Popular Science USA – November-December 2017
English | 100 pages | True PDF | 30.4 MB
Increased focus on computer science has recently brought about the new national curriculum in computing. This book explores the role of Computer Science Teacher in a secondary school environment. An overview of secondary school computing is covered, along with what the role encompasses, the attributes, knowledge and skills required to be a success and useful standards, tools, methods and techniques you can employ. Case studies and quotes from schools and current teachers are also included.
Ideal for undergraduates with little or no science background,Foundations of Earth Science provides a student-friendly, highly visual, non-technical survey of our physical environment with balanced, up-to-date coverage of geology, oceanography, astronomy, and meteorology. Foundations of Earth Science is thebrief, paperback version of the best-selling Earth Science by Lutgens and Tarbuck, and designed for introductory courses in Earth science. The new Eighth Edition facilitates active learning by incorporating learning objectives throughout each chapter to provide students with a structured learning path. The learning path is tied to chapter objectives, giving students opportunities to demonstrate their understanding at the end of each section.
The Oxford Illustrated History of Science is the first-ever fully illustrated global history of science, from Aristotle to the atom bomb – and beyond.
Data Science is booming thanks to R and Python, but Java brings the robustness, convenience, and ability to scale critical to today’s data science applications. With this practical book, Java software engineers looking to add data science skills will take a logical journey through the data science pipeline. Author Michael Brzustowicz explains the basic math theory behind each step of the data science process, as well as how to apply these concepts with Java.
Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they’re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools.
Packed with fascinating discoveries and facts, Science Year by Year takes kids on a fantastic visual journey through time, from stone tools and simple machines to rockets and robots.