About this Course
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Approx. 10 hours to complete

Suggested: 4 weeks of study, 1-3 hours/week...

English

Subtitles: English, Russian

Skills you will gain

ModelingLinear RegressionProbabilistic ModelsRegression Analysis

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 10 hours to complete

Suggested: 4 weeks of study, 1-3 hours/week...

English

Subtitles: English, Russian

Syllabus - What you will learn from this course

Week
1
2 hours to complete

Module 1: Introduction to Models

7 videos (Total 72 min), 1 reading, 1 quiz
7 videos
1.2 Definition and Uses of Models, Common Functions14m
1.3 How Models Are Used in Practice10m
1.4 Key Steps in the Modeling Process7m
1.5 A Vocabulary for Modeling8m
1.6 Mathematical Functions20m
1.7 Summary4m
1 reading
PDF of Lecture Slides10m
1 practice exercise
Module 1: Introduction to Models Quiz20m
Week
2
2 hours to complete

Module 2: Linear Models and Optimization

6 videos (Total 69 min), 1 reading, 1 quiz
6 videos
2.2 Growth in Discrete Time7m
2.3 Constant Proportionate Growth12m
2.4 Present and Future Value15m
2.5 Optimization13m
2.6 Summary2m
1 reading
PDF of Lecture Slides10m
1 practice exercise
Module 2: Linear Models and Optimization Quiz20m
Week
3
2 hours to complete

Module 3: Probabilistic Models

12 videos (Total 83 min), 1 reading, 1 quiz
12 videos
3.2 Examples of Probabilistic Models2m
3.3 Regression Models4m
3.4 Probability Trees5m
3.5 Monte Carlo Simulations6m
3.6 Markov Chain Models6m
3.7 Building Blocks of Probability Models9m
3.8 The Bernoulli Distribution7m
3.9 The Binomial Distribution16m
3.10 The Normal Distribution5m
3.11 The Empirical Rule7m
3.12 Summary2m
1 reading
PDF of Lecture Slides10m
1 practice exercise
Module 3: Probabilistic Models Quiz20m
Week
4
2 hours to complete

Module 4: Regression Models

8 videos (Total 70 min), 1 reading, 1 quiz
8 videos
4.2 Use of Regression Models15m
4.3 Interpretation of Regression Coefficients4m
4.4 R-squared and Root Mean Squared Error (RMSE)12m
4.5 Fitting Curves to Data8m
4.6 Multiple Regression7m
4.7 Logistic Regression8m
4.8 Summary of Regression Models4m
1 reading
PDF of Lecture Slides10m
1 practice exercise
Module 4: Regression Models Quiz20m
4.6
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Top reviews from Fundamentals of Quantitative Modeling

By APJun 16th 2019

Very clear and articulate explanation of the concepts. He doesn't skip a step in the sequencing ideas, drawing comparisons and differences, and illustrating both visually and story-telling. Excellent.

By NCJul 31st 2019

Very nice course for beginner, the mathematic level is not high (around french baccalaureat) so available to everyone. I enjoyed a lot this course that show how simple math can be used in real life.

Instructor

Avatar

Richard Waterman

Professor of Statistics
Statistics-Wharton School

About University of Pennsylvania

The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies. ...

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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