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[null,"1.","Record Nr.",null,"UNICAMPANIASUN0118679"]
[null,null,"Autore",null,"Mencuccini, Corrado"]
[null,null,"Titolo",null,"Esercizi di fisica : meccanica e termodinamica : interamente svolti / Corrado Mencuccini, Vittorio Silvestrini"]
[null,null,"Pubbl/distr/stampa",null,"Rozzano, : Casa Editrice Ambrosiana, 2017"]
[null,null,"ISBN",null,"978-88-08-28702-1"]
[null,null,"Descrizione fisica",null,"VI, 178 p. : ill. ; 27 cm."]
[null,null,"Soggetti",null,"70-XX - Mechanics of particles and systems [MSC 2020]"]
[{"$nulls":4},"00A79 (77-XX) - Physics [MSC 2020]"]
[{"$nulls":4},"74A15 - Thermodynamics in solid mechanics [MSC 2020]"]
[null,null,"Lingua di pubblicazione",null,"Italiano"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,"2.","Record Nr.",null,"UNISA996546834703316"]
[null,null,"Autore",null,"Hazzan Orit <1962->"]
[null,null,"Titolo",null,"Guide to teaching data science : an interdisciplinary approach / / Orit Hazzan and Koby Mike"]
[null,null,"Pubbl/distr/stampa",null,"Cham, Switzerland : , : Springer Nature Switzerland AG, , [2023]"]
[{"$nulls":4},"©2023"]
[null,null,"ISBN",null,"3-031-24758-2"]
[null,null,"Edizione",null,"[1st ed. 2023.]"]
[null,null,"Descrizione fisica",null,"1 online resource (xxvii, 321 pages) : illustrations (black and white, and colour)"]
[null,null,"Disciplina",null,"006.312"]
[null,null,"Soggetti",null,"Big data - Study and teaching"]
[{"$nulls":4},"Data mining - Study and teaching"]
[{"$nulls":4},"Database management - Study and teaching"]
[{"$nulls":4},"Electronic data processing - Study and teaching"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Part I: Overview of Data Science and Data Science Education -- Chapter 1. Introduction -- Chapter 2. What is data science -- Chapter 3. Introduction to data science education -- Chapter 4. Data science thinking -- Part II: Challenges of Data Science Education -- Chapter 5. The pedagogical challenge of data science education -- Chapter 6. Data science education and the variety of learners -- Chapter 7. The interdisciplinarity challenge -- Chapter 8. Data science skills -- Part III: Data science Teaching frameworks -- Chapter 9. Teacher Preparation - the Method for Teaching Data Science course -- Chapter 10. Data Science for Social Science -- Chapter 11. Conclusion."]
[null,null,null,"Sommario/riassunto","Data science is a new field that touches on almost every domain of our lives, and thus it is taught in a variety of environments. Accordingly, the book is suitable for teachers and lecturers in all educational frameworks: K-12, academia and industry. This book aims at closing a significant gap in the literature on the pedagogy of data science. While there are many articles and white papers dealing with the curriculum of data science (i.e., what to teach?), the pedagogical aspect of the field (i.e., how to teach?) is almost neglected. At the same time, the importance of the pedagogical aspects of data science increases as more and more programs are currently open to a variety of people. This book provides a variety of pedagogical discussions and specific "]
[{"$nulls":4},"teaching methods and frameworks, as well as includes exercises, and guidelines related to many data science concepts (e.g., data thinking and the data science workflow), main machine learning algorithms and concepts (e.g., KNN, SVM, Neural Networks, performance metrics, confusion matrix, and biases) and data science professional topics (e.g., ethics, skills and research approach). Professor Orit Hazzan is a faculty member at the Technion’s Department of Education in Science and Technology since October 2000. Her research focuses on computer science, software engineering and data science education. Within this framework, she studies the cognitive and social processes on the individual, the team and the organization levels, in all kinds of organizations. Dr. Koby Mike is a Ph.D. graduate from the Technion's Department of Education in Science and Technology under the supervision of Professor Orit Hazzan. He continued his post-doc research on data science education at the Bar-Ilan University, and obtained a B.Sc. and an M.Sc. in Electrical Engineering from Tel Aviv University."]