Big Data Summer Camp

Big Data Summer Camp – Data Science Academy

Details & Requirements

Applicants must begin their sophomore year in high school in the Fall of the year they’re applying, and own a laptop they can bring every day.

Sessions Schedule (Remote Instruction):
Session 1: June 15 – June 19, 2020
Session 2: July 27 – July 31, 2020
Advanced: August 3 – August 7, 2020
Monday-Friday, 9:00am – 3:00pm

Pricing:
Reduced to $995

Testimonials

This camp is extremely helpful in providing great information on data science as a career. It supplies hands on activities through a very understandable program, which gives a strong base to start off in the vast world of data science. Overall, this camp is a great experience, and gives support for people who want to pursue data science.
— Chris, Sophomore

 

The camp was so good and so exciting. It gave me a lot of information about my career and was a useful camp.
— Meron, Junior

 

Being a part of the camp made me feel like a college student. I was independent to go wherever and be responsible. I enjoyed the teaching that our instructor provided. I will recommend this to anyone who loves computer science.
— Prithvi, Senior

Big Data Summer Camp for High School Students

Our 2020 Summer Camps have ended. Please check back or subscribe to Enrich Updates for information on 2021 Summer Camps.

Hands-on Project-Based Summer Camps

UC San Diego Qualcomm Institute’s Big Data Summer Camps provide aspiring young data scientists an immersive educational experience using cutting-edge approaches to Big Data. These pre-college summer camps are designed for students with interests in data analytics and visualization, artificial intelligence and machine learning, and how these fields and approaches assist in discovering and evaluating predictive models. The summer camps are each a week long and will introduce participants to the use of data and tools related to Big Data ecosystem. Even in an online format, the Big Data Summer Camps remain hands-on and project-based.

Session 1 & Session 2. Students will learn the basic math, visualization and methods behind data science and will work on team projects with classmates using real life examples. Over the course of the week, the content will build in complexity and difficulty, and will include strategies for data visualization and model development and evaluation. No programming experience or knowledge is required. Additionally, invited guests from academia and industry will give presentations to expose the students to various data science application domains. Students can enroll in either Session 1 or Session 2.

Advanced Session. Advanced Session builds on the basics learned in the introductory sessions. Enrolling in Advanced Session requires concurrent enrollment in Session 1 or Session 2. Students who have taken Big Data Summer Camps in past years also qualify.

WEEK SCHEDULE FOR SESSION 1 & 2

MONDAY
9:00 AM – Welcome and Introduction
9:30 AM – Data Modeling in the Age of Big Data
10:00 AM – Data Science Industry Landscape: Who Does What?
11:00 AM – Intro to Big Data Concepts, Tools and Technologies
12:00 PM – Lunch Break
1:00 PM – Analytics Platform Introduction and Tutorial
2:00 PM – Hands-on Exercises Data Load and Manipulation

TUESDAY
9:00 AM – Intro to Basic Machine Learning Concepts and Methods
10:00 AM – Practical Approach to Data Science
10:30 AM – Hands-on Data Preparation and Cleaning
11:00 AM – Hands-on Practical Data Visualization
12:00 PM – Lunch Break
1:00 PM – Introduction to Basic Machine Learning Algorithms
2:00 PM – Basic Algorithms: K-Nearest Neighbor & Hands-on

WEDNESDAY
9:00 AM – Intro to Supervised Learning: Decision Trees and Regression Trees
10:00 AM – Decision Trees Hands-on
11:00 AM – Regression Trees Hands-on
12:00 PM – Lunch Break
1:00 PM – Market Basket Analysis and Recommendation Engines (Lecture + Hands-on)
2:00 PM – Industry Guest Speaker

THURSDAY
9:00 AM – Unsupervised Learning: Clustering Methods
10:00 AM – Hands-on Clustering
12:00 PM – Lunch Break
1:00 PM – Guest Speaker
2:00 PM – Model Evaluation and Validation

FRIDAY
9:00 AM – Hands-on Project: Small Group Team work on the Case Study and Discussion
(Choice of numerous data sets including Yelp, Twitter, Google, Instagram, Airlines, Bike Sharing, Sales, Foods, Health, etc.)
2:00 PM – Final Discussion, Overview and Conclusion

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