Information Course Schedule summer 2020

Lower-Division

Foundations of data science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks. It delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership. Also listed as Computer Science C8 and Statistics C8.

Section 111
MoWe 11:00 am - 1:00 pm — Internet/Online
Section 112
MoWe 1:00 pm - 3:00 pm — Internet/Online
Section 113
MoWe 3:00 pm - 5:00 pm — Internet/Online
Section 114
MoWe 5:00 pm - 7:00 pm — Internet/Online
Section 115
MoWe 1:00 pm - 3:00 pm — Internet/Online

A fast-paced introduction to the Python programming language geared toward students of data science. The course introduces a range of Python objects and control structures, then builds on these with classes on object-oriented programming. The last section of the course is devoted to Python’s system of packages for data analysis. Students will gain experience in different styles of programming, including scripting, object-oriented design, test-driven design, and functional programming. Aside from Python, the course also covers use of the command line, coding and presentation with Jupyter notebooks, and source control with Git and GitHub. This is an online course; students will attend regular live online sessions as well as reviewing recorded material.

This class is online and features required, weekly, live classes that are conducted through our online platform. Classes are collaborative seminars driven by problem solving and discussion. Between weekly live classes, students will complete coursework on their own time. Coursework is designed to be immersive and dynamic, engaging students in materials that prepare them for classroom discussions. This content includes dynamic videos, interactive case studies, self-paced lectures, and collaborative activities that foster teamwork.

Section 1
Session B (Jun 8 - Aug 14)
Mo 12:15 pm - 2:15 pm, We 9:00 am - 10:00 am — Internet/Online
Instructor(s): Kay Ashaolu
This is an online course; students are REQUIRED TO ATTEND... more
This is an online course; students are REQUIRED TO ATTEND THE LIVE (SYNCHRONOUS) ONLINE SESSIONS as well as reviewing recorded (ASYNCHRONOUS) material. Time conflicts are NOT allowed for this class.
Section 2
Session B (Jun 8 - Aug 14)
Mo 2:15 pm - 4:15 pm, We 9:00 am - 10:00 am — Internet/Online
Instructor(s): Kay Ashaolu
This is an online course; students are REQUIRED TO ATTEND... more
This is an online course; students are REQUIRED TO ATTEND THE LIVE (SYNCHRONOUS) ONLINE SESSIONS as well as reviewing recorded (ASYNCHRONOUS) material. Time conflicts are NOT allowed for this class.