The University of Pennsylvania is offering free online course on Big Data and Education. This course requires applicants to have basic knowledge of statistics, data mining, mathematical modeling, or algorithms.
In this four week course, applicants will learn the methods and strategies for using large-scale educational data to improve education and make discoveries about learning. This course will start on April 2, 2018.
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( votes)Course At A Glance
Length: 8 weeks
Effort: 6-12 hours pw
Subject: Data Analysis and statistics
Institution: University of Pennsylvania and edx
Languages: English
Price: Free
Certificate Available: Yes, Add a Verified Certificate for $49
Session: Course Starts on April 2, 2018
Providers’ Details
The University of Pennsylvania is an Ivy League institution with 12 undergraduate, graduate and professional schools in Philadelphia, serving a diverse community of more than 20,000 students from around the world. Ranked consistently among the top ten universities in the United States, Penn dates its founding to 1740 and is often considered the first university to offer both graduate and undergraduate studies.
About This Course
Online and software-based learning tools have been used increasingly in education. This movement has resulted in an explosion of data, which can now be used to improve educational effectiveness and support basic research on learning.
In this course, you will learn how and when to use key methods for educational data mining and learning analytics on this data. You will examine the methods being developed by researchers in the educational data mining, learning analytics, learning-at-scale, student modeling, and artificial intelligence communities.
Why Take This Course?
The course will discuss how to use each method to answer education research questions, and to drive intervention and improvement in educational software and systems. Methods will be covered at a theoretical level, and in terms of learning how to apply them using software tools like RapidMiner. We will also discuss validity and generalizability; establishing how trustworthy and applicable the analysis results.
Learning Outcomes
- Key methods for educational data mining
- How to apply methods using standard tools such as RapidMiner
- How to use methods to answer practical educational questions
Instructors
Ryan Baker
Ryan Baker is Associate Professor at the University of Pennsylvania, and Director of the Penn Center for Learning Analytics. His lab conducts research on engagement and robust learning within online and blended learning, seeking to find actionable indicators that can be used today but that predict future student outcomes.
Requirements
Basic knowledge of statistics, data mining, mathematical modeling, or algorithms is recommended. Experience with programming is not required.
How To Join This Course
- Go to the course website link
- Create an edX account to SignUp
- Choose “Register Now” to get started.
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