Free Online Course on Enabling Technologies for Data Science and Analytics
Columbia University is offering free online course on Enabling Technologies for Data Science and Analytics: The Internet of Things. In this data science course, you will learn about the major components of the Internet of Things and how data is acquired from sensors.
Applicants will discover the relationship between Big Data and the Internet of Things (IoT). This course will start on May 15, 2017.
Course At A Glance
Length: 5 weeks
Effort: 7-10 hours pw
Subject: Data Analysis & Statistics
Institution: Columbia University and edx
Languages: English
Price: Free
Certificate Available: Yes, Add a Verified Certificate for $149
Session: Course Starts on May 15, 2017
Providers’ Details
Columbia University is one of the world’s most important centers of research and at the same time a distinctive and distinguished learning environment for undergraduates and graduate students in many scholarly and professional fields. The University recognizes the importance of its location in New York City and seeks to link its research and teaching to the vast resources of a great metropolis.
About This Course
The Internet of Things is rapidly growing. It is predicted that more than 25 billion devices will be connected by 2020.
Why Take This Course?
In this data science course, you will learn about the major components of the Internet of Things and how data is acquired from sensors. You will also examine ways of analyzing event data, sentiment analysis, facial recognition software and how data generated from devices can be used to make decisions.
Learning Outcomes
- Networks, protocols and basic software for the Internet of Things (IoT)
- How automated decision and control can be done with IoT technologies
- Discuss devices including sensors, low power processors, hubs/gateways and cloud computing platforms
- Learn about the relationship between data science and natural language and audio-visual content processing
- Study research projects drawn from scientific journals, online media, and novels
- Review fundamental techniques for visual feature extraction, content classification and high-dimensional indexing
- Techniques that can be applied to solve problems in web-scale image search engines, face recognition, copy detection, mobile product search, and security surveillance
- Examine data collection, processing and analysis
Instructors
Kathy McKeown
Henry and Gertrude Rothschild Professor of Computer Science, Columbia University
Zoran Kostic
Associate Professor of Professional Practice & Director of the MS EE Program, Columbia University
Fred Jiang
Assistant Professor in the Electrical Engineering Department, Columbia University
Julia Hirschberg
Percy K. and Vida LW Hudson Professor of Computer Science
Chair of the Department, Computer Science, Columbia University
Michael Collins
Vikram S. Pandit Professor of Computer Science, Columbia University
Shih-Fu Chang
Richard Dicker Chair Professor
Director of the Digital Video and Multimedia Lab
Senior Vice Dean of Engineering School, Columbia University
Requirements
- High school math
- Some exposure to computer programming
How To Join This Course
- Go to the course website link
- Create an edX account to SignUp
- Choose “Register Now” to get started.
- EdX offers honor code certificates of achievement, verified certificates of achievement, and XSeries certificates of achievement. Currently, verified certificates are only available in some courses.
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