Data science combines several disciplines, including statistics, data analysis, machine learning, and computer science. And, with the evolution of technology in the 21st century, the field of Data Science is growing at a fast rate.
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 Data Science course will offer a fast lane through some techniques for recommendation systems used in the field of Data Science. Students will learn how to program using Python, review basic linear algebra and probability, build models and websites that give recommendations based on given rating inputs, and learn how to utilize selected recommendation system techniques such as user-based and item-based collaborative filtering and matrix factorization. After completing the course, students will be able to understand and utilize the same algorithms that have been applied for recommending various products in business world, as well.
- Monday: Python Programming Fundamentals
- Tuesday: Brief review on Linear Algebra and Probability
- Wednesday and Thursday: Recommendation Systems, Model building, and Web design and development
- Friday: Students complete their projects and showcase work