About this Course
4.3
149 ratings
32 reviews
Specialization

Course 5 of 6 in the

100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Hours to complete

Approx. 16 hours to complete

Suggested: 9 hours/week...
Available languages

English

Subtitles: English...

Skills you will gain

Cluster AnalysisData Clustering AlgorithmsK-Means ClusteringHierarchical Clustering
Specialization

Course 5 of 6 in the

100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Hours to complete

Approx. 16 hours to complete

Suggested: 9 hours/week...
Available languages

English

Subtitles: English...

Syllabus - What you will learn from this course

Week
1
Hours to complete
1 hour to complete

Course Orientation

You will become familiar with the course, your classmates, and our learning environment. The orientation will also help you obtain the technical skills required for the course....
Reading
1 video (Total 7 min), 3 readings, 1 quiz
Video1 video
Reading3 readings
Syllabus10m
About the Discussion Forums10m
Social Media10m
Quiz1 practice exercise
Orientation Quiz10m
Hours to complete
2 hours to complete

Module 1

...
Reading
13 videos (Total 65 min), 2 readings, 2 quizzes
Video13 videos
1.2. Applications of Cluster Analysis2m
1.3 Requirements and Challenges5m
1.4 A Multi-Dimensional Categorization2m
1.5 An Overview of Typical Clustering Methodologies6m
1.6 An Overview of Clustering Different Types of Data6m
1.7 An Overview of User Insights and Clustering3m
2.1 Basic Concepts: Measuring Similarity between Objects3m
2.2 Distance on Numeric Data Minkowski Distance7m
2.3 Proximity Measure for Symetric vs Asymmetric Binary Variables4m
2.4 Distance between Categorical Attributes Ordinal Attributes and Mixed Types4m
2.5 Proximity Measure between Two Vectors Cosine Similarity2m
2.6 Correlation Measures between Two variables Covariance and Correlation Coefficient13m
Reading2 readings
Lesson 1 Overview10m
Lesson 2 Overview10m
Quiz2 practice exercises
Lesson 1 Quiz8m
Lesson 2 Quiz12m
Week
2
Hours to complete
5 hours to complete

Week 2

...
Reading
15 videos (Total 78 min), 3 readings, 2 quizzes
Video15 videos
3.2 K-Means Clustering Method9m
3.3 Initialization of K-Means Clustering4m
3.4 The K-Medoids Clustering Method6m
3.5 The K-Medians and K-Modes Clustering Methods6m
3.6 Kernel K-Means Clustering8m
4.1 Hierarchical Clustering Methods1m
4.2 Agglomerative Clustering Algorithms8m
4.3 Divisive Clustering Algorithms3m
4.4 Extensions to Hierarchical Clustering3m
4.5 BIRCH: A Micro-Clustering-Based Approach7m
ClusterEnG Overview5m
ClusterEnG: K-Means and K-Medoids3m
ClusterEnG Application: AGNES4m
ClusterEnG Application: DBSCAN2m
Reading3 readings
Lesson 3 Overview10m
Lesson 4 Part 1 Overview10m
ClusterEnG Introduction10m
Quiz1 practice exercise
Lesson 3 Quiz10m
Week
3
Hours to complete
1 hour to complete

Week 3

...
Reading
9 videos (Total 53 min), 2 readings, 2 quizzes
Video9 videos
4.7 CHAMELEON: Graph Partitioning on the KNN Graph of the Data8m
4.8 Probabilistic Hierarchical Clustering7m
5.1 Density-Based and Grid-Based Clustering Methods1m
5.2 DBSCAN: A Density-Based Clustering Algorithm8m
5.3 OPTICS: Ordering Points To Identify Clustering Structure9m
5.4 Grid-Based Clustering Methods3m
5.5 STING: A Statistical Information Grid Approach3m
5.6 CLIQUE: Grid-Based Subspace Clustering7m
Reading2 readings
Lesson 4 Part 2 Overview10m
Lesson 5 Overview10m
Quiz2 practice exercises
Lesson 4 Quiz8m
Lesson 5 Quiz8m
Week
4
Hours to complete
4 hours to complete

Week 4

...
Reading
10 videos (Total 57 min), 1 reading, 2 quizzes
Video10 videos
6.2 Clustering Evaluation Measuring Clustering Quality2m
6.3 Constraint-Based Clustering4m
6.4 External Measures 1: Matching-Based Measures10m
6.5 External Measure 2: Entropy-Based Measures7m
6.6 External Measure 3: Pairwise Measures6m
6.7 Internal Measures for Clustering Validation7m
6.8 Relative Measures5m
6.9 Cluster Stability6m
6.10 Clustering Tendency5m
Reading1 reading
Lesson 6 Overview10m
Quiz1 practice exercise
Lesson 6 Quiz8m
Hours to complete
20 minutes to complete

Course Conclusion

In the course conclusion, feel free to share any thoughts you have on this course experience....
Reading
4.3
32 ReviewsChevron Right
Career Benefit

83%

got a tangible career benefit from this course
Career promotion

50%

got a pay increase or promotion

Top Reviews

By DDSep 25th 2017

A very good course, it gives me a general idea of how clustering algorithm work.

By TKOct 10th 2017

Very intense and required complex thinking and programming skill

Instructor

Avatar

Jiawei Han

Abel Bliss Professor
Department of Computer Science
Graduation Cap

Start working towards your Master's degree

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

About 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. ...

About the Data Mining 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....
Data Mining

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • 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. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.