Guide to Teaching Data Science: An Interdisciplinary by Orit Hazzan HARDBACK

Springer International Publishing AG

This comprehensive guide addresses the critical need for effective pedagogy in data science education. Designed for educators across K-12, academia, and industry, it bridges the gap in literature by focusing on 'how to teach' data science, rather than just 'what to teach'. Explore diverse pedagogical discussions, specific teaching methods, and practical frameworks. The book covers essential data science concepts like data thinking and workflow, key machine learning algorithms (KNN, SVM, Neural Networks), performance metrics, and professional topics such as ethics and research approaches. Written by leading experts Orit Hazzan and Koby Mike, this first edition hardcover is an invaluable resource for anyone involved in teaching data science. Key Features: * Focuses on the pedagogical aspects of data science education. * Provides specific teaching methods and frameworks. * Includes exercises and guidelines for data science concepts and algorithms. * Addresses important professional topics like ethics and skills. * Suitable for all educational frameworks: K-12, academia, and industry.