Data Mining
Course Learning Outcomes
At the end of the course, students should be able to:
1. Assess the methods of data mining related to real application in data science ( C5 )
2. Manipulate data mining methods based on the given tasks using data mining tools ( P4 )
3. Organise the use of digital skills in model development related to the data mining project ( P5 )
Course Description
The Data Mining course introduces the concepts and methods of data mining and shows its relationship with data science. All the steps involved in knowledge data discovery will be discussed. Topics include Introduction to Data Mining, Data Preparation and Pre-processing, Classification, Model Evaluation & Selection, Clustering, Association Analysis, and ends with Future Trends & Challenges. The algorithm for each modelling process is discussed with supporting examples using real-world datasets. These datasets are used for model building using assessable technology with easy-to-use platforms. The findings will be presented through digital tools. The knowledge and practical skills gained from this course would benefit the students for solving real problems in industry or society-related issues for various SDG-based applications.
Syllabus Content
1. Introduction to Data Mining
Evolution of Data Mining
Data Mining and Data Science Concept
Knowledge Discovery in Databases
Problem and Challenges
2. Data Preparation for Knowledge Discovery
Data Understanding
Basic Statistics
Data Exploration
Data Visualization
3. Data Pre-processing
Data Quality
Cleaning, Integration and Reduction
Transformation
Discretization
4. Classification
Classification Concepts
Classification Tasks
Decision Tree
Book chapter 4
5. Model Evaluation and Selection
Accuracy
Confusion Matrix
Comparison of models
Improving Classifier Accuracy
Book chapter 5
6. Association
Frequent Patterns
Market Basket Analysis
Apriori Algorithm
Association Rules
Frequent Pattern Tree
Book chapter 6
7. Clustering
Cluster Analysis
Similarity and Dissimilarity
Clustering Algorithms
Book chapter 7
8. Current and Future Works
Advanced Data Mining Methods
Future Trends and Applications
Book chapter 8
