Course Information

  • Location: Limudei HaSviva 013B
  • Time: Wednesday, 10:00 - 13:00

Instructor Information:

Tel Aviv University Intel
  • Dr. Amitai Armon
  • Dr. Zeev Waks
  • Dr. Lev Faivishevsky
  • Hagar Loeub
  • 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: 06.07.2018
Exam - Moed B: 07.08.2018

Requirements:

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

Course Schedule

# Date Given by Title Material Note
1 07.03.2018 Dr. Armon, Dr. Waks Introduction to Data Science, Data Understanding [ppt1] [ppt2]
2 14.03.2018 Dr. Waks Feature Selection [ppt]
3 21.03.2018 Slava Novgorodov Recitation #1 [ppt][code] HW #1 [pdf][ipynb], until 25.04.2018
4 11.04.2018 Dr. Faivishevsky Data Modeling #1 [ppt]
5 25.04.2018 Dr. Faivishevsky Data Modeling #2 [ppt]
6 02.05.2018 Slava Novgorodov Recitation #2 [ppt][code] HW #2 [pdf][ipynb], until 23.05.2018
7 09.05.2018 Hagar Loeub Introduction to Deep Learning [pdf]
8 16.05.2018 Tomer Levy Big Data - HDFS [pdf]
9 23.05.2018 Slava Novgorodov Recitation #3 [ppt][code]
10 30.05.2018 Prof. Milo Big Data - MapReduce [pdf1] [pdf2]
11 06.06.2018 Prof. Milo Big Data - Spark [pdf1] [pdf2]
12 13.06.2018 Slava Novgorodov Recitation #4 [ppt][code] HW #3 [pdf], until 27.06.2018
13 13.06.2018 Slava Novgorodov Summary [ppt] Sample exam A, Sample exam B