Modern databases can contain massive volumes of data. Within this data lies important information that can only be effectively analyzed using data mining. Data mining tools and techniques can be used to predict future trends and behaviors, allowing individuals and organizations to make proactive, knowledge-driven decisions. This expanded Data Mining for Advanced Analytics certificate provides individuals with the skills necessary to design, build, verify, and test predictive data models.
Newly updated with added data sets, a robust practicum course, a survey of popular data mining tools, and additional algorithms, this program equips students with the skills to make data-driven decisions in any industry. Students begin by learning foundational data analysis and machine learning techniques for model and knowledge creation. Then students take a deep-dive into the crucial step of cleaning, filtering, and preparing the data for mining and predictive or descriptive modeling.
Building upon the skills learned in the previous courses, students will then learn advanced models, machine learning algorithms, methods, and applications. In the practicum course, students will use real-life data sets from various industries to complete data mining projects, planning and executing all the steps of data preparation, analysis, learning and modeling, and identifying the predictive/descriptive model that produces the best evaluation scores. Electives allow students to learn further high-demand techniques, tools, and languages.
Key Topics (see individual courses for more information):
STUDENTS FINISHING THE PREVIOUS DATA MINING PROGRAM
Please use these links to register for remaining courses:
Frequently Asked Questions:
|Course Title||Course Number||Units||FA||WI||SP||SU|
|Statistics for Data Analytics||O||O||O||O|
|REQUIRED COURSES (Four courses required. Courses must be taken in the order listed.)|
|Fundamentals of Data Mining||O||O|
|Data Preparation for Analytics||O||O|
|Data Mining: Advanced Concepts and Algorithms||O||O|
|Data Mining Practicum||O||O|
|ELECTIVE COURSES (Choose one)|
|Introduction to R Programming||O||O||O||O|
|Python for Informatics||X||O||X||O|
|L=La Jolla M=Mission Valley O=Online U=University City X=Location TBA|
From the 'Apply Now' button, login to your student account, complete the online application, and pay the application fee if applicable. It is preferable that you create an account before proceeding if you have not already done so.
Candidates are encouraged to apply in the certificate program as early as possible to take advantage of program benefits. See Certificate FAQs for more information.
|Application Fee: $0||Apply Now!|
|Contact: Science & Technology, 858-534-9358|
|Please note: Upon acceptance into the program, there will be a $60 certificate fee.|
Knowledge of statistics and probability theory is required. A foundation in a programming language and advanced mathematics such as linear algebra is recommended.
To enroll in the certificate program, complete the application and, upon acceptance into the program, pay the $60 certificate fee. Although programs are open to all adult learners, UC San Diego Extension programs are designed to best serve college-prepared working professionals. Where program capacity is limited, applicants with this profile will receive preference for admission.
To earn the Data Mining for Advanced Analysis certificate, you must take four required courses and one elective course. All required courses are designed to be taken sequentially and should be taken in the order shown on the course matrix, above.
You must earn a Pass (if enrolled as Pass/No Pass) or a C- (if enrolled as Letter Grade) or better in each course.
You may enroll in the certificate program at any time. However, it is recommended that you enroll as soon as possible. The program curriculum may be updated at any time; if certificate requirements change, you must adhere to the curriculum at the time of your enrollment into the certificate.
You may take any course without registering for the certificate, provided you have fulfilled any and all prerequisites for the course.
Co-Founder and Chief Data Scientist
Huey Antley, Ed.D.
Vice President, Data Science Solutions
KAR Auction Services, Inc.
Steve Anton, Ph.D.
Sr. Data Scientist
Natasha Balac, Ph.D.
Founder, President and CEO
Data Insight Discovery, Inc.
San Diego Regional Data Library
Steve Coggeshall, Ph.D.
Chief Analytics and Science Officer
Partner, Head of Quantitative Insights
CTO/CPO – Cloud and Open Platforms
Julian McAuley, Ph.D.
Assistant Professor of Computer Science
UC San Diego
Joe Murray, Ph.D.
Jian Pei, Ph.D.
Executive Committee Member
Tamara Sipes, Ph.D.
Principal Data Scientist
Abe Weston, M.S.