Video

Introduction to Robotics

Collection: 
openAcademy
Author: 
Oussama Khatib
Year: 
0
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
Media Format: 
Material Type: 
Description: 
The purpose of this course is to introduce you to basics of modelling, design, planning, and control of robot systems. In essence, the material treated in this course is a brief survey of relevant results from geometry, kinematics, statics, dynamics, and control.The course is presented in a standard format of lectures, readings and problem sets. Topics include: robotics foundations in kinematics, dynamics, control, motion planning, trajectory generation, programming and design. Prerequisites: matrix algebra.

iPhone Application Programming

Collection: 
OpenAcademy
Author: 
Evan Doll, Alan Cannistraro
Year: 
2014
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
Media Format: 
Material Type: 
Description: 
Tools and APIs required to build applications for the iPhone platform using the iPhone SDK. User interface designs for mobile devices and unique user interactions using multi-touch technologies. Object-oriented design using model-view-controller pattern, memory management, Objective-C programming language. iPhone APIs and tools including Codex, Interface Builder and Instruments on Mac OS X. Other topics include: core animation, bonjour networking, mobile device power management and performance considerations.

iPad and iPhone Application Development

Collection: 
openAcademy
Author: 
Paul Hegarty
Year: 
2014
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
Media Format: 
Material Type: 
Description: 
Tools and APIs required to build applications for the iPhone and iPad platform using the iOS SDK. User interface designs for mobile devices and unique user interactions using multi-touch technologies. Object-oriented design using model-view-controller paradigm, memory management, Objective-C programming language. Other topics include: object-oriented database API, animation, multi-threading and performance considerations.

C9 Lectures: Introduction to Algorithms and Computational Complexity (Yuri Gurevich)

Collection: 
C9 Lectures
Author: 
Yuri Gurevich
Year: 
2010
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
Media Format: 
Material Type: 
Description: 
Introduction to Algorithms and Computational Complexity,

C9 Lectures: Introduction to Algorithms and Computational Complexity (Yuri Gurevich)

Collection: 
C9 Lectures
Author: 
Yuri Gurevich
Year: 
2010
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
Media Format: 
Material Type: 
Description: 
Introduction to Algorithms and Computational Complexity,

C9 Lectures: Introduction to Algorithms and Computational Complexity (Yuri Gurevich)

Collection: 
C9 Lectures
Author: 
Yuri Gurevich
Year: 
2010
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
Media Format: 
Material Type: 
Description: 
Introduction to Algorithms and Computational Complexity,

Machine Learning

Collection: 
openAcademy
Author: 
Yaser Abu Mostafa
Year: 
2014
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
Media Format: 
Material Type: 
Description: 
This is an introductory course on machine learning that covers the basic theory, algorithms, and applications. Machine learning (ML) enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML techniques are widely applied in engineering, science, finance, and commerce to build systems for which we do not have full mathematical specification (and that covers a lot of systems). The course balances theory and practice, and covers the mathematical as well as the heuristic aspects.

Machine Learning

Collection: 
openAcademy
Author: 
Andrew Ng
Year: 
2014
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
Media Format: 
Material Type: 
Description: 
This course is offered by Stanford as an online course for credit. It can be taken individually, or as part of a master’s degree or graduate certificate earned online through the Stanford Center for Professional Development.

This course provides a broad introduction to machine learning and statistical pattern recognition.

Topics include: supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, support vector machines); unsupervised learning (clustering, dimensionality reduction, kernel methods); learning theory (bias/variance tradeoffs; VC theory; large margins); reinforcement learning and adaptive control.

Human-Computer Interaction Seminar

Collection: 
openAcademy
Author: 
Terry Winograd
Year: 
2014
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
Media Format: 
Material Type: 
Description: 
This is a seminars on people, computers and design by Stanford university.

Computer Systems Colloquium

Collection: 
openAcademy
Author: 
Year: 
2014
Conditions of Use: 
Attribution-NonCommercial-ShareAlike 3.0 Unported
Media Format: 
Material Type: 
Description: 
The Colloquium is an ongoing guest lecture series touching on many elements of computer systems, the technologies they employ, and the systems they enable.

Pages

Subscribe to Video