Working on a project you propose is an excellent opportunity to explore and learn.

Some points to note are:

* It is usually not a good idea to conduct a survey of a field if you are a novice.

* Identifying a novel and challenging problem can be a project. However, it requires substantial work to show that it is novel, interesting, and challenging.

* Sometimes it is inevitable for a project to be unsuccessful due to the nature of research. Don’t worry. If you can objectively report the failures and explain carefully what the likely courses are, it is still possible to get a very good score.

Some topics of the course projects can be as follows (listed as examples and subject to revision):

1. Your idea – this needs to be approved by the instructor

2. Streaming Data Extraction

3. Selection Bias in Learning or Web Search

4. Bioinformatics: Microarray Data Preprocessing and Mining, Trends in Cyberinfrastructure for Bioinformatics and Computational Biology

5. Privacy Preserving Data Mining

6. Intrusion Detection, Anomaly Detection

7. Subspace Clustering

8. Data Privacy and Security

9. Web Mining

10. Learning with both Labeled and Unlabeled Data

11. Text Mining

12. Visual Data Analysis, Image Mining