Introduction to Data Science Academy| Course Description
The Introduction to Data Science Academy offers an inside look at the professional world of data science through the eyes of experts in the field. Through a combination of coding exercises, presentations from data science experts, and class discussions, you’ll be introduced to contemporary data science resources and best practices. You’ll have the opportunity to explore the processes of data collection and analysis, gain hands-on practice with statistical analysis and coding languages, and learn about the main elements of programming in R. By the end of the program, you’ll understand key concepts like how to wrangle data, how to visualize data, how to present your conclusions, and how to arrive at those conclusions.
Please note: A Mac- or Windows-based laptop is required to participate in this program. Chromebooks are not allowed.
How You’ll Benefit
Explore techniques for data collection, cleanup, analysis, and visualization
Learn the fundamentals of statistics
Take a tour of Microsoft Technology Centers
Hear from guest speakers, including Georgetown faculty and technology experts
Understand coding languages
Create a GitHub repository and learn how to fork and make pull requests
Program Format & Subject Areas*
As a student in the Introduction to Data Science Academy, you'll spend your day immersed in a blend of classroom lectures, field trips, hands-on activities, and group discussions. Throughout the course of the week, you'll have the opportunity to explore the following subject areas:
Identifying data sources
Basic statistical analysis techniques
Cleaning and analyzing data
Introduction to data visualization and how to create interactive visualizations
How data scientists collect data in a broad spectrum of fields
Presenting data analysis and interactive visualizations
The main elements of basic programming in R
Introduction to Data Science Academy| Schedule Description
7:00 a.m. – 9:00 a.m. Breakfast
9:00 a.m. – 10:30 a.m. Hands-on Coding, Data Wrangling, Data Analysis, Data Visualization, and Presenting Skills Workshops
10:30 a.m. – 12:30 p.m. Hear from a Data Scientist and a Subject Matter Expert
12:30 p.m. – 1:30 p.m. Lunch
1:30 p.m. – 5:00 p.m. Visit a campus place where data is collected
5:00 p.m. – 6:00 p.m. Brainstorm for personal projects
6:00 p.m. – 7:00 p.m. Dinner
7:00 p.m. – 9:00 p.m. Work on code, analysis, and visualization for final project to be presented
9:00 p.m. – 11:00 p.m. Student? activities and Residential Life ?supervision
Students are typically engaged in academic programming from 9:00 a.m. to 9:00 p.m. with free time and optional residential living activities until curfew. Students arrive and check-in on Sunday and depart on Saturday.
*How You’ll Benefit, Program Format & Subject Areas, and Sample Schedule are subject to change.