The Course Covers Practical Aspects of Predictive Analytics in The Financial Domain With Emphasis On Models of Risk, Pension, Real Estate, Insurance, Fraud, and Behavioral. Learning Outcomes# At The End of The Course The Student Will Be Able To# 1. Apply Fundamental Concepts in Financial Technologies (fintech). 2. Execute Prediction Models in Field of Finance.

Faculty: Data and Decision Sciences
|Undergraduate Studies |Graduate Studies
Pre-required courses

96411 - Machine Learning 1

Semestrial Information

Weekly Hours

3 Academic Credit • 2 Lecture Hours • 1 Discussion Hours • 1 Project Hours

Responsible(s)

Achikam Ben Artzi

Notes
  • ההרצאות בקורס יועברו באופן מקוון.
  • התרגולים יועברו פרונטלית.

Registration Groups
11
Lecture Wednesday 14:30 - 16:30 נהול 216 | Achikam Ben Artzi
Exercise Wednesday 16:30 - 17:30 נהול 216
12
Lecture Wednesday 14:30 - 16:30 נהול 216 | Achikam Ben Artzi
Exercise Tuesday 12:30 - 13:30 נהול 215
Weekly Hours

3 Academic Credit • 2 Lecture Hours • 1 Discussion Hours • 1 Project Hours

Responsible(s)

Achikam Ben Artzi

Notes
  • ההרצאה תועבר בזום

Registration Groups
11
Lecture Wednesday 14:30 - 16:30 נהול 112 | Achikam Ben Artzi
Exercise Wednesday 16:30 - 17:30 נהול 112 | Sagi Levy
12
Lecture Wednesday 14:30 - 16:30 נהול 112 | Achikam Ben Artzi
Exercise Tuesday 10:30 - 11:30 נהול 216 | Ofri Hefetz
Weekly Hours

3 Academic Credit • 2 Lecture Hours • 1 Discussion Hours • 1 Project Hours

Responsible(s)

Achikam Ben Artzi


Registration Groups
11
Lecture Tuesday 15:30 - 17:30 נהול 112 | Achikam Ben Artzi
Exercise Tuesday 17:30 - 18:30 נהול 112