About this course: How do Java programs deal with vast quantities of data? Many of the data structures and algorithms that work with introductory toy examples break when applications process real, large data sets. Efficiency is critical, but how do we achieve it, and how do we even measure it? 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, and in particular, we recommend that you have taken the first course in this specialization (which also requires some previous experience with Java). In this course, you will use and analyze data structures that are used in industry-level applications, such as linked lists, trees, and hashtables. You will explain how these data structures make programs more efficient and flexible. You will apply asymptotic Big-O analysis to describe the performance of algorithms and evaluate which strategy to use for efficient data retrieval, addition of new data, deletion of elements, and/or memory usage. The program you will build throughout this course allows its user to manage, manipulate and reason about large sets of textual data. This is an intermediate Java course, and we will build on your prior knowledge. This course is designed around the same video series as in our first course in this specialization, including explanations of core content, learner videos, student and engineer testimonials, and support videos -- to better allow you to choose your own path through the course!
Who is this class for: This is an intermediate software development course. We recommend this course to learners who have previous experience in programming, specifically in Java, or a background in computer science and who want to take the next step in designing data structures for more efficient and more complex algorithms.
Created by: University of California, San Diego
Taught by: Christine Alvarado, Associate Teaching Professor
Computer Science and Engineering
Taught by: Mia Minnes, Assistant Teaching Professor
Computer Science and Engineering
Taught by: Leo Porter, Assistant Teaching Professor
Computer Science and Engineering
| Basic Info |
Course 2 of 5 in the
Object Oriented Java Programming: Data Structures and Beyond Specialization.
|
| Level | Intermediate |
| Commitment | 6 weeks of study, 6-10 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 module in the second course of our Intermediate Java Programming Specialization. We'll start with introductions again: to ourselves, the Google engineers, and the structure of the course. After the introduction we'll have a short warm up to get you comfortable with the code you will be building on to this class. But don't worry--no graded programming assignments yet. This week is all about getting comfortable and excited to learn.
5 videos, 8 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 the course
- Video: Concept Challenges
- Video: In the Real World: Welcome from Google Engineers
- Reading: Project Overview
- Video: Project Prototype
- Reading: Setting up Java and Eclipse
- Reading: Getting and Working with the Starter Code
Graded: Quiz about the Starter Code and Course Structure
WEEK 2
Working with Strings
This week we're going to dive into the course programming project. In the first lesson you'll learn about Strings and Regular Expressions, and in the programming assignment this week you'll apply that knowledge to adding functionality to your text editor so that it can measure the "readability" of text by calculating something called the "Flesch Readability Score". This course is focused on building code that not only does interesting things, but also finishes them quickly. So, let's get started building some code!
15 videos, 6 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 Overview
- Video: Core: Introduction to the Flesch Readability Score
- Video: Core: Basics of Strings in Java
- Video: Core: Working with Strings in Java
- Practice Quiz: Where to next?
- Video: Support: For-Each Loops, part 1 of 5
- Video: Support: For-Each Loops, part 2 of 5
- Video: Support: For-Each Loops, part 3 of 5
- Video: Support: For-Each Loops, part 4 of 5
- Video: Support: For-Each Loops, part 5 of 5
- Video: Core: Introduction to Regular Expressions
- Video: When I struggled: Regular expressions
- Video: Concept Challenge: Regular Expressions
- Video: Support: More with Regular Expressions
- Practice Quiz: Strings and Regular Expressions
- Reading: Did you have trouble with any question(s) on the practice quiz?
- Discussion Prompt: What questions do you have about Strings and Regular Expressions?
- Reading: Week 2: Additional Resources
- Video: Project: Programming Assignment Walk Through
- Reading: Programming Assignment FAQ
- Reading: Week 2: Congratulations and quiz answers
Graded: How Easy to Read is Your Writing?
