UPenn - Big Data and Education
- Offered byedX
Big Data and Education at edX Overview
Big Data and Education
at edX
Upskilling is a better roadmap to success. Enroll in this course to learn critical principles of Big Data through real-life case studies & examples
Duration | 32 hours |
Start from | Start Now |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Intermediate |
Official Website | Go to Website  |
Credential | Certificate |
Big Data and Education at edX Highlights
Big Data and Education
at edX
- 45% got a tangible career benefit from this course
- Earn a certificate of learning on course completion
- Add a Verified Certificate for ?12,920
- This course is offered by University of Pennsylvania
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Big Data and Education at edX Course details
Big Data and Education
at edX
Skills you will learn
What are the course deliverables?
- Knowledge and application of MapReduce
- Understanding the rate of occurrences of events in big data
- How to design algorithms for stream processing and counting of frequent elements in Big Data
- Understand and design PageRank algorithms
- Understand underlying random walk algorithms
More 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. You'll also gain experience with standard data mining methods frequently applied to educational data. You will learn how to apply these methods and when to apply them, as well as their strengths and weaknesses for different applications
- 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 in Python or using software tools like RapidMiner. We will also discuss validity and generalizability; establishing how trustworthy and applicable the analysis results.
Big Data and Education at edX Curriculum
Big Data and Education
at edX
Section 1: The basics of working with big data
Section 2: Web and social networks
Section 3: Clustering big data
Section 4: Google web search
Section 5: Parallel and distributed computing using MapReduce
Section 6: Computing similar documents in big data
Section 7: Products frequently bought together in stores
Section 8: Movie and music recommendations
Section 9: Google's AdWordsTM System
Section 10: Mining rapidly arriving data streams
Big Data and Education at edX Admission Process
Big Data and Education
at edX
Important Dates
May 25, 2024
Course Commencement Date
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Big Data and Education
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