Presentation draft	Create a list of slides with content for a presentation. If you have enough data, for each slide create a list of key information points (or simply provide text information for each slide). The titles of all slides must be formatted as headings (do not numerate slides)
Which subject	Computer science
What age group	Adult courses
What topic	Data mining
Number of slides	7
Include images descriptions
Text to use as a source
Any other preferences

• Definition of data mining
• Importance of data mining in computer science
• Brief history of data mining

Types of Data Mining

• Descriptive vs. predictive data mining
• Supervised vs. unsupervised data mining
• Clustering vs. classification data mining

Data Mining Techniques

• Association rule learning
• Decision tree induction
• Neural networks
• Linear and logistic regression
• Time series analysis

Data Mining Applications

• Customer relationship management
• Fraud detection and prevention
• Market basket analysis
• Healthcare and medicine
• Social media analysis

Data Mining Tools

• SPSS
• R programming language
• SAS
• RapidMiner
• KNIME

Challenges in Data Mining

• Data quality and preprocessing
• Overfitting and underfitting
• Privacy and security concerns
• Interpreting and presenting results

Conclusion

• Recap of key points
• Future of data mining in computer science
• Opportunities for further study and research