Online Graduate Certificate in Data Mining
Program Description
The Department of Computer Engineering and Computer Science (CECS) and the Department of Mathematics have developed this joint certificate in data mining to address the need for trained professionals in the interdisciplinary field of data mining. Learn from award-winning faculty who are leaders in data mining, warehousing, and analysis. Their expertise spans the use of text, web, numerical and image databases, and they have applied this to the fields of medicine, e-commerce, security, military, education and more.
The program can be completed entirely online or in combination with on-campus sections in as little as 12 months.
Career Opportunities
Data miners are specialists in finding valuable hidden data in large masses of stored data, and are critical to industries including insurance, healthcare, retail, education, banking, manufacturing, pharmaceuticals, biotechnology, travel, government, and intelligence.
IT professionals; Marketing, Sales and Customer Relations Managers; Database and Direct Marketers; Data Analysts; Statisticians; Financial Managers; Business and Data Analysts; and Project Managers are all professions that can utilize Data Mining expertise.
Virtually any organization, regardless of industry, can reap the enormous payoffs of data mining.
Admission Requirements
For non-degree seeking students (certificate only):
- Bachelors degree - in a technically related field or have technical experience.
- Knowledge of calculus.
- Completion of Application for Admission and payment of non-refundable $50 application fee.
For degree status - those who want to continue beyond the 18-hour certificate program for a Masters or PhD degree - applicants must also submit:
- Graduate Record Examanation (GRE) score
- Two letters of Recommendation
The Test of English as a Foreign Language ( TOEFL ) is required of all foreign students from countries in which English is not the native language. Applicants holding a baccalaureate or advanced degree from an accredited college or university in the United States are exempt from the TOEFL requirement.
Program / Course Requirements
The certificate program consists of 18 credit hours, with two required computer science courses, two required mathematical statistics courses (offered as CECS 694 Special Topics classes), and two elective courses from a list of relevant elective courses in computer science and/or mathematics.
| Areas | Courses | Requirements | Credit Hours |
|---|---|---|---|
| Required Courses |
CECS 535
- Database Design
|
complete all 4 courses | 12 |
| Electives |
CECS 522
- Evaluation of Computer Systems
|
complete 2 courses | 6 |
| Total Hours (for Certificate): | (18) | ||
Refer to the Schedule of Online Classes for a list of current, upcoming and past courses offered at a distance at U of L.– NOTE: All distance courses listed in the schedule of classes will have a section number in the 50’s and a note with the course title that indicates it is offered either online or televised.
To search for both on-line and on-campus classes, go to the Schedule of Classes. Distance classes will have a section number in the 50s and will have a note indicating they are online or televised.
Information / Assistance:
Toll Free: 1-800-334-8635 extention 852-6456
Telephone : (502) 852-6456
Email : Service Account Online Students
U of L Course Descriptions
Disclaimer:
The course descriptions provided herein are for the guidance of students. The University, however, reserves the right to change course descriptions without prior notice. The provisions of this listing do not constitute an express or implied contract between the University and any member of the student body, faculty or general public.
CECS 522 - Evaluation of Computer Systems
A study of approaches to the evaluation of computer systems. Measurement techniques and evaluation techniques are treated in detail with attention to existing commercial hardware and software monitors and simulators. Prerequisite: IE 360 (Probability & Statistics for Engineers), and CECS 420 (Design of Operating Systems).
CECS 535 - Database Design
This course covers the basic issues in the field: database design, SQL, query processing and optimization, transactions. The emphasis will be placed on Engineering design and implementation of relational systems. A written project is required. Prerequisites: CECS 335 (Design of File Structures).
CECS 619 - Computer Algorithms
The engineering design of efficient computer algorithms. A study of the inter-relationships between algorithmic statements, data structures, and the resulting computational complexity of the algorithm. An engineering analysis of the effect of the computer implementation of the algorithmic statement on the computational complexity. Categorization of algorithms into complexity classes. Prerequisite: CECS 335 (Design of File Structures), and CECS 410 (Discrete Structures).
CECS 632 - Data Mining
Data mining concepts, methodologies, and techniques, including statistical and fuzzy inference, cluster analysis, artificial neural networks, and genetic algorithms, rule association and decision trees, N-dimensional visualization, Web and text mining, and advanced topics. Prerequisites: IE 360 (Probability & Statistics for Engineers), CECS 535 (Introduction to Databases).
CECS 660 - Intro to Bioinformatics
Covers the current state of the art programs designed for sequence alignment, database searching, RNA structure prediction, microarray, sequence analysis, gene prediction, repeat detection, and protein folding prediction. A detailed analysis of the algorithms behind each of these will be explored. The algorithmic techniques discussed will include dynamic programming, hidden Markov models, finite state automata, grammars, Karlin-Altschul statistics and Bayesian statistics. Prerequisites: CECS 302 (Information Structures) or CECS 503 (Survey of Computer Engineering and Computer Science.)
CECS 694 - Special Topic: Linear Statistical Models
CECS 694 - Special Topic: Methods of Classification
CECS 694 - Special Topic: Data Mining with Time Series
CECS 694 - Special Topic: Intro to Data Analysis
CECS 694 - Special Topic: Web Mining
CECS 696 - CECS Project
Independent design or experimental project in Computer Engineering and Computer Science. Written and verbal reports required. Reports must include literature, speech, experimental methodology, design details, implementation details, test results, conclusions, and references. Verbal reports will be presented at a specified date each semester. Prerequisites: Graduate Standing in CECS.