Course Information

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

Instructor Information:

Tel Aviv University Intel
  • Dr. Amitai Armon
  • Dr. Itay Lieder
  • Dr. Lev Faivishevsky
  • Hagar Loeub
  • Tomer Levi

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 Dr. 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: 01.08.2019
Exam - Moed B: 20.09.2019

Requirements:

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

Course Schedule

# Date Given by Title Material Note
1 27.02.2019 Dr. Armon, Dr. Lieder Introduction to Data Science, Data Understanding [ppt1] [ppt2]
2 06.03.2019 Dr. Lieder Feature Selection [ppt]
3 13.03.2018 Dr. Novgorodov Recitation #1 [ppt]Code: [original][lesson] HW #1 [pdf][ipynb], until 03.04.2019
4 20.03.2019 Dr. Faivishevsky Data Modeling #1 [ppt]
5 27.03.2019 Dr. Faivishevsky Data Modeling #2 [ppt]
6 03.04.2019 Dr. Novgorodov Recitation #2 [ppt]Code: [original][lesson] HW #2 [pdf][ipynb], until 15.05.2019
7 10.04.2019 Hagar Loeub Introduction to Deep Learning [pdf]
8 01.05.2019 Dr. Novgorodov Recitation #3 [ppt][code]
9 15.05.2019 Tomer Levi Big Data - Overview [pdf]
10 22.05.2019 Prof. Milo Big Data - MapReduce [pdf1] [pdf2]
11 29.05.2019 Prof. Milo Big Data - Spark [pdf1] [pdf2]
12 05.06.2018 Dr. Novgorodov Recitation #4 [ppt][code] HW #3 [pdf], until 27.06.2019
13 12.06.2018 Dr. Novgorodov Summary [ppt] Exam 16/17 Moed A, Exam 16/17 Moed B
Exam 17/18 Moed A, Exam 17/18 Moed B