Online образование
Материал из Department of Theoretical and Applied Mechanics
Кафедра ТМ > Интересные ссылки > Online образование
Links[править]
Coursera[править]
Online lectures have some advantages over the traditional in-person instruction:
- they allow students to control the pacing of a lecture – they can speed it up or instantly replay the material;
- a large library of online classes could allow students to personalize their education, students could combine many different lecture chunks to create courses tailored to their interests and abilities;
- analytical programs built into the course-hosting system could allow faculty to monitor a course in real time, tracking student progress and adjusting their teaching techniques to maximize effectiveness throughout the quarter.
Online education[править]
Programming[править]
Stanford[править]
Computer Science[править]
- CS 101
- Machine Learning
- Software as a Service
- Human-Computer Interaction
- Natural Language Processing
- Game Theory
- Probabilistic Graphical Models
- Cryptography
- Design and Analysis of Algorithms I
- Computer Security
Entrepreneurship[править]
Medicine[править]
Civil Engineering[править]
Electrical Engr.[править]
Complex Systems[править]
Online lectures[править]
Academic Earth[править]
Subjects[править]
- Art & Architecture
- Astronomy
- Biology
- Business
- Chemistry
- Computer Science
- Economics
- Education
- Electrical Engineering
- Engineering (Except Electrical)
- Entrepreneurship
- Environmental Studies
- History
- International Relations
- Law
- Literature
- Mathematics
- Media Studies
- Medicine & Healthcare
- Online Bachelor's Degrees
- Online Courses for Credit
- Online Master's Degrees
- Online Professional Certificates
- Philosophy
- Physics
- Political Science
- Psychology
- Religious Studies
- Test Preparation
- Writing
Universities[править]
- Berkeley
- Columbia
- Harvard
- Khan Academy
- Maryland
- Michigan
- MIT
- Norwich
- NYU
- Princeton
- Stanford
- UCLA
- UNSW
- USC
- Yale
Stanford[править]
YouTube channel of Stanford
Stanford Engineering Everywhere (SEE) programming includes one of Stanford’s most popular engineering sequences: the three-course Introduction to Computer Science taken by the majority of Stanford undergraduates, and seven more advanced courses in artificial intelligence and electrical engineering.
Subjects[править]
Introduction to Computer Science[править]
Artificial Intelligence[править]
Linear Systems and Optimization[править]
- The Fourier Transform and its Applications EE261
- Introduction to Linear Dynamical Systems EE263
- Convex Optimization I EE364A
- Convex Optimization II EE364B
Additional School of Engineering Courses[править]
- Programming Massively Parallel Processors CS193G
- iPhone Application Programming CS193P
- Seminars and Webinars
Khan Academy[править]
перше число 60 друге - у 3 рази менше за перше а третє - у 4 рази менше за друге Знайти третє число
Audience[править]
| Group 20510/1 | |
|---|---|
| Audience | Course |
| Веренинов Игорь | Machine Learning |
| Dainis Dzenushko | Machine Learning |
| Kovalev Oleg | Design and Analysis of Algorithms I |
| Краморов Данил | CS101 |
| Пшенов Антон | Design and Analysis of Algorithms I |
| Симонов Роман | Machine Learning |
| Степанов Алексей | Design and Analysis of Algorithms I |
| Фролова Ксения | Game Theory |
