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Summer 2022 Pre-College Prog: Big Data, Machine Learning and Applied Analytics PS0101 section 004
Big Data, Machine Learning, and their Re
Big Data, Machine Learnin

Call Number 10905
Day & Time
Location
MTWRF 9:10am-11:00am
601 Sherman Fairchild Life Sciences Building
Day & Time
Location
MTWRF 1:10pm-3:00pm
601 Sherman Fairchild Life Sciences Building
Points 0
Grading Mode Ungraded
Approvals Required None
Instructor Harrison S Groll
Type LECTURE
Method of Instruction In-Person
Course Description The exponential growth of data, advances in cloud computing, and machine learning have transformed every industry from retail and banking to healthcare and education. This introductory-level course enables participants to navigate the new reality of the “data economy,” in which data is the “the new oil”—a ubiquitous and invaluable asset. We focus on the strategic use of data and innovative technologies to derive actionable business insights. Participants develop a strong foundation in data-driven thinking for solving real-world problems. They are introduced to a variety of popular technologies for data analytics and gain a familiarity with programming in R, a software environment for statistical computing and graphics. Much of the in-class work involves working with R. Students learn how to import, export, manipulate, transform, and visualize data; use statistical summaries; and run and evaluate machine learning models. From the start of the course participants are immersed in the world of data: they are introduced to the concepts of big data, artificial intelligence, the internet of things, cloud computing, and data ethics in the context of real-world business scenarios. Through hands-on experience and practice they study data harvesting and exploration, as well as the basics of data visualization. After they get comfortable with data manipulation and transformation, they gain familiarity with statistical frameworks and methods designed to extract practical insights from data. Participants learn and implement common machine-learning techniques and develop and evaluate analytical solutions. Toward the conclusion of the course, students work in groups on a final project and presentation, thereby (a) solidify their newly acquired analytical and programming skills and (b) practicing storytelling with data. Participants should expect a dynamic and interactive environment: hands-on exercises, teamwork, continuous in-class dialogue, demonstrations, and interactive presentations. The course features real-world applications of data analytics across industries and challenges students to think in terms of the business value of data and machine learning.
Web Site Vergil
Subterm 07/19-08/05 (L)
Department Pre-College Programs (SHSP)
Enrollment 22 students (24 max) as of 5:21PM Thursday, September 29, 2022
Subject Pre-College Prog: Big Data, Machine Learning and Applied Analytics
Number PS0101
Section 004
Division Professional Studies & Special Pgrms: Pre-College Programs
Open To Pre-College Programs, Professional Studies
Campus Morningside
Section key 20222BIGD0101N004

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SIS update 09/29/22 17:21    web update 09/29/22 20:37