Fall 2024 Actuarial Science PS5842 section 001

Advanced Data Science Applications in Fi

Adv Data Sci App in Fin a

Call Number 12267
Day & Time
Location
TR 2:40pm-3:55pm
606 Lewisohn Hall
Points 3
Grading Mode Standard
Approvals Required None
Instructor Yubo Wang
Type LECTURE
Method of Instruction In-Person
Course Description

The Advanced Data Science Applications in Finance and Insurance course covers topics in database navigation, select advanced predictive analytics models and model interpretability. Topics include relational databases, generalized additive models, deep learning models, linear mixed models, Bayesian approaches, and interpretable machine learning.

Course discussions help students develop an understanding of the models and methodologies, as well as the ability to implement these models in R or python using opensource packages. Course assignments help students practice applying these models to financial, insurance and other data, as well as gain additional insights through validating aspects of the models. After taking this course, students will be able to apply these advanced predictive analytics models to financial and insurance data to better inform data-driven decision making by combining their theoretical understanding, domain knowledge and coding skills.

Some topics covered are relevant to the Advanced Topics in Predictive Analytics (ATPA) exam of the Society of Actuaries, and (with a more analytical emphasis) to the quantitative methods section of the CFA Program Level II exam by the CFA Institute.

Familiarity with machine learning models covered in the Data Science in Finance and Insurance course is helpful. Prior exposure to linear algebra, calculus, statistics, and a working knowledge of python, R and spreadsheets are necessary.

Web Site Vergil
Department Actuarial Science
Enrollment 9 students (15 max) as of 9:05PM Monday, December 2, 2024
Subject Actuarial Science
Number PS5842
Section 001
Division School of Professional Studies
Note PRIORITY TO ACTU; OPEN TO CU. IN-PERSON.
Section key 20243ACTU5842K001