About this course: How does Google Maps plan the best route for getting around town given current traffic conditions? How does an internet router forward packets of network traffic to minimize delay? How does an aid group allocate resources to its affiliated local partners? To solve such problems, we first represent the key pieces of data in a complex data structure. In this course, you’ll learn about data structures, like graphs, that are fundamental for working with structured real world data. You will develop, implement, and analyze algorithms for working with this data to solve real world problems. In addition, as the programs you develop in this course become more complex, we’ll examine what makes for good code and class hierarchy design so that you can not only write correct code, but also share it with other people and maintain it in the future. The backbone project in this course will be a route planning application. You will apply the concepts from each Module directly to building an application that allows an autonomous agent (or a human driver!) to navigate its environment. And as usual we have our different video series to help tie the content back to its importance in the real world and to provide tiered levels of support to meet your personal needs.
Who is this class for: This is an intermediate Java course. We recommend this course to learners who have previous experience in software development or a background in computer science.
Created by: University of California, San Diego
Taught by: Leo Porter, Assistant Teaching Professor
Computer Science and Engineering
Taught by: Mia Minnes, Assistant Teaching Professor
Computer Science and Engineering
Taught by: Christine Alvarado, Associate Teaching Professor
Computer Science and Engineering
| Basic Info | Course 3 of 5 in the Object Oriented Java Programming: Data Structures and Beyond Specialization |
| Level | Intermediate |
| Commitment | 5 weeks of study, 1-3 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Introduction to the Course
Welcome to the first week in the third course of our Intermediate Java Programming Specialization. Once again start with introductions, and in particular introduce the unique structure of this course. Also, if you're not sure if this course is right for you, we've got an optional pre-course quiz coming right up that can help you figure out if you're in the right place. If you decide to stay with us (and we really hope you will!) we've got a great backbone project for you: your very own mapping application, inspired by Google Maps! The core data structure throughout this course is graphs, which may very well be the most fundamental data structure in all of computer science. Ready to begin? So are we!
4 videos, 10 readings, 2 practice quizzes
- Video: Welcome
- Reading: After completing this course, you will be able to ...
- Reading: Is this course right for me?
- Practice Quiz: Pre-course quiz
- Reading: Up Next: A short survey
- Practice Quiz: Survey: Your goals for the course
- Reading: If you want more practice before you begin...
- Reading: The structure of this course
- Video: Your path through this course
- Video: Concept challenges
- Reading: Welcome from the Google engineers
- Discussion Prompt: Introduce Yourself!
- Reading: Project Overview
- Video: Project Prototype
- Reading: Setting up Java and Eclipse
- Reading: Getting and Setting up the Starter Code
- Reading: Project: Orientation to the Starter Code, Data Files and Front-end
Graded: Course Structure and Starter Code Quiz (make sure you can run the starter code first)
WEEK 2
Introduction to Graphs
This week we'll start getting technical, introducing you to the central data structure in the course: Graphs. You'll learn the basics and then have a chance to dive in a little deeper into the code, getting ready to start building that Google Maps-like application.
17 videos, 7 readings, 2 practice quizzes
- Video: Introduction
- Reading: A note about week numbers
- Reading: By the end of this week, you will be able to...
- Video: Project: Introduction to Graphs Project Overview
- Video: Core: What's a graph?
- Video: Core: Graph definitions
- Video: In the real world: Graphs at Google
- Video: In the real world: More graphs at Google
- Practice Quiz: Graphs
- Reading: (Read only AFTER finishing Graphs Quiz)
- Video: Core: Implementing graphs in Java
- Video: Core: Adjacency matrix
- Video: Core: Adjacency list
- Practice Quiz: Where to next?
- Video: Concept Challenge: Comparing implementations of graphs
- Video: In the real world: Performance considerations
- Video: When I struggled: Analyzing implementations
- Video: Core: Neighbors
- Video: Support: Coding getNeighbors
- Video: Support: Coding 2-Hop Neighbors
- Video: Support: Multiplying Adjacency Matrices
- Reading: Graph definitions and implementation: a glossary
- Reading: Week 2: Additional Resources
- Video: Project: Programming Assignment Walkthrough
- Reading: Programming Assignment FAQ
- Reading: Graph definitions and implementations Quiz Answer explanations (Read ONLY after you pass the quiz)
Graded: Project: Implementing Graphs
Graded: Graph definitions and implementation
WEEK 3
Class design and simple graph search
This week you'll get the backbone of your map search engine up and running. In previous courses, including the previous courses in this specialization, you've probably been given most of the classes you needed to complete the assignments. But learning how to design classes from scratch is a key skill that you will need as you become a more sophisticated Java programmer. This week we'll give you the tools you need to create a robust and elegant class design for your map search engine. We'll introduce a similar problem and show you how it can be represented as a graph. Then we'll introduce two core search algorithms: depth-first search and breadth-first search. Finally, we'll turn our graph problem into a set of Java classes. Your task on the programming assignment this week will be to do the same thing, but in the context on the map search engine!
20 videos, 3 readings, 1 practice quiz
- Video: Introduction
- Reading: By the end of this week, you will be able to ...
