Course Information

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

Instructor Information:

Tel Aviv University Intel
  • Dr. Amitai Armon
  • Dr. Itay Lieder
  • Avishai Wagner
  • 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 recitations 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: 04.08.2020
Exam - Moed B: 22.09.2020

Requirements:

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

Course Material:

All the material is available in Moodle.

Course Schedule

# Date Given by Title Note
1 11.03.2020 Dr. Lieder Introduction to Data Science, Data Understanding
2 18.03.2020 Dr. Lieder Feature Selection
3 25.03.2020 Dr. Novgorodov Recitation #1 HW #1 [pdf][ipynb], until 22.04.2020
4 01.04.2020 Avishai Wagner Data Modeling #1
5 22.04.2020 Avishai Wagner Data Modeling #2
6 06.05.2020 Dr. Novgorodov Recitation #2 HW #2 [pdf][ipynb], until 31.05.2020
7 13.05.2020 Hagar Loeub Introduction to Deep Learning
8 20.05.2020 Tomer Levi Big Data - Overview
9 27.05.2020 Dr. Novgorodov Recitation #3
10 03.06.2020 Prof. Milo Big Data - MapReduce
11 10.06.2020 Prof. Milo Big Data - Spark
12 17.06.2020 Dr. Novgorodov Recitation #4 HW #3 [pdf], until 27.06.2020
13 24.06.2020 Dr. Novgorodov Course Summary