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Fundamentals of Quantitative Modeling
Course
en
English
Subtitles available
4 h
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- Self-paced
- Free Access
- Fee-based Certificate
- 4 Sequences
- Introductive Level
- Subtitles in Russian
Course details
Syllabus
- Week 1 - Module 1: Introduction to Models
In this module, you will learn how to define a model, and how models are commonly used. You’ll examine the central steps in the modeling process, the four key mathematical functions used in models, and the essential vocabulary used to describe models. By the e... - Week 2 - Module 2: Linear Models and Optimization
This module introduces linear models, the building block for almost all modeling. Through close examination of the common uses together with examples of linear models, you’ll learn how to apply linear models, including cost functions and production functions t... - Week 3 - Module 3: Probabilistic Models
This module explains probabilistic models, which are ways of capturing risk in process. You’ll need to use probabilistic models when you don’t know all of your inputs. You’ll examine how probabilistic models incorporate uncertainty, and how that uncertainty co... - Week 4 - Module 4: Regression Models
This module explores regression models, which allow you to start with data and discover an underlying process. Regression models are the key tools in predictive analytics, and are also used when you have to incorporate uncertainty explicitly in the underlying ...
Prerequisite
None.
Instructors
Richard Waterman
Professor of Statistics
Statistics-Wharton School
Editor
The University of Pennsylvania (commonly known as Penn), founded in 1740, is a private university located in Philadelphia, Pennsylvania, USA. A member of the Ivy League, Penn is the fourth oldest institution of higher learning in the United States and considers itself the first university in the United States to offer both undergraduate and graduate degrees.
Platform
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