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.
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
All the material is available in Moodle.
# | 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 |