter Notebook in order to use this program. There is more information about this in Unit 1 of the course.
We also recommend (not require) the use of a TI-83 calculator in this course. There are several online options (TI emulators) available for download (with free trial) if you do not have an actual calculator.