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Community Research and Program Evaluation Certificate

Data Mining for Advanced Analytics Certificate

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.

Benefits:

  • Essential knowledge and skills in data extraction and collection, data preparation, and identifying effective methods across datasets
  • Hands-on comprehensive training designed to immerse students in the skills needed to successfully begin or advance their career
  • Industry-neutral curriculum allows students to apply knowledge to their field of interest

Key Topics (see individual courses for more information):

  • Model training, testing, and evaluation
  • Decision tables and trees
  • Classification rules
  • Association rules
  • Bayesian learning
  • Numeric prediction
  • Clustering
  • Ensemble learning
  • Artificial neural networks
  • Hidden Markov models
  • Support vector machines

STUDENTS FINISHING THE PREVIOUS DATA MINING PROGRAM
Please use these links to register for remaining courses:

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Certificate Course Matrix
Course Title Course Number Units FA WI SP SU
PREREQUISITE (Recommended)
Statistics for Data Analytics
CSE-41264
3
O O O O
REQUIRED COURSES (Four courses required. Courses must be taken in the order listed.)
Fundamentals of Data Mining
CSE-41258
3
O   O  
Data Preparation for Analytics
CSE-41261
2
  O   O
Data Mining: Advanced Concepts and Algorithms
CSE-41262
3
O   O  
Data Mining Practicum
CSE-41263
3
  O   O
ELECTIVE COURSES (Choose one)
Introduction to R Programming
CSE-41097
3
O O O O
Python for Informatics
CSE-41225
3
X O X O
Text Mining
CSE-41151
2
O O O O
L=La Jolla M=Mission Valley O=Online U=University City X=Location TBA
Certificate Programs

To Apply for the Certificate Program

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
Email: unex-techdata@ucsd.edu
Please note: Upon acceptance into the program, there will be a $60 certificate fee.

Conditions for Admission

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.

Certificate Guidelines

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.

Please Note

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.

Advisors

Dean Abbott
Co-Founder and Chief Data Scientist
SmarterHQ

Huey Antley, Ed.D.
Vice President, Data Science Solutions
KAR Auction Services, Inc.

Steve Anton, Ph.D.
Sr. Data Scientist
ID Analytics

Natasha Balac, Ph.D.
Founder, President and CEO
Data Insight Discovery, Inc.

Eric Busboom
Director
San Diego Regional Data Library

Steve Coggeshall, Ph.D.
Chief Analytics and Science Officer
ID Analytics

Angel Evans
Partner, Head of Quantitative Insights
ModOp

Stefanos Makris
CTO/CPO – Cloud and Open Platforms
Teradata

Julian McAuley, Ph.D.
Assistant Professor of Computer Science
UC San Diego

Joe Murray, Ph.D.
Principal Scientist
FICO

Jian Pei, Ph.D.
Executive Committee Member
ACM SIGKDD

Tamara Sipes, Ph.D.
Principal Data Scientist
Optum/UnitedHealth Group

Abe Weston, M.S.
Associate Principal
Google