- Level Professional
- Duration 5 hours
- Course by Duke University
-
Offered by
About
Ever wonder how Netflix decides what movies to recommend for you? Or how Amazon recommends books? We can get a feel for how it works by building a simplified recommender of our own! In this capstone, you will show off your problem solving and Java programming skills by creating recommender systems. You will work with data for movies, including ratings, but the principles involved can easily be adapted to books, restaurants, and more. You will write a program to answer questions about the data, including which items should be recommended to a user based on their ratings of several movies. Given input files on users ratings and movie titles, you will be able to: 1. Read in and parse data into lists and maps; 2. Calculate average ratings; 3. Calculate how similar a given rater is to another user based on ratings; and 4. Recommend movies to a given user based on ratings. 5. Display recommended movies for a given user on a webpage.Modules
Step One
1
Assignment
- Step One
2
Videos
- Introduction and Motivation
- Reading and Storing Data
2
Readings
- Module Description / Resources
- Programming Exercise: Step One
Step Two
1
Assignment
- Step Two
1
Videos
- Average Ratings
2
Readings
- Module Description
- Programming Exercise: Step Two
Step Three
1
Assignment
- Step Three
1
Videos
- Filtering Recomendations
2
Readings
- Module Description
- Programming Exercise: Step Three
Step Four
1
Assignment
- Step Four
1
Videos
- Calculating Weighted Averages
2
Readings
- Module Description
- Programming Exercise: Step Four
Step Five
1
Peer Review
- Step Five
Farewell
1
Videos
- Farewell from the Instructor Team
Auto Summary
Dive into the world of recommendation systems with the course "Java Programming: Build a Recommendation System." Guided by Coursera, this professional-level course offers a hands-on approach to understanding how popular platforms like Netflix and Amazon suggest content to their users. In this capstone project, you'll harness your Java programming and problem-solving skills to create your own recommender system. Working with movie rating data, you'll learn techniques that can be applied to various domains such as books and restaurants. The course will walk you through: - Reading and parsing data into lists and maps - Calculating average ratings - Determining the similarity between users based on their ratings - Recommending movies based on user ratings - Displaying recommendations on a webpage Spanning 300 hours, this course is designed for professionals looking to deepen their expertise in IT and computer science. Learners can access the course through Starter, Professional, or Paid subscription options. This course is a perfect fit for those eager to explore the mechanics behind recommendation engines and apply these skills in real-world scenarios.

Robert Duvall

Owen Astrachan

Andrew D. Hilton

Susan H. Rodger