The Certificate in Data Analytics is a 4-course, affordable option for professionals
who need to upgrade their IT skills to meet current market demands.
More and more organizations are collecting large amounts of data, both structured
and unstructured. There is a real need for professionals who can analyze and interpret
such data, detect patterns, identify new decision alternatives and make predictions.
Data analytics is the systematic analysis and interpretation of data using various
computational and statistical tools in order to support decision-making based on the
scientific method.
This program will prepare you to create, develop and implement data models as well
as work with big data sets using a real-world data cluster managed in-house to derive
insights and make recommendations.
An applied curriculum based on machine learning and statistical techniques, visualization
tools and R language provides students the necessary skills to launch their careers
into data analytics domain in any industry.
A completed admissionApplicationand non-refundable application fee
Graduate Program Advisement with an admission counselor
Official Transcript(s) from a regionally accredited college or university verifying
the applicant’s bachelor’s degree. Normally, a grade point average of approximately 3.0 or higher in upper division
undergraduate work is expected
Benefits
Specifically, by completing the certificate program in Data Analytics, students will
be able to:
Understand the general framework surrounding data management, analytics and big data
Assess organizational data and information requirements and construct data models
Develop an ability to effectively clean, manipulate and visualize large volumes of
data
Apply machine learning and statistical tools to big data sets
Make data-driven decisions based on analytics techniques
Write professional reports and present findings to target audiences
Program Completion Time
The certificate can be completed in as little as six months, and is based on a sequence
of four 3-unit graduate courses for a total of twelve credits. This requires enrollment
for at least two terms, based on 11-week term schedules. The completion time does
not account for any pre-requisite courses a student may need.
Admission Requirements
The program requires a solid quantitative background rooted in probability and statistics
as well as programming.
At a minimum, all students entering the program need to have completed the following
courses which are pre-requisites into the program:
Probability & Statistics
Java/Object Oriented Programming
These courses are also offered at Cal Lutheran (and are not part of the certificate
program). Relevant work experience in the IT field will also be considered.
An undergraduate degree in computer science, engineering, math, physics and other
natural sciences, statistics, information systems, or a related field is required
for admission to the program. Students with other backgrounds will be considered based
on their work experience and/or completion of pre-requisite courses as noted above.
International students (who have completed a degree outside of the US) need to submit
English proficiency requirements such as Toefl of minimum 88 or IELTS or minimum 6.5.
Courses
This is a required course that must be taken first in the certificate program. The
course provides students with an introduction to the fundamental concepts, techniques
and tools used in design, development and application of relational database technology
in organizations. Topics include data modelling based on organizational requirements
and data manipulation via structured query language tools.
Students will also choose any three of the electives below:
This course is an introduction to business analytics, defined as the extensive use
of data, statistical and quantitative analysis, exploratory and predictive models,
and fact-based management to drive decisions and actions. Topics include implementation
of successful analytics platforms, big and little data, predictive analytics, social
media analytics, mobile analytics and data visualization.
This course is an overview of leading data mining methods and their applications to
real-world problems. It is designed to provide students with the skills to conduct
data mining and statistical analysis for dealing with analytical tasks such as prediction,
classification, decision trees and clustering.
This course introduces the principles and procedures related to the design and management
of data warehouse (DW) and business intelligence (BI) systems. The course focuses
on the data warehousing process including requirement collection, data warehouse architectures,
dimensional modeling, extracting, transforming, and loading strategies, and creation
of data marts. The course also uses data warehousing as a platform for BI applications,
such as reporting, dashboards and online analytical processing (OLAP).
This course introduces students to the world of big data and associated technologies.
The focus of the course is Apache Hadoop, which is an open source software project
that enables, distributed processing of large data sets across clusters of commodity
servers. Topics include Hadoop system architecture, Hadoop Distributed File System
(HDFS), MapReduce programming model and design patterns and technologies surrounding
Hadoop ecosystem such as Pig, Hive and Oozie. The course will also introduce big data
science concepts and NoSQL database technologies.
Special topics courses vary and are used to introduce students to new topics in the
Information Technology field.
Tuition & Fees
Fall 2023 - Summer 2024
Tuition
Alumni: $480 per credit Non-Alumni: $595 per credit
Technology Fee
$60 per term
Application Fee
$25 online $50 paper
Late Registration Fee for registration submitted after the add/drop deadline
$50
Late Transaction Fee for employer reimbursement applications received after the second week of the semester
$50
Transcript Fee
$5.00 minimum Additional fees may apply, refer to the Registrar's site
All fees are subject to change without notice. The University reserves the right to
change, delete or add to this pricing schedule as deemed appropriate. Transcripts
and diploma will not be released for any student who has an outstanding balance owed
to Cal Lutheran.