000			01103nam a2200217 4500
005			20250713144355.0
008			250713b |||||||| |||| 00| 0 eng d
020			_a9783031247576
082			_a005.7 HAZ _bHAZ
100			_aHazzan, Orit
245			_aGuide to teaching data science _b: an interdisciplinary approach
260			_aSwitzerland: _bSpringer Nature, _c2023.
300			_axxvii, 321p.
500			_aIncludes bibliographical references and index.
520			_aThis book provides a variety of pedagogical discussions and specific 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).
650			_aData Science Education
650			_a Interdisciplinarity
650			_a Computer Science Education
700			_aMike, Koby _eAuthor
942			_2ddc _n0 _cC
999			_c30525 _d30525