Data Mining Project 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.
This course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more:
MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder
MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder
Course logo image courtesy of Mariana Proença, available here on Unsplash: https://unsplash.com/photos/_WgnXndHmQ4
Overview
Syllabus
- Data Mining Project
- This week provides you with a general introduction of the Data Mining Project course from the architect's perspective, focusing on the the initial brainstorming of project ideas which will prepare you for the rest of the course.
- Project Proposal
- This week discusses in detail what should be included in your project proposal and ends with an opportunity to craft your own.
- Project Checkpoint
- This week focuses in on checking the status of your project. After reviewing your project, you will take some time to incorporate the progress you've made with updates to your initial proposal.
- Final Project Report
- This week discusses in detail the final project report, highlighting the importance of summarizing the key findings and analyzing the overall project process.
Taught by
Qin (Christine) Lv
