Download Database and Data Analytics

engineering & Technology
yo u r U C i n S i l i c o n Va l l e y
Database and
Data Analytics
UCSC Silicon Valley Extension’s Certificate in Database
and Data Analytics consists of two fields of study:
• The Database focus is designed for enterprise data professionals who are involved in designing, administering and using
shared databases, including building business intelligence.
• The Data Analytics focus offers a comprehensive introduction
to the field, including the algorithms, tools, frameworks and
practices in managing Big Data and performing data mining.
This certificate program offers up-to-date training for data
scientists, analysts, administrators and managers who
want to apply analytics to business decision-making.
ucsc-extension.edu/
engineering
Apache Spark with Scala, Introduction
Database and Data Analytics Certificate
Certificate Requirements
Total: 14 units (minimum)
To obtain the Certificate in Database and Data
Analytics, you must successfully complete a total
of 14 units, including one of the two core courses.
One related outside elective or “Also of Interest”
course may be counted toward the certificate upon
department approval.
GPA: 3.0 with a C or better in all courses.
Prerequisites
Each course has different prerequisites.
Please review the course details on our website to
ensure that you meet the requirements, whether
through education or job experience. Programming
knowledge is helpful.
Recommended Course Sequence
We recommend that students begin with one of the
two core courses (“Relational Database Design and
SQL Programming” or “Data Analysis, Introduction”),
and follow the recommended prerequisite for other
courses. The sequence may vary based on student
background and professional interest.
Note: Some courses may be listed in more than one
program. However, you may only share one course
between two Engineering and Technology certificate
programs when applying for the certificates unless
otherwise noted.
Program Contact
Engineering and Technology Department,
(408) 861-3860 or email
[email protected]
Apache Spark is the latest data processing engine that
supports batch, interactive, iterative and graphing data
Curriculum
processing. Its elegant APIs and fast computing system
makes it attractive for companies to leverage for data
14 unit minimum
processing. This course introduces its architecture, the
execution model. It includes a short introduction to
*Take one of these two core courses
UnitsCourse
the functional programming language Scala. You’ll
learn how to manipulate Apache Spark’s programming
Oracle Database
model Resilient Distributed Dataset (RDD) through
*Relational Database Design
its APIs for data processing and how to build Spark
and SQL Programming............................... 3.0.......30215
applications with Scala. The course covers its stream
Oracle PL/SQL, Introduction....................... 2.0.......21320
processing capability and how to develop streaming
applications with Apache Spark.
Oracle 12c: Enterprise Architecture
and Administration on Linux...................... 3.5.......19069
Oracle 12c: Administration on Linux II....... 4.0.......19070
MySQL Database
MySQL Database for Developers
and Designers............................................ 2.0.......22632
Linux-Based Web Application
Development—Apache, MySQL, PHP........ 3.0.......21958
Data Warehouse and Business Intelligence
Data Modeling, Introduction..................... 3.0.........2957
Business Intelligence Solutions.................. 2.0.......30322
Dashboards and Data Visualization........... 2.0.......30282
Data Science and Data Mining
Course 30388
Big Data: Overview, Tools and Use Cases
This course provides an overview of Big Data concepts,
its technological landscape and deployment patterns.
You will learn data management, including how to
acquire, cleanse and normalize Big Data. The course
discusses practical use cases and explores the key
concepts, schema, data access and methodology of
NoSQL, a database management system designed to
handle Big Data. You will also learn the technology infrastructure, Hadoop and SMAQ (Storage, MapReduce
and Query) stacks in Big Data. The course concludes
with Data Visualization Tools (DVT), analytics tools,
and deployment patterns in various industries.
Course 30122
*Data Analysis, Introduction........................ 3.0.......30211
Machine Learning and Data Mining,
Introduction............................................... 3.0.........2612
Predictive Analytics: Applications of
Machine Learning...................................... 3.0.......30331
Big Data
Big Data:
Overview, Tools and Use Cases.................. 3.0.......30122
Hadoop:
Distributed Processing of Big Data............ 3.0.......30088
Apache Spark with Scala, Introduction...... 3.0.......30388
NoSQL Databases, Introduction................. 3.0.......30213
Enrollment Information
Visit ucsc-extension.edu/engineering for
the most up-to-date information about our
courses and programs, including textbooks,
instructors, schedules and locations.
Enroll online at ucsc-extension.edu.
Business Intelligence Solutions
This course takes a hands-on approach to the fundamentals of business intelligence, using the Microsoft
BI stack as an example. You will learn the features of
Info
Info Session for Information Technology and Database and Data Analytics
Join us to learn about our Information Technology and the Database and Data Analytics certificate programs. The IT certificate includes tracks on
networking fundamentals, data center technologies, system administration, enterprise security and IT automation. The Database and Data Analytics
Session
certificate offers basic database courses, as well as data science, Big Data and business intelligence. In addition to general Q&A, program staff will be
available to answer your questions, help you select courses and plan a course sequence. Register early to reserve your space.
Course 30047
To learn more, visit ucsc-extension.edu/events.
