Data Science: Artificial Intelligence (AI) and Machine Learning

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Using Google Cloud based Colaboratory

Imagine that you are the Chief Data Scientist of an online movie store. Your task is to recommend movies for your customers movies to watch based on collected rating data from other users. This task is similar to what Amazon data scientists do behind the scenes at IMDb, the world's most popular and authoritative source for all things cinema. IMDb uses components of data science and uses data rating to recommend movies to users. So, what are you going to do to drive revenue for an online movie enterprise?

The scenario above is just one example of the various ways in which data science is becoming increasingly important in today's society. With the evolution of technology in the 21st century, the need for data scientists is growing at a fast rate. It can be readily applied to a vast array of fields ranging from business to social sciences to the laboratory sciences. Data science combines several disciplines, including statistics, data analysis, machine learning, and computer science.

Our Pre-College Data Science course will offer a fast lane through techniques for recommender systems used in the field of Data Science. Students will learn how to program using Python, review basic linear algebra and probability, build models that give recommendations based on given rating inputs, and learn how to utilize selected recommender system techniques. After completing the course, students will be able to understand and utilize the same algorithms that have been applied for recommending various products in artificial intelligence (AI) and the business world.

Tentative Schedule:

  • Monday: Python Programming Fundamentals
  • Tuesday: Python Programming with Linear Algebra and Probability
  • Wednesday and Thursday: Recommender Systems
  • Friday: Students complete their projects and showcase work

There will be many hands-on activities, so you need to bring a laptop and charger. You should know how to use a web browser to access websites, download files, simple file and directory manipulation before attending the course

At a Glance:


Supplemental Lab Fee: $40.00

Course Prerequisites:

  • Some exposure to linear algebra (basic knowledge about vectors, matrices, and operations) and Python programming will be helpful in taking this course but is not necessary. 

Sessions Offered:

  • Session 1: July 7 - July 13

Location: UConn Storrs Campus

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UConn Pre-College Summer: Data Science
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Faculty:

  • Cuong Do, PhD, Director of the Data Science Graduate Programs, UConn Department of Mathematics
  • Tingting Huan, PhD, Senior Data Scientist, Advanced Analytics, Plymouth Rock Assurance Corporation
  • Haiyang Kong, Doctoral Student, UConn Department of Economics

 

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