Certificate in Data Analytics
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.
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.
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.
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
|Tuition||Alumni: $410 per credit
Non-Alumni: $505 per credit
|Technology Fee||$55 per term
$275 maximum per academic year
|Application Fee||$25 online
|Late Registration Fee
for registration submitted after the add/drop deadline
|Late Transaction Fee
for employer reimbursement applications
received after the second week of the semester
|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.