Big Data, Machine Learning, and Applied Analytics

Level:
Open to students entering grades 11 or 12 or freshman year of college in the fall
Session:
II - July 16–August 2, 2019
Days & Time:
Monday–Friday, 9:10 –11:00 a.m. and 1:10–3:00 p.m.
Teacher(s):
TBD
Prerequisites:

Algebra 1, Algebra 2, and Geometry. Some background with statistics is recommended but not required.

Course Description

What is big data? What is machine learning? Participants in this course gain a hands-on understanding of these concepts, how they are shaping the world we live in, and how they can be applied to real-world business and social ventures.

The course focuses on the strategic use of data, through innovative technologies and strategies, to derive actionable business insights. Students gain a familiarity with fundamental data analytics concepts, learn techniques for harvesting big data, evaluate statistical models, and convert knowledge into action by effectively presenting data analytics in compelling narratives useful to organizations in decision-making.

In the process of designing and developing analytics solutions, students gain exposure to tools, technologies, and methodologies such as R, Tableau, MicroStrategy, augmented reality, and artificial intelligence.

In-class activities include lectures, small-group work, class discussions, guest speakers, and interactive case studies applying analytical concepts and methodologies.

Participants are required to bring laptops equipped with the Microsoft Office Suite.

Teacher(s)

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Specific course detail such as hours and instructors are subject to change at the discretion of the University. Not all instructors listed for a course teach all sections of that course.