Data Mining Project

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Free Online Course: Data Mining Project provided by Coursera is a comprehensive online course, which lasts for 4 weeks long, 38 hours worth of material. The course is taught in English and is free of charge. Upon completion of the course, you can receive an e-certificate from Coursera. Data Mining Project is taught by Qin (Christine) Lv.

Overview
  • This course offers step-by-step guidance and hands-on experience of designing and implementing a real-world data mining project, including problem formulation, literature survey, proposed work, evaluation, discussion and future work.

    Data Mining Project can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

    Course logo image courtesy of Mariana Proença, available here on Unsplash: https://unsplash.com/photos/_WgnXndHmQ4

Syllabus
    • Introduction to Data Mining Project
      • This module provides a general introduction of data mining project from the architect's perspective, focusing on the the initial brainstorming of project ideas.
    • Project Proposal
      • This module discusses in detail what should be included in the project proposal.
    • Project Checkpoint
      • This module focuses on checking the status of the project, identifying the progress so far and any changes to the initial proposal.
    • Project Final Report
      • This module discusses in detail the final project report, highlighting the importance of summarizing the key findings and analyzing the overall project process.