- Video: Project: Route Finding Project Overview
- Video: Core: Intro to Class Design
- Video: When I struggled: Building useful classes
- Video: In the Real World: Design patterns
- Video: Core: DFS, Part 1
- Video: Core: DFS, Part 2
- Video: Core: BFS
- Video: Support: Developing Small Examples to Test Your Code
- Practice Quiz: Where to next?
- Video: When I struggled: Data structures jargon
- Video: When I struggled: The right data structure for the job
- Video: Concept Challenge: Performance of DFS and BFS
- Video: Core: Class Design
- Video: When I struggled: If you fail to plan ...
- Video: When I struggled: ... but don't forget to start!
- Video: In the real world: Planning ahead with design
- Video: Core: Refactoring
- Video: Support: Where to start the project design?
- Video: In the Real World: Why is code refactored?
- Reading: Week 3: Additional Resources
- Video: Project: Programming Assignment Walk-through
- Reading: End of Week Quiz Answers
Graded: Project: Class Design and Graph Search
Graded: Code Design Peer Review
Graded: End of Week Quiz (complete project and peer review first)
WEEK 4
Finding shortest paths in weighted graphs
In the past two weeks, you've developed a strong understanding of how to design classes to represent a graph and how to use a graph to represent a map. In this week, you'll add a key feature of map data to our graph representation -- distances -- by adding weights to your edges to produce a "weighted graph". Although this might seem like a small change, the algorithms that work for unweighted graphs may prove ineffective for weighted graphs. To address this problem, you'll explore more advanced shortest path algorithms. First, you'll see how to find the shortest path on a weighted graph, then you'll see how to find it more quickly. In the project, you'll apply these ideas to create the core of any good mapping application: finding the shortest route from one location to another.
10 videos, 4 readings
- Video: Introduction
- Reading: By the end of this week, you will be able to ...
- Video: Project: Shortest Path Overview
- Video: Core: Shortest Path with BFS
- Video: Core: Geographic Maps
- Video: Core: Dijkstra's Algorithm
- Video: Concept Challenge: Performance of Dijkstra's Algorithm
- Video: Core: A* Search Algorithm
- Video: When I struggled: Tackling large programming projects
- Video: When I Struggled: Remembering classical algorithms
- Reading: Week 4: Additional Resources
- Video: Project: Shortest Path Programming Assignment Walkthrough
- Reading: Test cases and debugging guide for the quiz
- Reading: End of Week Quiz Answers
Graded: Project: Shortest Path
Graded: End of Week Quiz (very short, do programming assignment first)
WEEK 5
Route planning and NP-hard graph problems
In this week, we'll go beyond the problem of finding a path between two points, and focus on problems requiring overall path planning. For example, if you wanted to go on errands and visit 6 different locations before returning home, what is the optimal route? This problem is actually a really well known problem in computer science known as the Travelling Salesperson Problem (TSP). Attempting to solve the problem will lead us to explore complexity theory, what it means to be NP-Hard, and how to solve "hard" problems using heuristics and approximation algorithms. We'll end the week by showing how reformulating a problem can have a huge impact: making something which was effectively unsolvable before, now solvable!
11 videos, 3 readings
- Video: Introduction
- Reading: By the end of this week, you will be able to ...
- Video: Core: Traveling Salesperson Problem (TSP)
- Video: Concept Challenge: An algorithm for TSP
- Video: Core: TSP Brute-Force Algorithm
- Video: Core: TSP Algorithm Running Time
- Video: Core: NP Hard
- Video: Core: Approximations and Heuristics
- Video: Core: Hamiltonian Graphs
- Video: Core: Eulerian graphs
- Video: Core: Eulerian graphs, an algorithm
- Video: Core: An application in bioinformatics
- Reading: Week 5: Additional Resources
- Reading: End of Week Quiz Answers
Graded: End of Week Quiz
WEEK 6
End of Course Project Extension
You made it to the last week of our course! We're glad you're still with us. As a reward, there's no new content to learn this week. Instead you'll get the opportunity to extend your project in a direction of your own choosing. We hope you've got some neat ideas for personalizing your map application, and we look forward to seeing them in the peer review gallery. Submitting to the peer review gallery is optional (though the extension is required), but we hope you'll choose to participate.
1 video, 2 readings
- Reading: Week 6 Introduction
- Reading: Project: Week 6 Description -- REQUIRED EXTENSION
- Peer Review: Project Extension Feedback
- Video: End of course message
Graded: Week 6 Project Quiz (Complete your project extension first)
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Pricing
| Purchase Course | Audit | |
|---|---|---|
| Access to course materials | Available | Available |
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Ratings and Reviews
Great into to Java, instructors have clearly put thought in to the format with the choose your own learning style videos, and additional coverage where it may be needed. These have been very helpful.
It's a great course for getting started with Graphs but for an "advanced data structures" course, this is as basic as can be.
Very intresting course
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AR
Very good course. The hands on material makes it easy to learn and they are fun. It's challenging, however, starter code and excellent video lectures gave me the tools required to meet those challenges. Thanks to Coursera and UCSD.