Instructor Insights

Instructor Insights pages are part of the OCW Educator initiative, which seeks to enhance the value of OCW for educators.

Course Overview

This page focuses on the course 15.097 Prediction: Machine Learning and Statistics as it was taught by Professor Cynthia Rudin in Spring 2012.

This introductory course provides a selection of the most important topics from the subjects of machine learning and statistical methods.

Course Outcomes

Course Goals for Students

  • Gain a foundational understanding of how machine learning and statistical algorithms work
  • Explore statistical learning theory, which provides the mathematical foundation for machine learning algorithms
  • Learn about Bayesian analysis
  • Leave the course with a toolbox of algorithms that can be used on students’ own datasets

Possibilities for Further Study/Careers

15.097 prepares students for more in-depth study in fields involving predictive modeling.

Curriculum Information

Prerequisites

  • Permission of instructor.
  • Knowledge of MATLAB® may be helpful.

Offered

This course was offered once in Spring 2012.

 

Instructor Insights

In the following paper, Professor Cynthia Rudin describes various aspects of how she taught 15.097 Prediction: Machine Learning and Statistics. Topics include the organizational structure of the course and the strategy of using of large-font lecture notes. 

Teaching "Prediction: Machine learning and Statistics” (PDF)

The Classroom

  • Classroom with 5 tired and curved rows of tables. Red chairs positioned behind the tables. Three sliding chalkboards at the front of the room.

    Room 1 of 1

    Lecture

    Lectures were held in a classroom with tiered seating, AV equipment, and sliding chalkboards.

 

Assessment

The students' grades were based on the following activities:

The color used on the preceding chart which represents the percentage of the total grade contributed by problem sets. 50% Problem sets
The color used on the preceding chart which represents the percentage of the total grade contributed by course project proposal. 10% Course project proposal
The color used on the preceding chart which represents the percentage of the total grade contributed by course project advertisement. 2% Course project advertisement
The color used on the preceding chart which represents the percentage of the total grade contributed by course project paper and talk. 38% Course project paper and talk

Student Information

36 students took this course when it was offered in Spring 2012.

Breakdown by Year

Mostly graduate students

Breakdown by Major

Predominantly students from the Operations Research Center

Typical Student Background

Students had a general background in mathematics. Topics from machine learning and statistical methods were new to them. 

 

 

How Student Time Was Spent

During an average week, students were expected to spend 12 hours on the course, roughly divided as follows:

Lecture

3 hours per week
  • Met 2 times per week for 1.5 hours per session; 25 sessions total.
  • Lectures based on notes (distributed in class and through the course webpage), with some additional materials, such as source papers or excerpts from textbooks
  • Student project talks scheduled during the last two weeks of the class
 

Out of Class

9 hours per week
  • Problem sets
  • Course projects
 

Semester Breakdown

WEEK M T W Th F
1 No classes throughout MIT. No session scheduled. Lecture was scheduled for this session. No session scheduled. No session scheduled.
2 Lecture was scheduled for this session. No session scheduled. Lecture was scheduled for this session. No session scheduled. No session scheduled.
3 No classes throughout MIT. No session scheduled. Lecture was scheduled for this session. No session scheduled. No session scheduled.
4 Lecture was scheduled for this session. No session scheduled. Lecture was scheduled for this session. No session scheduled. No session scheduled, but an assignment was due on this date.
5 Lecture was scheduled for this session. No session scheduled. Lecture was scheduled for this session. No session scheduled. No session scheduled.
6 Lecture was scheduled for this session. No session scheduled. Lecture was scheduled for this session. No session scheduled. No session scheduled.
7 Lecture was scheduled for this session. No session scheduled. Lecture was scheduled for this session. No session scheduled. No session scheduled, but an assignment was due on this date.
8 No classes throughout MIT. No classes throughout MIT. No classes throughout MIT. No classes throughout MIT. No classes throughout MIT.
9 Lecture was scheduled for this session. No session scheduled. Lecture was scheduled for this session. No session scheduled. No session scheduled.
10 Lecture was scheduled for this session with a project due on this date. No session scheduled. Lecture was scheduled for this session. No session scheduled. No session scheduled.
11 No classes throughout MIT. No classes throughout MIT. Lecture was scheduled for this session. No session scheduled. No session scheduled, but an assignment was due on this date.
12 Lecture was scheduled for this session. No session scheduled. Lecture was scheduled for this session with a project due on this date. No session scheduled. No session scheduled.
13 Lecture was scheduled for this session. No session scheduled, but a project was due on this date. Student project advertisements presented was scheduled for this session. No session scheduled. No session scheduled.
14 Student project talk was scheduled for this session with a problem set due at this date. No session scheduled. Student project talk was scheduled for this session. No session scheduled. No session scheduled.
15 Student project talk was scheduled for this session. No session scheduled. Student project talk was scheduled for this session. No session scheduled, but a project was due on this date. No classes throughout MIT.
16 No classes throughout MIT. No classes throughout MIT. No classes throughout MIT. No classes throughout MIT. No classes throughout MIT.
Displays the color and pattern used on the preceding table to indicate dates when classes are not held at MIT. No classes throughout MIT
Displays the color used on the preceding table to indicate dates when seminars are held. Lecture session
Displays the color used on the preceding table to indicate dates when small group presentations are held.Student project talks
Displays the color used on the preceding table to indicate date when guest discussion is held. Project due date
Displays the color used on the preceding table to indicate dates when no class session is scheduled. No class session scheduled
Displays the color used on the preceding table to indicate dates when debate is held. Student project advertisements presented
Displays the symbol used on the preceding table to indicate due dates. Problem set due date