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This website is created to share the activities in the Data Mining course in Universiti Putra Malaysia (UPM). In UPM, the Data Mining course is offered at the Faculty of Computer Science and Information Technology, under Department of Computer Science. This course covers concepts and techniques of data mining. It includes data warehouse, data mining primitive, data pre-processing, data mining functions, data mining techniques, and data mining software. The chosen techniques are applied in the data mining application system development.
This website is created to share the activities in the Data Mining course in Universiti Putra Malaysia (UPM). In UPM, the Data Mining course is offered at the Faculty of Computer Science and Information Technology, under Department of Computer Science. This course covers concepts and techniques of data mining. It includes data warehouse, data mining primitive, data pre-processing, data mining functions, data mining techniques, and data mining software. The chosen techniques are applied in the data mining application system development.
The learning outcomes of this course are:
The learning outcomes of this course are:
Students can:
Students can:
1. Generate rules to represent knowledge and make decisions using data mining tools.
1. Generate rules to represent knowledge and make decisions using data mining tools.
2. Show the ability to make decisions using data mining techniques.
2. Show the ability to make decisions using data mining techniques.
3. Analyze problems, propose alternative solutions and make presentations.
3. Analyze problems, propose alternative solutions and make presentations.
4. Ability to collaborate in groups.
4. Ability to collaborate in groups.
The assessments of this course cover: First Test, Assignments, Mini Project and Final.
The assessments of this course cover: First Test, Assignments, Mini Project and Final.
For the assignments and mini project, the students are typically encouraged or assigned real-world problems to be solved and they are expected to develop data analytics and data mining solutions for the predetermined stakeholders. The tested skills cover both the fundamental knowledge and applied knowledge.
For the assignments and mini project, the students are typically encouraged or assigned real-world problems to be solved and they are expected to develop data analytics and data mining solutions for the predetermined stakeholders. The tested skills cover both the fundamental knowledge and applied knowledge.
Students are also evaluated in terms of their ability to design and develop suitable problem solutions using their chosen data mining tools. The students are also asked to demonstrate their knowledge through development of multimedia presentation such as below:
Students are also evaluated in terms of their ability to design and develop suitable problem solutions using their chosen data mining tools. The students are also asked to demonstrate their knowledge through development of multimedia presentation such as below:
The complete materials for the delivery, activity and assessment in this course are provided in PutraBlast, the formal learning hub for UPM students. Some materials of the course is also available in https://padlet.com/nurfadhlina/SSK4604.
The complete materials for the delivery, activity and assessment in this course are provided in PutraBlast, the formal learning hub for UPM students. Some materials of the course is also available in https://padlet.com/nurfadhlina/SSK4604.
Project
Project
The project is conducted as part of the continuous assessment in the Data Mining (SSK4604) course at the Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Malaysia.
The project is conducted as part of the continuous assessment in the Data Mining (SSK4604) course at the Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Malaysia.
The expected outcome of the project is to prepare students for:
The expected outcome of the project is to prepare students for:
- data mining task understanding using a selected industry scenario
- data mining task understanding using a selected industry scenario
- data exploration, data analysis and data visualization skills which are to be demonstrated by applying suitable tools
- data exploration, data analysis and data visualization skills which are to be demonstrated by applying suitable tools
- data mining project planning and management by utilizing elevator pitch technique, and project reporting through online blog
- data mining project planning and management by utilizing elevator pitch technique, and project reporting through online blog
- teamwork skills through management, development, implementation and reporting of the project
- teamwork skills through management, development, implementation and reporting of the project
Various approaches have been taken to ensure that the content of the course is up-to-date and sync with the industry needs. This includes the exposure on the tools for data mining, PowerBI, Tableau, Weka, Python and R. Datasets from competitions, research and supplied by the industry is also used.
Various approaches have been taken to ensure that the content of the course is up-to-date and sync with the industry needs. This includes the exposure on the tools for data mining, PowerBI, Tableau, Weka, Python and R. Datasets from competitions, research and supplied by the industry is also used.
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