Explore a preview version of Android App Developer right now. Concepts are presented in the context of fully tested programs. Using the Deitel's signature App-Driven Approach in which all concepts are presented in the context of complete working apps, you'll then build seven Android apps that introduce everything you need to start creating your own—Welcome app, Tip Calculator app, Flag Quiz app, , Doodlz drawing app, Cannon Game app, WeatherViewer app, Twitter Searches app, and Address Book app.
Learn algorithms for solving classic computer science problems with this concise guide covering everything from fundamental …. Go from beginner to expert in Python by building projects.
The best investment for your Python …. This material is protected under all copyright laws, as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. Prepares students for future careers with the most current and relevant real-world applications.
Helps instructors adapt to a range of computer-science and data-science courses with the flexible modular architecture. Provides hundreds of real-world examples, challenging exercises, and projects for both computer science and data science topics. Check out the preface for a complete list of features.
DS Important: To use the test banks below, you must download the TestGen software from the TestGen website. If you need help getting started, read the tutorials on the TestGen site. Pearson offers affordable and accessible purchase options to meet the needs of your students. Connect with us to learn more. Paul J. He and his co-author, Dr. Harvey M. Deitel earned B. Deitel has delivered hundreds of programming courses to academic, corporate, government and military clients. We're sorry!
We don't recognize your username or password. Please try again. The work is protected by local and international copyright laws and is provided solely for the use of instructors in teaching their courses and assessing student learning. You have successfully signed out and will be required to sign back in should you need to download more resources. Reviews "Strikes a good balance between teaching computer science fundamentals and putting data science techniques into practice.
Designed to help students not only learn programming fundamentals but also leverage the large number of existing libraries to start accomplishing tasks with minimal code. Concepts are accompanied by rich Python examples that students can adapt to implement their own solutions to data science problems. I like that cloud services are used. Great overview of all the big data technologies with relevant examples. This book has my strongest recommendation both as an introduction to Python as well as Data Science.
A great introduction to IBM Watson and the services it provides! The examples involving the top-down, stepwise refinement of programs illustrate how programs are really developed. A fantastic job providing background on various machine learning concepts without burdening the users with too many mathematical details. My business analytics students had little to no coding experience when they began the course.
In addition to loving the material, it was easy for them to follow along with the example exercises and by the end of the course were able to mine and analyze Twitter data using techniques learned from the book. The chapters are clearly written with detailed explanations of the example code, which makes it easy for students without a computer science background to understand.
The modular structure, wide range of contemporary data science topics, and companion Jupyter notebooks make this a fantastic resource for instructors and students of a variety of Data Science, Business Analytics, and Computer Science courses. Fabulous Big Data chapter—it covers all of the relevant programs and platforms.
Great Watson chapter! This is the type of material that I look for as someone who teaches Business Analytics. The chapter provided a great overview of the Watson applications. Machine Learning is a huge topic and this chapter serves as a great introduction. I loved the housing data example—very relevant for business analytics students.
The chapter was visually stunning. A compelling feature is the integration of content that is typically considered in separate courses. This is important for building data science programs that are more than just cobbling together math and computer science courses.
A book like this may help facilitate expanding our offerings and using Python as a bridge for computer and data science topics.
For a data science program that focuses on a single language mostly , I think Python is probably the way to go. I would likely use this book. The most compelling feature is that it could, theoretically, be used for both computer science and data science programs. Mark Pauley, University of Nebraska at Omaha. The material is presented in digestible sections accompanied by engaging interactive examples.
This book should appeal to both computer science students interested in high-level Python programming topics and data science applications, and to data science students who have little or no prior programming experience.
Nearly all concepts are accompanied by a worked-out example. Start your free trial. Deitel , Harvey M. Deitel , Abbey Deitel , Michael Morgano. Table of contents Product information. Introduction to Android 2. Android Market and App Business Issues 3. Show and hide more.
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