Essential Computational Thinking: Computer Science from Scratch

Essential Computational Thinking: Computer Science from Scratch helps students build a theoretical and practical foundation for learning computer science. Rooted in fundamental science, this text defines elementary ideas including data and information, quantifies these ideas mathematically, and, through key concepts in physics and computation, demonstrates the relationship between computer science and the universe itself. In Part I, students explore the theoretical underpinnings of computer science in a wide-ranging manner. Readers receive a robust overview of essential computational theories and programming ideas, as well as topics that examine the mathematical and physical foundations of computer science. Part 2 presents the basics of computation and underscores programming as an invaluable tool in the discipline. Students can apply their newfound knowledge and begin writing substantial programs immediately. Finally, Part 3 explores more sophisticated computational ideas, including object-oriented programing, databases, data science, and some of the underlying principles of machine learning. Essential Computational Thinking is an ideal text for a firmly technical CS0 course in computer science. It is also a valuable resource for highly-motivated non-computer science majors at the undergraduate or graduate level who are interested in learning more about the discipline for either professional or personal development.Ricky J. Sethi is an associate professor of computer science at Fitchburg State University, the director of research for the Madsci Network, and a team lead for SNHU Online at Southern New Hampshire University. Prior to joining the faculty at Fitchburg, Dr. Sethi served as a research scientist at UMass Amherst/UMass Medical School and at UCLA/USC Information Sciences Institute, where he was chosen as an NSF Computing Innovation Fellow by the CCC and CRA. He holds a Ph.D. in computer science from the University of California, Riverside, a M.S. in physics/information systems from the University of Southern California, and a B.A. in neurobiology/physics from the University of California, Berkeley.