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!
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Programme du cours : ce que vous apprendrez dans ce cours
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.
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!
Efficiency Analysis and Benchmarking
Welcome to week 3! 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.
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.
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Meilleurs avis pour Data Structures and Performance
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.
The course curriculum is well designed and teaches students the basic data structures needed to be a successful software engineer. The project is good, and the weekly assignments are challenging.
Enseignants
Christine Alvarado
Associate Teaching Professor
Mia Minnes
Assistant Teaching Professor
Leo Porter
Associate Teaching ProfessorÀ propos de Université de Californie à San Diego
Foire Aux Questions
Quand aurai-je accès aux vidéos de cours et aux devoirs ?
Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.
À quoi ai-je droit si je m'abonne à cette Spécialisation ?
Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.
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