Perform text analysis, discover patterns, and visualize data. Develop skills to solve practical challenges in data mining.
Suggested by: Coursera (What is Coursera?)
No prior knowledge required
No unnecessary risks
The data mining specialization teaches data mining techniques for structured data that conforms to a clear schema, and unstructured data that appears in the form of natural language text.
The final project task is to solve real-world data mining challenges using a restaurant review dataset from Yelp.
Courses 2-5 of this specialization constitute the coursework portion of the Master of Science in Computer Science in Data Science program. You can apply to the degree program before or after starting the specialization.
Duration: 15 hours
Rating: 4.5 (1,370 ratings)
This course will teach you how to create more effective data visualizations. You will learn new ways to present data using fundamental principles of design and human understanding.
Duration: 30 hours
Rating: 4.5 (949 ratings)
This course will include search engine technologies, which play a significant role in all data mining applications involving textual data.
Duration: 33 hours
Rating: 4.5 (726 ratings)
This course will cover the important techniques for mining and analyzing text data to discover interesting patterns and support decision-making.
Duration: 17 hours
Rating: 4.3 (318 ratings)
Learn the general concepts of data mining with basic methodologies and applications.
Duration: 16 hours
Rating: 4.5 (406 ratings)
Discover the basic concepts of cluster analysis, and learn about typical methods and algorithms.
Duration: 10 hours
Rating: 4.5 (45 ratings)
This course will allow you to apply the data mining algorithms and techniques you learned in previous courses.
By working on these tasks, you will gain experience in a typical data mining flow that includes data processing, data exploration, data analysis, and results presentation.
