NEW - Revel® empowers students to actively participate in learning. More than a digital textbook, Revel delivers an engaging blend of author content, media, and assessment. With Revel, students read and practice essential coding skills in one continuous experience, anytime, anywhere, on any device. Learn more about Revel. Dynamic content brings concepts to life Videos and interactives integrated directly into the narrative enable students to practice essential coding skills in context. VideoNotes are narrated step-by-step video tutorials that show how to solve problems completely, from design through coding. Animated Listings step students through the code line-by-line, showing what is happening in the program. Interactives test students'' new-found knowledge with multiple-choice and matching questions at the end of each section.
Live coding practice side-by-side with Revel and Jupyter Notebooks helps students practice what they''ve learned in a live coding environment. Assignable and automatically graded programing exercises allow students to experience the power of practice as they work through their coding assignments and receive immediate personalized feedback. The exercises let instructors gauge student comprehension frequently, provide timely feedback, and address learning gaps along the way. The intuitive user interface makes it easier for students (and you) to seamlessly search and navigate the text. Keyword searches now scan videos and figures in addition to text, making it easier to locate the information you and your students need when you need it. Personalized search histories are also saved for easier and faster access. The Quick View navigation pane displays surrounding pages in a convenient visual sidebar. As students work in Revel, they can also identify sections, videos, or images they''d like to revisit.
The Quick View pane lets them jump right back into the bookmarked content they''d like to review. The Revel mobile app lets students read and practice anywhere, anytime, on any device, online and off. It syncs work across all registered devices automatically, allowing learners to toggle between phone, tablet, and laptop as they move through their day. Prepares students for future careers with the most current and relevant real-world applications Students implement hands-on, real-world case studies through free open source Python and data science libraries using Jupyter Notebooks. Students work with artificial-intelligence technologies including natural language processing, data mining Twitter®, IBM® Watson(tm), speech synthesis, speech recognition, supervised and unsupervised machine learning, deep learning, and big data with Hadoop, Spark, SQL/NoSQL and the Internet of Things (IoT). Extensive static, dynamic and interactive 2D and 3D visualizations and animations. Artificial Intelligence, a key intersection between computer science and data science, is emphasized, with all six data-science implementation case study chapters rooted in AI technologies and/or discussions of the big data hardware and software infrastructure that enables AI-based solutions. A companion website, www.
pearson.com/deitel, contains dynamic support resources for instructors and students: VideoNotes. Live animations in source-code files and Jupyter Notebooks enable students to conveniently edit the code, modify animation parameters and re-execute the animations. Many open source visualization packages have animation capabilities for dynamic visualization, and some can turn animations into videos. Students will use visualization libraries and tools like Matplotlib, Seaborn and Folium to make data come alive. Helps instructors adapt to a range of computer-science and data-science courses with the flexible modular architecture Content is divided into groups of related chapters that instructors can easily include or omit. The Preface includes a chapter dependency chart to help instructors plan their syllabi. Chapters 1-11 cover the examples, exercises and projects (EEPs) traditionally associated with introductory computer-science Python programming courses.
Chapters 1-10 each include optional brief Intro to Data Science sections that prepare students for the Data Science Case Studies in Chapters 12-17. In these intro sections, the Deitels present data science history and terminology, Python''s statistics module, basic descriptive statistics, measures of central tendency, measures of dispersion, static and dynamic visualizations (Seaborn and Matplotlib), simulation, data preparation with pandas, CSV file manipulation, time series and simple linear regression. Chapters 12-17 are fully implemented AI- and big-data-based data-science case studies. Most instructors will cover the core Python content. Computer-science courses will likely work through more of Chapters 1-11 and fewer of Chapters 12-17 and the Intro to Data Science sections. Data science courses will likely work through the Intro to Data Science sections, fewer of Chapters 1-11 and more of Chapters 12-17. Functional-Style Programming Topics help students write more concise programs that are easier to debug and parallelize. Provides hundreds of real-world examples, challenging exercises, and projects for both computer science and data science topics Examples, exercises, projects (EEPs) and implementation case studies give students an engaging, challenging and entertaining introduction to Python programming, while also involving them in hands-on data science.
Jupyter Notebooks allow users to combine text, graphics, audio, video and interactive coding functionality, in a web browser for interactive programming exercises and self-checks. Self-Check Exercises and Answers after most sections enable students to test their knowledge of the concepts with short-answer questions and interactive IPython coding sessions. Actionable insights help improve results The educator dashboard offers an at-a-glance look at overall class performance. It helps instructors identify and contact struggling and low-activity students, ensuring that the class stays on pace. Easy assignment creation makes it simple to add content, set due dates, and publish assignments in one step. Flexible assignment settings allow you to change due date and time, availability, and points possible for any content within an assignment. And you can extend due dates for individual students or the entire class. The Performance dashboard provides detailed insight on student performance, from specific assignments to individual student scores and student code submissions.
LMS integration provides institutions, instructors, and students easy access to their Revel courses via Blackboard Learn(tm), Canvas(tm), Brightspace by D2L(tm), and Moodle(tm). Single sign-on lets students access Revel on their first day.