Graded: Module and Programming Assignment Quiz
WEEK 3
Efficiency Analysis and Benchmarking
Welcome to week 2! The text-editor application you worked with last week does something, but it doesn't do it particularly fast. This week we'll start talking about efficiency. We'll introduce the concept of "Big-O" notation, which sounds a little silly, but is really a powerful (and extremely common) way of analyzing a program's efficiency, independent of the system that it's running on and the exact details of how it's implemented. Then we'll go the other direction and dive into the details, talking about how to measure the actual running time of a piece of code to get an idea of how it really performs in practice.
25 videos, 3 readings, 3 practice quizzes
- Video: Introduction
- Reading: By the end of this week, you will be able to...
- Video: Project Overview
- Video: In the Real World: Efficiency
- Video: Core: Our Motivation for Asymptotic Analysis
- Video: Core: Counting Operations
- Video: Core: Introduction to Asymptotic Analysis, Part 1
- Video: Core: Introduction to Asymptotic Analysis, Part 2
- Video: Core: Computing Big O with Consecutive Operations
- Video: Core: Computing Big O with Nested Operations
- Practice Quiz: Where to next?
- Practice Quiz: Practice Quiz
- Video: Concept Challenge: Classifying Functions using Big O
- Video: Support: Analyzing Selection Sort
- Video: Concept Challenge: Estimating Big O from Code
- Video: Core: Worst, Best, and Average Cases
- Video: In the Real World: Worst Case Analysis
- Video: Core: Analyzing Search Algorithms
- Video: Core: Analyzing Sorting Algorithms
- Video: When I struggled: Algorithm performance
- Video: Core: Merge Sort
- Video: Core: A Summary of Sorting
- Video: Core: Common Pitfalls in Asymptotic Analysis
- Practice Quiz: Asymptotic Notation and Analysis
- Video: Core: Introduction to Benchmarking
- Video: Core: Using Java Time
- Video: Core: Analyzing Timings
- Video: Concept Challenge: Relating Timing Data to Algorithm Analysis
- Reading: Week 3: Additional Resources
- Video: Project: Week 3 Project Walk Through
- Reading: Week 3: Congratulations and quiz answers
Graded: Making Flesch Score Calculation More Efficient
Graded: Module and After Programming Assignment Quiz
WEEK 4
Interfaces, Linked Lists vs. Arrays, and Correctness
This week we'll start talking about some of the basic concepts that one expects to find in a data structures course: the idea of data abstraction, and a data structure called a Linked List. Even though Linked Lists are not very efficient structures (for the most part), they do hit home the idea of "linking" pieces of data together in your computer's memory, rather than storing the data in one contiguous region. This linking idea will be central to many of the more advanced data structures, namely trees and graphs, that are coming up later in this course and in the next course in this specialization. In this module you'll also learn tools and procedures for unit testing your code, which is a way to make sure that what you've written is correct, and a staple practice of any sophisticated software developer.
26 videos, 3 readings, 2 practice quizzes
- Video: Introduction
- Reading: By the end of this week, you will be able to...
- Video: Project Overview
- Video: Core: Introduction to Abstraction
- Video: In the Real World: Data Abstraction
- Video: Core: Linked Lists vs. Arrays
- Video: In the Real World: Lists vs. Arrays
- Video: Core: Generics and Exceptions
- Video: Core: Java Code for a Linked List
- Video: Concept Challenge: Implementing linked lists, a first attempt
- Video: Concept Challenge: Drawing Linked Lists, second attempt
- Video: Support: Adding to a Linked List
- Video: When I struggled: Data structures
- Video: Core: Testing and Confidence
- Video: In the Real World: How can the compiler help with testing?
- Video: Core: Testing Practices
- Practice Quiz: Where to next?
- Video: In the Real World: How do you test the behavior of code?
- Video: Support: JUnit in Eclipse
- Video: In the Real World: Unit Testing
- Video: Core: Testing Linked List's "Get" Method
- Video: Concept Challenge: Which Tests Should You Run?
