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--- mds:pds:start [05/03/2024 alle 16:59 (7 mesi fa)] – [Exams] Laura Semini
+++ mds:pds:start [16/09/2024 alle 17:40 (10 giorni fa)] (versione attuale) – [Software] Laura Semini
@@ Linea 1: / Linea 1: @@
-====== Programming for Data Science A.Y. 2023/24 ======
+====== Programming for Data Science A.Y. 2024/25 ======
 This is an introductory course to computer programming and related mathematical/logic background for students without a Bachelor in Computer Science or in Computer Engineering. The objective is to smoothly introduce the student to the programming concepts and tools needed for typical data processing and data analysis
 tasks. The course consists of lectures and practice in computer labs.
-The course is **ANNUAL**: so, classes will start in September and finish in May. Hence, the first exam date for students attending the course this year for the first time will be at the end of May: there will be a written/lab exam first, if you succeed, then you are admitted to the second part of the exam, the oral.
+The course is in the **1st SEMESTER**: so, classes will start in September and finish in January: there will be a written/lab exam first, if you succeed, then you are admitted to the second part of the exam, the oral.
-As a facilitation, we allow students who wish to do so, to take a partial test (a midterm) during the winter exam session (which is for A.Y. 22/23 students). If interested, we ask you to send us an email (with subject MidTerm_P4DS) a week before the exam asking us to attend the midterm, for organizational reasons.
 =====Instructors=====
@@ Linea 19: / Linea 17: @@
-Lessons: <del>first semester on Wednesday 16-18 and Friday 14-16, room H;</del> Second semester on Wednesday 14-16 (Fib E) and Thursday 11-13 (Fib C)
+Lessons: <
-Course slides & other material on **Teams: "667AA 23/24 - PROGRAMMING FOR DATA SCIENCE [WDS-LM]",  https://teams.microsoft.com/l/team/19%3ajiJs1z1bW5HinlbZkWvktsol65Y19Ix0dJ7FS9sQnPY1%40thread.tacv2/conversations?groupId=0f25d973-7388-4c24-b3a4-c2c13bf054dd&tenantId=c7456b31-a220-47f5-be52-473828670aa1**
+Course slides & other material on **Teams: "667AA 24/25 - PROGRAMMING FOR DATA SCIENCE [WDS-LM]", https://teams.microsoft.com/l/team/19%3ArjrbC2bZuNSJ6YDv_xoiS42M171Z8jbk1PFarIMVwpk1%40thread.tacv2/conversations?groupId=63b57f30-ba5e-4503-a794-1f23f80a7f10&tenantId=c7456b31-a220-47f5-be52-473828670aa1**
 =====Text Books=====
-  * **[LA]**   Mike X Cohen // Linear Algebra: Theory, Intuition, Code // 2021
+    * **[T]** Kenneth H. Rosen.  //Discrete Mathematics and Its Applications//. MCGraw-Hill. [[http://highered.mheducation.com/sites/0073383090|Supplement material]] (including Errata-Corrige).
-  * **[T]** Kenneth H. Rosen.  //Discrete Mathematics and Its Applications//. MCGraw-Hill. [[http://highered.mheducation.com/sites/0073383090|Supplement material]] (including Errata-Corrige).
+  * **[LA]** “Linear Algebra: Theory, Intuition, Code” by Mike X Cohen, chapters: Vectors; Vector multiplication; Matrices; Matrix multiplication; Rank; Determinant; Matrix inverse; Eigendecomposition
-  * **[T]** “Linear Algebra: Theory, Intuition, Code” by Mike X Cohen, chapters: Vectors; Vector multiplication; Matrices; Matrix multiplication; Rank; Determinant; Matrix inverse; Eigendecomposition
+  * **[MV]** Any book on multivariable calculus
   * **[P]** Pieter Spronck. //The Coder’s Apprentice: Learning Programming with Python 3//, 2017. [[http://www.spronck.net/pythonbook|Book and supplement material]].
-  * **[C]** Brian W. Kernighan, Dennis M. Ritchie. //C Programming Language//. Second Edition, Prentice Hall, 1988.
 =====Software=====
   * **Python programming:** [[https://www.continuum.io/downloads|Anaconda distribution of Python 3]]. Computers at lab rooms include it both on Linux and Windows OS.
-  * **C programming (Linux):** either [[https://wiki.gnome.org/Apps/Gedit|gedit]] (or equivalent text editor) and [[https://gcc.gnu.org/|gcc]]. If you do not have gcc on your machine, check next item. Gedit and gcc are available on computers at lab room (Linux only).
+   * **Unix Shell** Either use Linux on lab machines, or install [[https://www.cygwin.com/|CygWin]] (on your PC).
-  * **C programming (Windows)** Either DevC++ (already installed on LabMachines) or install [[https://www.cygwin.com/|CygWin]] (not on lab machines -- on your PC) or install a Virtual Machine  (such us [[https://www.virtualbox.org/|VirtualBox]]) running any Linux distribution.
+  * **Python online** including visualization of memory state [[http://pythontutor.com/|PythonTutor]].
-  * **Editor for C files on Windows** Either use the DevC++ editor, or use [[https://notepad-plus-plus.org/download/v7.5.2.html|Notepad++ ]].
-  * **Unix Shell** Either use Linux on lab machines, or install [[https://www.cygwin.com/|CygWin]] (on your PC).
-  * **Python/C online** including visualization of memory state [[http://pythontutor.com/|PythonTutor]].
   * **Jupyter Notebooks** shown during theory classes [[https://github.com/GiulioRossetti/PDS_notebooks|GitHub]]