Course Information

  • Location: Orenstein 111
  • Time: Wednesday, 10:00 - 13:00

Instructor Information:

Tel Aviv University Intel
  • Dr. Amitai Armon
  • Dr. Zeev Waks
  • Dr. Lev Faivishevsky
  • Tomer Levy

Course Goals and Short Syllabus:

The course will provide an overview of data science methodologies and technology, including data understanding, modeling and analysis in big scale.
A joined set of teachers, from Intel and TAU, will cover each of the topics from both theoretical and practical perspectives.

Course Format:

Each class will be a 3 hours lecture (given by one of Intel lectors or by Prof. Tova Milo) or a 3 hours recitation (tirgul) given by Slava Novgorodov.
Homework - 3 HW assigments during the semester (submission in pairs) - 30% of the final grade
Final exam - 70% of the final grade
Exam - Moed A: 04.08.2017
Exam - Moed B: 25.09.2017

Requirements:

  • Introduction to Probability/Statistics, Algorithms, Data Bases (in parallel)

Course Schedule

# Date Given by Title Material Note
1 15.03.2017 Dr. Armon, Dr. Waks Introduction to Data Science, Data Understanding [ppt1] [ppt2]
2 22.03.2017 Dr. Waks Feature Selection [ppt]
3 29.03.2017 Slava Novgorodov Recitation #1 [ppt][code] HW #1 [pdf][ipynb], until 03.05.2017
4 19.04.2017 Dr. Faivishevsky Data Modeling #1 [ppt]
5 26.04.2017 Dr. Faivishevsky Data Modeling #2 [ppt]
6 03.05.2017 Slava Novgorodov Recitation #2 [ppt][code] HW #2 [pdf][ipynb], until 21.06.2017
7 10.05.2017 Dr. Armon Introduction to Deep Learning [ppt]
8 17.05.2017 Tomer Levy Big Data - HDFS [pdf]
9 24.05.2017 Slava Novgorodov Recitation #3 [ppt][code]
10 07.06.2017 Prof. Milo Big Data - MapReduce [pdf1] [pdf2]
11 14.06.2017 Prof. Milo Big Data - Spark [pdf1] [pdf2]
12 21.06.2017 Slava Novgorodov Recitation #4 [ppt][code] HW #3 [pdf], until 28.07.2017
13 28.06.2017 Dr. Armon, Slava Novgorodov Summary