- Video: In the Real World: Test-driven development
- Reading: Week 4: Additional Resources
- Video: Project: Linked List Assignment Walk Through
- Video: When I struggled: confidence in code
- Practice Quiz: Where to next?
- Video: Core: Markov Text Generation
- Video: Core: Implementing Markov Text Generation
- Video: Project: Markov Text Generation Walk Through
- Ungraded Programming: Markov Text Generation
- Reading: Week 4: Congratulations
Graded: Implement and Test a Linked List
Graded: Week 4 Reflective Programming Assignment Quiz
WEEK 5
Trees! (including Binary Search Trees and Tries)
Welcome to week 4! We know you've been working hard. We hope you tried that optional Markov Text Generation programming assignment last week, but if not, no worries. You can always go back and do it later (spoiler alert: it's pretty amazing that such a simple algorithm can produce such realistic text). This week there's more fun (and hard work) as we learn about trees. Trees rely on the same linked structure idea as Linked Lists, only they're MUCH faster (usually...). In the project this week you'll add auto-complete to your text editor. Believe us when we say it's so cool when you get it working! You'll see... and we bet you can't wait for the programming assignment now. :)
22 videos, 3 readings, 1 practice quiz
- Video: Introduction
- Reading: By the end of this week, you will be able to...
- Video: Project Overview
- Video: Core: Trees
- Video: In the Real World: Trees
- Video: Core: Defining Trees
- Video: Core: Binary Trees
- Video: Core: Pre-Order Traversals
- Practice Quiz: Where to next?
- Video: Core: Post-Order, In-Order, and Level-Order Traversals (Breadth-first search)
- Video: When I struggled: Why traverse a tree?
- Video: Core: Introduction to Binary Search Trees
- Video: Core: Searching in a BST
- Video: Support: Code for BST's "Find" Method
- Video: Core: Inserting into a BST
- Video: Support: Code for BST's "Insert" Method
- Video: Core: Deleting from a BST
- Video: Concept Challenge: BST Shape
- Video: Core: Performance of BSTs and Balancing, Part 1
- Video: Core: Performance of BSTs and Balancing, Part 2
- Video: Core: Introduction to Tries
- Video: Core: Performance of Tries
- Video: Core: Implementing a Trie
- Reading: Week 5: Additional Resources
- Video: Project: Week 5 Project Walk Through
- Reading: Week 5: Congratulations and quiz answers
Graded: Spell Checking and Autocomplete
Graded: Week 5 Content and Programming Assignment Quiz
WEEK 6
Hash Maps and Edit Distance
You made it to the last week! Congratulations on getting this far! In this last week we'll be looking at a fundamental data structure called a Hash Table. If you thought trees were fast, just wait until you see what Hash Tables can do! Your last programming assignment will add spelling correction suggestions to your text editor, and there's an optional assignment that builds on the same ideas as the main assignment too, if you have the time and energy.
14 videos, 3 readings
- Video: Introduction
- Reading: By the end of this week, you will be able to...
- Video: Project Overview
- Video: Core: Hash Tables
- Video: Core: Collisions in Hash Tables
- Video: When I Struggled: Hash Tables
- Video: Core: Applications of Hash Tables
- Video: Support: Modular Arithmetic
- Video: Concept Challenge: Hash Tables
- Video: Core: Overview
- Video: Core: Algorithm
- Video: Core: Edit Distance
- Reading: Week 6: Additional Resources
- Video: Project: Spelling Suggestions Walk Through
- Video: Project: Word Path Walk Through
- Ungraded Programming: Word Paths (Optional but Recommended)
- Reading: Week 6: Congratulations and quiz answers
- Video: Core: Congratulations!
Graded: Spelling Suggestions
Graded: Week 6: Programming Assignment and Content Quiz
FAQs
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Pricing
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|---|---|---|
| Access to course materials | Available | Available |
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Ratings and Reviews
involving course and best part is the project which provides practical exposure along with conceptual knowledge
Learnt a lot from it.
Excellent course! Strongly recommended!
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RK
Cource is too good