Java Programming: Build a Recommendation System
Create a Netflix-style movie recommendation engine using Java. Learn data structures, interfaces, and algorithmic thinking.
Create a Netflix-style movie recommendation engine using Java. Learn data structures, interfaces, and algorithmic thinking.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Java Programming and Software Engineering Fundamentals Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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English
বাংলা, اردو, Tiếng Việt, 2 more
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What you'll learn
Parse and organize movie ratings data
Implement average rating calculations
Create user similarity algorithms
Build weighted recommendation systems
Display recommendations through web interface
Skills you'll gain
This course includes:
0.6 Hours PreRecorded video
4 quizzes, 1 peer review
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This capstone course teaches students how to build a movie recommendation system similar to those used by Netflix and Amazon. The curriculum covers data parsing, average rating calculations, user similarity metrics, and weighted recommendations. Students implement the system step-by-step, from basic functionality to advanced features using Java, while learning practical software design principles and data structure manipulation.
Introducing the Recommender
Module 1 · 1 Hours to complete
Simple Recommendations
Module 2 · 52 Minutes to complete
Interfaces, Filters, Database
Module 3 · 58 Minutes to complete
Weighted Averages
Module 4 · 2 Hours to complete
Farewell
Module 5 · 1 Minutes to complete
Instructors
Associate Professor of the Practice
Andrew Hilton is an Associate Professor of the Practice in the Department of Electrical and Computer Engineering at Duke University's Pratt School of Engineering, where he has been teaching since 2012. Before joining Duke, he worked as an advisory engineer at IBM. One of the key courses he teaches is ECE 551, an intensive introduction to programming designed to equip graduate students with no prior experience to master programming and tackle advanced courses. In 2015, Professor Hilton received the Klein Family Distinguished Teaching Award for his excellence in teaching. He holds a Ph.D. in Computer Science from the University of Pennsylvania.
Transforming Computer Science Education at Duke University
Robert Duvall is a dedicated Lecturer in the Department of Computer Science at Duke University, where he has been instrumental in reshaping introductory computing curricula for over 15 years. His innovative teaching approach focuses on creating a simplified yet intellectually rigorous learning environment for novice students, enabling them to leverage technological advancements to tackle significant challenges. Recently, he has collaborated with colleagues to redesign Duke’s introductory computer science course, aiming to engage a diverse range of students from various backgrounds and disciplines. Duvall holds a Master of Science in Computer Science from Brown University and is recognized for his commitment to educational excellence, having developed several courses that emphasize practical skills and critical thinking. His passion for teaching and continuous improvement in computer science education underscores his role as a leader in fostering an inclusive and effective learning atmosphere at Duke.
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4.7 course rating
639 ratings
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