Learn how to take data (consumers, genes, stores, …) and organise them into homogeneous groups for use in many applications, such as market analysis and biomedical data analysis, or as a pre-processing step for many data mining tasks. Learn about this very active field of research in statistics and data mining, and discover new techniques.
Cluster analysis is covered with the help of real case studies.
Course Outline
The most popular version of this course comprises 3 sessions described as follows:
Session 1: Principles & Classic Methods
- Introduction to Cluster Analysis
- Context of Use, Objective, Terminology
- Principle of Hierarchical Methods: Determining the Distance Between Objects, Linking Clusters (Agglomerative Methods)
- Modeling Techniques
Session 2: Modern Methods & Applications
- Optimization Methods
- Other Methods: Fuzzy Clustering
- Dealing with Continuous & Categorical Classification Variables
Session 3: What to do with Clusters?
- Use and Interpretation of Clusters
- Unsupervised Learning
- Software Packages for Cluster Analysis
- Summary
Course Duration
The recommendation course duration is 3 online sessions.
Target Audience
This course is aimed at engineers, researchers, biologists and depending on the target audience, the course is adapted. On the one hand by using examples specific to the field of application and on the other hand by presenting specific tools or applications, if applicable.
This module introduces advanced concepts in multivariate data analysis methods.
This course was excellent value for the money. Well-structured and with plenty of hands-on opportunities, it is suited to both beginners and to those with some experience in the technique. The instructors were familiar with all the software packages used by the students and were able to offer practical advice on getting the desired output. A very practical course; loaded with information I could put to use right away. Highly recommended.
This course is very well structured and instructed. I attended both the PCA and cluster analysis session followed by workshop. The instructor (Natalie) is very knowledgeable and very good at explaining difficult statistical problem in a simple way. This course is especially suitable for non-statistician who needs to perform hands on data analysis. This course also exposed students to many different popular statistics packages so you can get a flavor of each of them which helps me a lot in choosing tools in my future research.