海外15所顶级名校名企的机器学习公开课_数据挖掘与数据分析

原创 admin  2017-06-18 00:00 

来自:全球人工智能

一、Stanford University7门

1. 机器学习(Machine Learning)

Stanford University via Coursera

开课时间:3rd Apr, 2017

地址:https://www.class-central.com/mooc/835/coursera-machine-learning

2. 人工智能导论(Intro to Artificial Intelligence)

Stanford University via Udacity

开课时间:完全自主

地址:https://www.class-central.com/mooc/592/udacity-intro-to-artificial-intelligence

3. 机器人学的人工智能(CS 8802, Artificial Intelligence for Robotics: Programming a Robotic Car)

Stanford University via Udacity

开课时间:完全自主

地址:https://www.class-central.com/mooc/1021/udacity-cs-8802-artificial-intelligence-for-robotics-programming-a-robotic-car

4. 机器学习导论(Intro to Machine Learning)

Stanford University via Udacity

 开课时间:完全自主

地址:https://www.class-central.com/mooc/2996/udacity-intro-to-machine-learning

5. 机器人学的人工智能(Artificial Intelligence for Robotics)

Stanford University via Udacity

开课时间:完全自主

地址:https://www.class-central.com/mooc/319/udacity-artificial-intelligence-for-robotics

6. 概率图模型1:表示(Probabilistic Graphical Models 1: Representation)

Stanford University via Coursera

开课时间:24th Apr, 2017

地址:https://www.class-central.com/mooc/309/coursera-probabilistic-graphical-models-1-representation

7. 概率图模型2:推理(Probabilistic Graphical Models 2: Inference)

Stanford University via Coursera

开课时间:10th Apr, 2017

地址:https://www.class-central.com/mooc/7292/coursera-probabilistic-graphical-models-2-inference

 

二、University of California(2门)

1. 大数据导论(Introduction to Big Data)

University of California, San Diego via Coursera

开课时间:3rd Apr, 2017

地址:https://www.class-central.com/mooc/4164/coursera-introduction-to-big-data

2. 大数据机器学习(Machine Learning With Big Data)

University of California, San Diego via Coursera

开课时间:10th Apr, 2017

地址:https://www.class-central.com/mooc/4238/coursera-machine-learning-with-big-data


三、Johns Hopkins University(2门)

1. 收集与清洗数据(Getting and Cleaning Data)

Johns Hopkins University via Coursera

开课时间:3rd Apr, 2017

地址:https://www.class-central.com/mooc/1714/coursera-getting-and-cleaning-data

2. 实践机器学习(Practical Machine Learning)

Johns Hopkins University via Coursera

开课时间:3rd Apr, 2017

地址:https://www.class-central.com/mooc/1719/coursera-practical-machine-learning 

 

四、Google(3门)

1. 谷歌云平台基础:核心架构(Google Cloud Platform Fundamentals: Core Infrastructure)

Google via Coursera

开课时间:3rd Apr, 2017

地址:https://www.class-central.com/mooc/7784/coursera-google-cloud-platform-fundamentals-core-infrastructure

2. 谷歌云平台大数据与机器学习基础(Google Cloud Platform Big Data and Machine Learning Fundamentals)

Google Cloud via Coursera

开课时间:3rd Apr, 2017

地址:https://www.class-central.com/mooc/8234/coursera-google-cloud-platform-big-data-and-machine-learning-fundamentals

3. 深度学习(Deep Learning)

Google via Udacity

开课时间:完全自主

地址:https://www.class-central.com/mooc/5681/udacity-deep-learning

 

五、Brown University(4门)

1. 机器学习:无监督学习(Machine Learning: Unsupervised Learning)

Brown University via Udacity

开课时间:完全自主

地址:https://www.class-central.com/mooc/1848/udacity-machine-learning-unsupervised-learning

2. 机器学习:监督学习(Machine Learning: Supervised Learning)

Brown University via Udacity

开课时间:完全自主

地址:https://www.class-central.com/mooc/1847/udacity-machine-learning-1-supervised-learning

3. 强化学习(Reinforcement Learning)

Brown University via Udacity

开课时间:完全自主

地址:https://www.class-central.com/mooc/1849/udacity-reinforcement-learning

4. 机器学习(Machine Learning)

Brown University via Udacity

开课时间:完全自主

地址:https://www.class-central.com/mooc/3531/udacity-machine-learning

 

六、Microsoft(3门

1. 开发智能Apps 和 Bots(Developing Intelligent Apps and Bots)

Microsoft via edX

开课时间:完全自主

地址:https://www.class-central.com/mooc/6357/edx-developing-intelligent-apps-and-bots

