Duke University
Java Programming: Build a Recommendation System
Duke University

Java Programming: Build a Recommendation System

This course is part of Java Programming and Software Engineering Fundamentals Specialization

Taught in English

Some content may not be translated

Robert Duvall
Owen Astrachan
Andrew D. Hilton

Instructors: Robert Duvall

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Course

Gain insight into a topic and learn the fundamentals

4.7

(635 reviews)

|

94%

Intermediate level
Some related experience required
4 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.7

(635 reviews)

|

94%

Intermediate level
Some related experience required
4 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Java Programming and Software Engineering Fundamentals Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 5 modules in this course

You will start out the capstone project by taking a look at the features of a recommender engine. Then you will choose how to read in and organize user, ratings, and movie data in your program. The programming exercise will provide a check on your progress before moving on to the next step.

What's included

2 videos2 readings1 quiz

Your second step in building a recommender will focus on making simple recommendations based on the average ratings that a movie receives. You'll also make sure that each recommended movie has a least a minimal number of user ratings before including it in your recommendations. Throughout this step you are encouraged you use your knowledge of the seven step process to design useful algorithms and successful programs to solve the challenges you will face.

What's included

1 video2 readings1 quiz

In your third step, you will be encouraged to use interfaces to rewrite your existing code, making it more flexible and more efficient. You will also add filters to select a desired subset of movies that you want to recommend, such as 'all movies under two hours long' or 'all movies made in 2012'. You'll also make your recommendation engine more efficient as you practice software design principles such as refactoring.

What's included

1 video2 readings1 quiz

In your fourth step, you will complete your recommendation engine by finding users in the database that have similar ratings and weighting their input to provide a more personal recommendation for the users of your program. Once you complete this step, you could request ratings of movies from those you know, run your program, and give them recommendations tailored to their own interests and tastes!

What's included

1 video2 readings1 quiz1 peer review

Congratulations on completing your recommender programming project! As we conclude this capstone course, our instructors have a few parting words as you embark in future learning and work in computer science!

What's included

1 video

Instructors

Instructor ratings
4.7 (77 ratings)
Robert Duvall
Duke University
8 Courses842,252 learners
Owen Astrachan
Duke University
8 Courses842,252 learners

Offered by

Duke University

Recommended if you're interested in Software Development

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