Analyze Text, Discover Patterns, Visualize Data. Solve real-world data mining challenges.

4.5

stars

3,284 ratings

John C. Hart +2 more instructors

Offered By

Part of the Master in Computer Science degree

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Data Mining SpecializationUniversity of Illinois at Urbana-Champaign

Skills you will gain

Data Clustering AlgorithmsText MiningData Visualization (DataViz)Data MiningData Visualization SoftwareTableau SoftwareData VirtualizationInformation Retrieval (IR)Document RetrievalMachine LearningRecommender SystemsProbabilistic Models

About this Specialization

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. Courses 2 - 5 of this Specialization form the lecture component of courses in the online Master of Computer Science Degree in Data Science. You can apply to the degree program either before or after you begin the Specialization.

Learner Career Outcomes

33%

Started a new career after completing this specialization.

33%

Got a pay increase or promotion.

Shareable Certificate

Earn a Certificate upon completion

100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Intermediate Level

Some related experience required.

Approximately 8 months to complete

Suggested pace of 4 hours/week

English

Subtitles: English, Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Spanish

Learner Career Outcomes

33%

Started a new career after completing this specialization.

33%

Got a pay increase or promotion.

Shareable Certificate

Earn a Certificate upon completion

100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Intermediate Level

Some related experience required.

Approximately 8 months to complete

Suggested pace of 4 hours/week

English

Subtitles: English, Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Spanish

There are 6 Courses in this Specialization

Course1

Course 1

Data Visualization

4.5

stars

1,176 ratings

•

274 reviews

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for pattern-based classification and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns.

Course2

Course 2

Text Retrieval and Search Engines

4.5

stars

791 ratings

•

173 reviews

Recent years have seen a dramatic growth of natural language text data, including web pages, news articles, scientific literature, emails, enterprise documents, and social media such as blog articles, forum posts, product reviews, and tweets. Text data are unique in that they are usually generated directly by humans rather than a computer system or sensors, and are thus especially valuable for discovering knowledge about people’s opinions and preferences, in addition to many other kinds of knowledge that we encode in text.

This course will cover search engine technologies, which play an important role in any data mining applications involving text data for two reasons. First, while the raw data may be large for any particular problem, it is often a relatively small subset of the data that are relevant, and a search engine is an essential tool for quickly discovering a small subset of relevant text data in a large text collection. Second, search engines are needed to help analysts interpret any patterns discovered in the data by allowing them to examine the relevant original text data to make sense of any discovered pattern. You will learn the basic concepts, principles, and the major techniques in text retrieval, which is the underlying science of search engines.

Course3

Course 3

Text Mining and Analytics

4.5

stars

624 ratings

•

137 reviews

This course will cover the major techniques for mining and analyzing text data to discover interesting patterns, extract useful knowledge, and support decision making, with an emphasis on statistical approaches that can be generally applied to arbitrary text data in any natural language with no or minimum human effort.

Detailed analysis of text data requires understanding of natural language text, which is known to be a difficult task for computers. However, a number of statistical approaches have been shown to work well for the "shallow" but robust analysis of text data for pattern finding and knowledge discovery. You will learn the basic concepts, principles, and major algorithms in text mining and their potential applications.

Course4

Course 4

Pattern Discovery in Data Mining

4.3

stars

292 ratings

•

54 reviews

Learn the general concepts of data mining along with basic methodologies and applications. Then dive into one subfield in data mining: pattern discovery. Learn in-depth concepts, methods, and applications of pattern discovery in data mining. We will also introduce methods for data-driven phrase mining and some interesting applications of pattern discovery. This course provides you the opportunity to learn skills and content to practice and engage in scalable pattern discovery methods on massive transactional data, discuss pattern evaluation measures, and study methods for mining diverse kinds of patterns, sequential patterns, and sub-graph patterns.

Instructors

Offered by

University of Illinois at Urbana-Champaign

The University of Illinois at Urbana-Champaign is a world leader in research, teaching and public engagement, distinguished by the breadth of its programs, broad academic excellence, and internationally renowned faculty and alumni. Illinois serves the world by creating knowledge, preparing students for lives of impact, and finding solutions to critical societal needs.

Start working towards your Master's degree

This specialization is part of the 100% online Master in Computer Science from University of Illinois at Urbana-Champaign. If you are admitted to the full program, your courses count towards your degree learning.

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Frequently Asked Questions

What is the refund policy?
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Can I just enroll in a single course?
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.
Can I take the course for free?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
Is this course really 100% online? Do I need to attend any classes in person?
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
How long does it take to complete the Specialization?
Time to completion can vary widely based on your schedule. Most learners are able to complete the Specialization in 4-5 months.
How often is each course in the Specialization offered?
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.
Will I earn university credit for completing the Specialization?
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.

More questions? Visit the Learner Help Center.

Data Mining Specialization

Skills you will gain

About this Specialization

There are 6 Courses in this Specialization