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Sama AL-Rawdhan
02-03-2024
Video of Lecture 1: Introduction to Data Mining in Data Mining course by eLearning Centre - IUG - Video Lectures channel, video No. 1 free certified online
مساق: تنقيب البيانات Data Mining
كلية تكنولوجيا المعلومات
تقديم د. إياد حسني الشامي
رمز المساق: SDEV 3304
رابط المساق عبر مودل
https://moodle.iugaza.edu.ps/course/view.php?id857
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Course’s Description
This course has been designed to give students an introduction to data mining and hands on experience with all phases of the data mining process using real data and modern tools. It covers many topics such as data formats, and cleaning; make prediction using supervised and unsupervised learning using Python and other tools, and sound evaluation methods; and data/knowledge visualization.
Course’s Objectives
This course is designed to achieve a number of goals for each student such as:
• Providing the fundamental understanding of data mining in order to extract hidden knowledge.
• Exploring the different data mining tasks to extract knowledge:
o Classification,
o Clustering,
o Association Rules extraction, and
o Outlier detection.
• Practicing the data mining project phases
• Presenting the data in the early stage of data mining projects as well as the extracted knowledge.
• Provide the students the latest hot topics in data mining field.
• Strengthen the team work
Course’s Outcome
By the end of this course the students should be able to:
• Identify the meaning of data mining, describe the suitable data for data mining projects, list/identify at least five different data mining tasks and evaluate the extracted knowledge for each task.
• Collect and prepare data set suitably for data mining projects.
• Use machine learning techniques to perform the different data mining tasks.
• Analysis and build data mining projects individually or as a team member/leader as well .
• Adopt the ethics of profession with the sensitive personal data
Text book & References
• Text Book: “Data Mining: Concepts and Techniques”, 4th edition by Jiawei Han and Micheline Kamber, Morgan Kaufmann 2017.
• Additional Books:
• “Data Mining – Practical Machine Learning Tools and Techniques”, 4th edition by Ian H. Witten and Eibe Frank, Elsevier 2016.
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