Eligibility Requirements
- Rising ninth through 12th graders.
- Students participating in Illinois Tech online summer programs must be at least 14 years old to participate.
- The program will take place online using the Zoom platform. In order for the program to be as interactive as possible, students are encouraged to use their webcam during the synchronous sessions. View our Zoom privacy policy.
Location
Online
Dates/Time
June 17–21 from 8:30 a.m.–11:30 a.m. CST
*There will be no programming scheduled on Juneteenth, which falls on Wednesday, June 19, 2024.
Cost
$350; a $100 deposit is due at the time of registration
Program Description
This program aims to introduce high school students to the fascinating world of data science and analysis, offering foundational skills that are essential for understanding and working with data. Students will embark on an exciting journey where they will learn to decipher the language of data and extract meaningful insights from it. This hands-on experience will empower them to play the role of a “data explorer,” unraveling the mysteries hidden within datasets.
Throughout the program, students will engage in interactive labs designed to take them through the entire data analysis process. Using tools employed by data scientists, they will gain practical experience in tasks such as data cleaning, exploration, and visualization. By the end of the course, students will have a solid grasp of the fundamental principles of data science and be equipped with valuable analytical skills.
The demand for individuals with data science expertise is rapidly growing across various industries, making these skills increasingly valuable. This course not only lays the groundwork for a potential future career in data science, but also nurtures a critical mindset that is essential for understanding and interpreting the data-driven world we live in.
Join us in this exciting exploration of data, where students will learn the basics of data science and develop a keen understanding of its real-world applications. The knowledge gained in this course will undoubtedly set the stage for further academic and professional pursuits in the dynamic field of data science.
Throughout this engaging course, participants will dive into hands-on labs designed to reinforce key concepts and foster practical skills. These labs are crammed to provide a dynamic learning experience within virtual environments, allowing students to apply their knowledge in a simulated, but realistic, sensing. Some of the exciting labs included in the curriculum are:
- 1. Data Exploration Lab
- Students will navigate through diverse datasets, learning to identify patterns, trends, and outliers.
- Hands-on experience with tools for basic statistical analysis to draw insights from raw data.
- 2. Data Cleaning Challenge
- Participants will tackle real-world scenarios of messy data and develop skills to clean and preprocess data effectively.
- Use of data cleaning tools and techniques employed by data scientists in the industry.
- 3. Visualization Workshop
- A lab focused on translating data into compelling visualizations.
- Students will create charts and graphs to effectively communicate their findings, mastering tools commonly used in the field.
- 4. Predictive Modeling Simulation
- Introduction to the concept of predictive modeling using simplified examples.
- Application of basic machine learning techniques to make predictions based on provided datasets.
- 5. Introduction to Python for Data Science
- A practical lab where students will get hands-on experience with Python, a programming language widely used in the data science community.
- Writing simple scripts to manipulate and analyze data.
- 6. Interactive Data Storytelling
- Students will cram a narrative around a dataset, honing their skills in presenting data-driven insights.
- Incorporation of storytelling techniques to make data more accessible and compelling.
These labs are designed to not only reinforce theoretical concepts, but also to provide students with practical skills that are directly applicable in the field of data science. By actively engaging with these hands-on activities, students will grasp the fundamental principles of data science and develop the confidence to apply these skills in real-world scenarios.
Example Activities
- Programming concepts
- Powerpoint presentation
- Capstone project
Instructor
Parth Kaushik, cloud data science engineer at Deloitte
Questions?
Questions about the application process? Email them to precollege@iit.edu.