Course Information

  • Location: Melamed 006
  • Time: Wednesday, 10:00 - 13:00

Instructor Information:

Tel Aviv University Intel
  • Dr. Amitai Armon
  • Dr. Itay Lieder
  • Avishai Wagner

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 Dr. Slava Novgorodov) or a 3 hours recitations given by Feras Baransi.
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: 18.07.2023
Exam - Moed B: 24.08.2023

Requirements:

  • Introduction to Probability/Statistics, Algorithms

Course Material:

All the material is available in Moodle.

Course Schedule

# Date Given by Title Note
1 15.03.2023 Avishai Wagner Introduction to Data Science, Data Understanding
2 22.03.2023 Avishai Wagner Feature Selection
3 29.03.2023 Feras Baransi Recitation #1 HW #1 [pdf][ipynb], until 03.05.2023
4 19.04.2022 Dr. Lieder Data Modeling #1
5 03.05.2023 Dr. Lieder Data Modeling #2
6 10.05.2023 Feras Baransi Recitation #2 HW #2 [pdf][ipynb], until 07.06.2023
7 17.05.2023 Dr. Lieder Introduction to Deep Learning
8 24.05.2023 Dr. Novgorodov Big Data - Overview
9 31.05.2023 Feras Baransi Recitation #3
10 07.06.2023 Dr. Novgorodov Big Data - MapReduce
11 14.06.2023 Dr. Novgorodov Big Data - Spark
12 21.06.2023 Feras Baransi Recitation #4 HW #3 [pdf], until 07.07.2023
13 28.06.2023 Dr. Novgorodov Course Summary