Introduction to Data Science
Gr. 9-12
This introductory course develops computational thinking and tools necessary to answer questions that arise from large-scale datasets. This course emphasizes an end-to-end approach to data science, introducing programming techniques in Python that cover data processing, modeling and analysis.
First, how can data be extracted that describes real-world phenomenon? This part of the course includes data collection, processing, cleaning (“munging”) and dealing with formatted and semi-formatted data (e.g., json). Second, how can data be modeled and used to make predictions? This includes methods in regression and classification, and experimental design. And third, how can the results of this analysis be understood and reasoned? This includes topics in visualization and methods for hypothesis testing and validation. The course involves hands-on analysis of a variety of real-world datasets, including economic data, document collections, geographical data and social networks. The class includes work on a real-world case study utilizing data and based on student interests.
This course can be applied to the Data Science Certificate Track.
Notes
Once your child is registered, there are no refunds or transfers. Refunds are made only for classes canceled by CFK&T.
Discount: If registering for six or more classes, please use discount code CFK6PLUS to receive 15% off. This does not include before or after care.
Date:
Delivery Method: Blended
In-person
Date: 2 wks, Mon-Fri, June 17-28
Time: 9am-1:30pm CT
Location: UWM Merrill Hall, 2512 East Hartford Ave, Milwaukee, WI
Course-Paced Online
Available:
Platform: Canvas
Instructor: TBA
Fee: $299
Enrollment Limit: 15
Program Number: 8410-132
Note: Gr. 9-12, Session I
Once your child is registered, there are no refunds or transfers. Refunds are made only for classes canceled by CFK&T.
Discount: If registering for six or more classes, please use discount code CFK6PLUS to receive 15% off. Does not include before or after care.
Note: There is a 30-minute, supervised lunch break every day. Please make sure students bring a bagged lunch.
Registration Deadline: June 8, 2024