Browse Lessons

Class 10 Video: Equivalence and Intervals (I); Hierarchies (IV)

Class 24 Video: Algorithmic Composition (II)

Video 3c: How to Approach the Problem Sets

Class 2 Video: Representation of Notes, Pitches, and Durations

Video 22a: Chord Review and 13 Chords: Some Problems with Roots

Class 11 Video: Equivalence and Intervals (II) and Filters  in music21

Video 9b: Introduction to MusicXML

Video 3b: Pitch Representation: Pros, Cons, and Stakeholders

Video 9a: Music Information Retrieval (MIR): Sound to Score and Music Theory

Class 1 Video: How Do Computers "Hear" Music?

Class 25 Video: Algorithmic Composition (III)

Class 23 Video: Algorithmic Composition

Video 29a: Feature Extraction and Machine Learning (III): Artificial Intelligence

Class 31 Video: Music Visualization and Optical Music Recognition

AI + Open Education Initiative: AI Literacies and Evaluation

AI + Open Education Initiative: Professional Education and the Judicious Use of AI

Video 9: All There Is to Unlearn - MIT Innovation Teams

Video 5: Prototype Problems Not Products - MIT Innovation Teams

Video 1: Congratulations, You Are a Terrible Robot - MIT Innovation Teams

Video 3: Technology Isn’t What You Think It Is - MIT Innovation Teams

Introduction: How to Move Technologies from Lab to Impact - MIT Innovation Teams

Video 2: All Great Ideas Start Out Bad - MIT Innovation Teams

Video 7: Lessons From a Real Garage - MIT Innovation Teams

Video 10: Go Combinatorial - MIT Innovation Teams

Video 6: Don’t Start Small, Start With What You Have - MIT Innovation Teams

Video 4: Problems Are Not Catastrophes - MIT Innovation Teams

Video 8: Are You Sure That’s a Risk? - MIT Innovation Teams

07. EdTech Before the Internet

09. Massive Open Online Courses (MOOCs)

10. Intelligent Tutors

14. Learning Games

16. Start-Up and the Curse of the Familiar

20. The Toxic Power of Data and Experiment

12. Interest-Driven Learning

03. How People Learn: Situated Learning

02. How People Learn: Cognitive Load Theory

18. Trap of Routine Assessment

Lecture 9: Strategy, Skill, and Chance, Part 2

Lecture 12: Knowing Your Players

Lecture 2: Iterative Design

Lecture 19: Abstraction and Simulation

Lecture 4: Prototyping

Lecture 32: Live Action Games

Lecture 33: Ethics in Games

Lecture 31: Assignment 3 Brainstorming and Team Formation

Lecture 30: Clients for Assignment 3 Visit

Lecture 27: Games as Art

Lecture 25: Fiction and Stories in Games