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
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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.
Course 3 of 3 in the Data Mining Foundations and Practice Specialization.
What You Will Learn
- Identify the key components of and propose a real-world data mining project.
- Design and develop real-world solutions across the full data mining pipeline.
- Summarize and present the key findings of the data mining project.
- Analyze the overall project process and identify possible improvements.
Syllabus
WEEK 1
Introduction to Data Mining Project
This module provides a general introduction of data mining project from the architect's perspective, focusing on the initial brainstorming of project ideas.
WEEK 2
Project Proposal
This module discusses in detail what should be included in the project proposal.
WEEK 3
Project Checkpoint
This module focuses on checking the status of the project, identifying the progress so far and any changes to the initial proposal.
WEEK 4
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.
