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Filter your search by area of study, location, and date range. Qualified pre-college students may also consider the undergraduate courses listed below.

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Results for: “Data Analytics Workshop”

Data Analytics Workshop - AS.110.100

Pre-College students June 24 - July 5 Online
1 Credit Status: Open Save this Course View Saved Courses

In this two-week pre-college program, students work in groups to construct and present a data analysis project which collects, organizes, cleanses, and visualizes a dataset of their choosing. Topics include exploratory data analysis, data visualization, probability distributions, data scraping and cleansing, the basics of hypothesis testing, and regression modeling. Students will primarily use Microsoft Excel. Programs like Octave (Matlab), and Octoparse, will also be introduced to help students learn the basics of data analytics. 

This self-paced program is primarily delivered asynchronously; however, your instructor may schedule live interactions as well. Please refer to your syllabus for these opportunities and for your important program deadlines.

Prerequisite: Precalculus. (There is no programming requisite required for this course.)

Required Text: There are no required textbooks for this program; all readings and resources will be made available to you throughout the program.

Duration
2 weeks
Area of Study
Department
Mathematics
Instructor
Zoll, Aaron
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

Data Analytics Workshop - AS.110.100

Pre-College students July 8 - July 19 Online
1 Credit Status: Open Save this Course View Saved Courses

In this two-week pre-college program, students work in groups to construct and present a data analysis project which collects, organizes, cleanses, and visualizes a dataset of their choosing. Topics include exploratory data analysis, data visualization, probability distributions, data scraping and cleansing, the basics of hypothesis testing, and regression modeling. Students will primarily use Microsoft Excel. Programs like Octave (Matlab), and Octoparse, will also be introduced to help students learn the basics of data analytics. 

This self-paced program is primarily delivered asynchronously; however, your instructor may schedule live interactions as well. Please refer to your syllabus for these opportunities and for your important program deadlines.

Prerequisite: Precalculus. (There is no programming requisite required for this course.)

Required Text: There are no required textbooks for this program; all readings and resources will be made available to you throughout the program.

Duration
2 weeks
Area of Study
Department
Mathematics
Instructor
Zoll, Aaron
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

Data Analytics Workshop - AS.110.100

Pre-College students July 22 - August 2 Online
1 Credit Status: Open Save this Course View Saved Courses

In this two-week pre-college program, students work in groups to construct and present a data analysis project which collects, organizes, cleanses, and visualizes a dataset of their choosing. Topics include exploratory data analysis, data visualization, probability distributions, data scraping and cleansing, the basics of hypothesis testing, and regression modeling. Students will primarily use Microsoft Excel. Programs like Octave (Matlab), and Octoparse, will also be introduced to help students learn the basics of data analytics. 

This self-paced program is primarily delivered asynchronously; however, your instructor may schedule live interactions as well. Please refer to your syllabus for these opportunities and for your important program deadlines.

Prerequisite: Precalculus. (There is no programming requisite required for this course.)

Required Text: There are no required textbooks for this program; all readings and resources will be made available to you throughout the program.

Duration
2 weeks
Area of Study
Department
Mathematics
Instructor
Zoll, Aaron
Class Schedule
Monday
Self-paced
Tuesday
Self-paced
Wednesday
Self-paced
Thursday
Self-paced
Friday
Self-paced

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