Java Programming: Solving Problems with Software
Learn Java programming fundamentals and develop problem-solving skills through hands-on projects with data analysis, image processing, and CSV file handling.
Learn Java programming fundamentals and develop problem-solving skills through hands-on projects with data analysis, image processing, and CSV file handling.
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 Object Oriented Programming in Java 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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What you'll learn
Edit, compile, and run Java programs
Use conditionals and loops effectively
Develop algorithms to solve specific problems
Process and analyze data from CSV files
Create reusable methods and classes
Skills you'll gain
This course includes:
5.2 Hours PreRecorded video
16 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive Java programming course teaches fundamental programming concepts and problem-solving skills through practical projects. Students learn Java syntax, data processing, algorithm development, and debugging techniques while working with real-world applications including DNA analysis, CSV data processing, and baby names analysis. The course emphasizes hands-on coding practice and systematic problem-solving approaches.
Introduction to the Course
Module 1 · 22 Minutes to complete
Fundamental Java Syntax and Semantics
Module 2 · 6 Hours to complete
Strings in Java
Module 3 · 5 Hours to complete
CSV Files and Basic Statistics in Java
Module 4 · 2 Hours to complete
MiniProject: Baby Names
Module 5 · 2 Hours to complete
Fee Structure
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.
Professor of the Practice in Computer Science at Duke University
Susan H. Rodger is a Professor of the Practice in the Computer Science Department at Duke University, where she specializes in visualization, interaction, and computer science education. She earned her PhD and M.S. in Computer Science from Purdue University and her B.S. in Computer Science and Mathematics from North Carolina State University. Professor Rodger is renowned for developing JFLAP, an educational software tool widely used for teaching formal languages and automata theory, which has been implemented globally in over 160 countries. She also leads the Adventures in Alice Programming project, which integrates computing into K-12 education by providing curriculum materials and professional development for teachers. Her significant contributions to computer science education have been recognized with numerous awards, including the 2013 ACM Karl V. Karlstrom Outstanding Educator Award and the 2019 Taylor L. Booth Education Award. In addition to her teaching and research, she has authored two books and published over fifty journal and conference articles. Outside of academia, Susan enjoys reading, hiking, traveling, swimming, and baking, often creating computer science-themed cookies for her students.
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Frequently asked questions
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