2. 机器学习原则(Principles of Machine Learning)

Microsoft via edX

开课时间:完全自主

地址:https://www.class-central.com/mooc/6511/edx-principles-of-machine-learning

3. 应用机器学习(Applied Machine Learning)

Microsoft via edX

开课时间:完全自主

地址:https://www.class-central.com/mooc/6406/edx-applied-machine-learning

 

七、University of Washington(5门)

1. 机器学习基础:专题研究(Machine Learning Foundations: A Case Study Approach)

University of Washington via Coursera

开课时间:3rd Apr, 2017

地址:https://www.class-central.com/mooc/4352/coursera-machine-learning-foundations-a-case-study-approach

2. 机器学习:回归分析(Machine Learning: Regression)

University of Washington via Coursera

开课时间:3rd Apr, 2017

地址:https://www.class-central.com/mooc/4289/coursera-machine-learning-regression

3. 机器学习:分类(Machine Learning: Classification)

University of Washington via Coursera

开课时间:3rd Apr, 2017

地址:https://www.class-central.com/mooc/4219/coursera-machine-learning-classification

4. 机器学习:聚类&检索(Machine Learning: Clustering & Retrieval)

University of Washington via Coursera

开课时间:3rd Apr, 2017

地址:https://www.class-central.com/mooc/4313/coursera-machine-learning-clustering-retrieval

5. 计算神经科学(Computational Neuroscience)

University of Washington via Coursera

开课时间:10th Apr, 2017

地址:https://www.class-central.com/mooc/449/coursera-computational-neuroscience

 

八、Wesleyan University(1门)

1. 数据分析的机器学习(Machine Learning for Data Analysis)

Wesleyan University via Coursera

开课时间:3rd Apr, 2017

地址:https://www.class-central.com/mooc/4354/coursera-machine-learning-for-data-analysis

 

九、University of Toronto(1门)

1. 机器学习的神经网络(Neural Networks for Machine Learning)

University of Toronto via Coursera

开课时间:17th Apr, 2017

地址:https://www.class-central.com/mooc/398/coursera-neural-networks-for-machine-learning

 

十、University of Michigan(1门)

1. Python机器学习应用(Applied Machine Learning in Python)

University of Michigan via Coursera

开课时间:24th Apr, 2017

地址:https://www.class-central.com/mooc/6673/coursera-applied-machine-learning-in-python

 

十一、Georgia Institute of Technology(4门)

1. 基于知识的AI:认知系统(Knowledge-Based AI: Cognitive Systems)

Georgia Institute of Technology via Udacity

开课时间:完全自主

地址:https://www.class-central.com/mooc/1025/udacity-knowledge-based-ai-cognitive-systems

2. 计算机视觉导论(Introduction to Computer Vision)

Georgia Institute of Technology via Udacity

开课时间:完全自主

地址:https://www.class-central.com/mooc/1022/udacity-introduction-to-computer-vision

3. 高性能计算(High Performance Computing)

Georgia Institute of Technology via Udacity

开课时间:完全自主

地址:https://www.class-central.com/mooc/1028/udacity-high-performance-computing

 4. 贸易上的机器学习(Machine Learning for Trading)

Georgia Institute of Technology via Udacity

开课时间:完全自主

地址:https://www.class-central.com/mooc/1026/udacity-machine-learning-for-trading

 

十二、Columbia University(1门

1. 数据科学与分析的机器学习(Machine Learning for Data Science and Analytics)

Columbia University via edX

开课时间:完全自主

地址:https://www.class-central.com/mooc/4912/edx-machine-learning-for-data-science-and-analytics

 

十三、fast.ai(1门

1. 编程实践深度学习:第一部分(Practical Deep Learning For Coders, Part 1)

fast.ai via Independent)

开课时间:完全自主

地址:https://www.class-central.com/mooc/7887/practical-deep-learning-for-coders-part-1


十四、Massachusetts Institute of Technology(2门

1. 深度学习导论(6.S191: Introduction to Deep Learning)

Massachusetts Institute of Technology via Independent

开课时间:完全自主

地址:https://www.class-central.com/mooc/8083/6-s191-introduction-to-deep-learning

2. 深度学习:无人驾驶(6.S094: Deep Learning for Self-Driving Cars)

Massachusetts Institute of Technology via Independent

开课时间:完全自主

地址:https://www.class-central.com/mooc/8132/6-s094-deep-learning-for-self-driving-cars

 

十五、University of Oxford(1门

1. 深度学习:自然语言处理(Deep Learning for Natural Language Processing)

University of Oxford via Independent

开课时间:完全自主

地址:https://www.class-central.com/mooc/8097/deep-learning-for-natural-language-processing


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