The Data Mining Specialization teaches data mining techniques for both structured data which conform to a clearly defined schema, and unstructured data which exist in the form of natural language text. Specific course topics include pattern discovery, clustering, text retrieval, text mining and analytics, and data visualization. The Capstone project task is to solve real-world data mining challenges using a restaurant review data set from Yelp.
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This was my favorite course in the whole specialization. Everything is explained very concisely and clearly making the subject matter very easy to understand.
It is an excellent course under data mining specialization. Going for it will be definitely a great investment in terms of education.\n\nTeddy Muchape.
Excellent ! Well organized, presented with aptitude to detail. Definitely will recommend and take further units in this specialization.\n\nThanks Prof
The project help me to practice the whole specialization algorithms and techniques.
seemed to me the best course of the specialization
Excellent course, the pipeline they propose to help you understand text mining is quite helpful. It has an important introduction to the most key concepts and techniques for text mining and analytics.
The content of Text Mining and Analytics is very comprehensive and deep. More practise about how formula works would be better. Quiz could be not tough to be completed after attending every lectures.
This is a very good course. I think it provides a very good foundation of text mining and analytics like PLSA and LDA. More advanced research discussed in the last lecture is also very interesting.
此课程是 100% 在线学习吗？是否需要现场参加课程？
Time to completion can vary widely based on your schedule. Most learners are able to complete the Specialization in 4-5 months.
Each course in the Specialization is offered on a regular schedule with sessions starting about once per month. If you don't complete a course on the first try, you can easily transfer to the next session, and your completed work and grades will carry over.
What background knowledge is necessary?
Comfortable with computer programming in multiple programming languages
Basic knowledge of probability and statistics
Do I need to take the courses in a specific order?
It is recommended that the courses in the Specialization be taken in the order outlined. In the Capstone Project, you will have the opportunity to synthesize your learning in all the courses and apply your combined skills in a final project.
MCS courses in Coursera do not carry University of Illinois credit on their own. Each course has an enhanced for-credit component. You can earn academic credit if you combine an MCS Coursera course with the enhanced for-credit component offered on the University of Illinois platform. Some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.
What will I be able to do upon completing the Specialization?
At completion of this Specialization in Data Mining, you will (1) know the basic concepts in pattern discovery and clustering in data mining, information retrieval, text analytics, and visualization, (2) understand the major algorithms for mining both structured and unstructured text data, and (3) be able to apply the learned algorithms to solve real-world data mining problems.