PivotTables, Power Pivot and Power View, including
how to load data from SQL Server and create Power
View dashboards, charts and maps. You will use Visual
Studio to build an Online Analytical Processing (OLAP)
cube and dimensions. You’ll also learn to use SQL
Server Analysis Services (SSAS), Integration Services,
and Reporting Services. The course is intended for
BI developers and analysts.
areas. This course provides in-depth knowledge and
hands-on practice in data modeling and design. After
introducing the concepts and principles of data modeling, the course covers data modeling techniques and
practices in four modeling areas: conceptual, logical,
physical, and dimensional. You will study real-world
examples of data models for transactional systems,
data marts and enterprise data warehouses.
Course 30322
Course 2957
Dashboards and Data Visualization
This course introduces dashboard and data visualization technologies with a hands-on approach. You will
identify and design key performance indicators (KPIs),
learn the principles of data visualization, and design
and implement dashboards and scorecards. Other
topics include identifying and selecting dashboard
software tools, as well as common mistakes, tips,
and best practices relevant to dashboards and data
visualization. You will learn how to choose data
sources, extract required data, perform data analysis
using an example tool, and visually present results
on the dashboard.
Course 30282
Data Analysis, Introduction
*
Hadoop: Distributed Processing of Big
Data
Hadoop is an open-source platform for distributed
processing of large amounts of data across clusters
of servers. This course provides an overview of the
MapReduce framework and Hadoop Distributed File
System (HDFS). You will learn how to write MapReduce
code and optimize data processing applications.
The course also covers Hadoop’s ecosystem, including
the data-flow programming language Pig, the
distributed scalable database HBase, the data
warehouse and query service Hive, and the distributed
processing coordination system Zookeeper. The course
consists of interactive lectures, lab exercises and
programming assignments.
Course 30088
This course examines different approaches to a
data analysis project, with a framework for organizing
an analytical effort. Popular tools for data analysis
(such as R and Python) are introduced to carry
out analysis. The course covers how to obtain and
manipulate the raw data for use. It covers the basic
exploratory analysis and common data analytical
techniques such as regression, simulation, estimation
and forecasting, and it includes several graphing
and visualization tools to understand the data and
to present findings and results.
Course 30211
Data Modeling, Introduction
Data modeling defines and applies structure to the
information systems in an enterprise, allowing data to
flow across the enterprise, departments, or business
Linux Based Web Application
Development: Apache, MySQL, PHP
Linux, Apache, MySQL and PHP, collectively known
as LAMP, comprise the majority of servers, databases
and scripting languages on the Internet today. LAMP
belongs to open-source and is very robust, available
free, easily configured, deployed and maintained. This
course teaches LAMP basics, including installation,
deployment and development of a website. You will
learn the basics of programming MySQL (a popular
Web database) and PHP (Hypertext Preprocessor, a
website scripting language). You will learn to develop
basic to intermediate level 3-tier websites and
applications with a database in the back-end.
Course 21958
Machine Learning and Data Mining,
Introduction
Machine learning automatically recognizes complex
patterns in all types of data. This hands-on course
covers the concepts and principles of a variety of
data mining methods and includes machine learning
examples written in the statistical language R. The
course presents supervised learning concepts, which
require labeled training data and include various
types of linear regression, decision trees, k-nearest
neighbors, Naive Bayes, Support Vector Machines and
ensemble methods. Though you may use any language
for your final project, homework must be written in R.
Course 2612
MySQL Database for Developers and
Designers
MySQL is a reliable database engine commonly
used for storing and serving data as Web content.
This course reviews the basic SQL queries and the
types of storage engines. It introduces the aggregate,
the index merge, data manipulation, and stored
procedures in MySQL. You will learn to write complex
queries and get hands-on experience with advanced
features such as creating sub programs, data security,
triggers, and dynamic SQL. You will also learn
performance tuning strategy, server configuration,
loading techniques and the application architecture
for efficient database design.
Course 22632
NoSQL Databases, Introduction
This course offers a study of the features of NoSQL
databases and why they are good fit for Big Data,
covering the types and categories of popular NoSQL
databases, including overviews and examples. The
instructor will provide a data processing example in
NoSQL databases using Hadoop, Apache Hive and Pig.
The course also covers the API coding and cloudbased NoSQL. You will complete a course project that
involves setting up, populating, and using a NoSQL
of your choice. By the end of the course, you will
understand NoSQL concepts and learn to use
popular NoSQL databases.
Course 30213
Oracle 12c: Enterprise Architecture and
Administration on Linux
In this course, you will learn how to install and
configure an Oracle 12c instance and gain experience
with the tools and interfaces required of a database
administrator. The course emphasizes approaches for
sustaining DB administration, performance, backup
and recovery. It features real-world examples of DBA
situations relating to resource management, job
Courses continue on reverse…
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scheduling, performance tuning and DB infrastructure
reports. You’ll learn how to install, work on, and
administer databases in the cloud. The course utilizes
cloud accounts provided by Amazon Web Services and
is designed to prepare you for the Oracle Certified
Associate exam.
Course 19069
Oracle 12c: Administration on Linux II
This course extends the architectural concepts and
DBA practices beyond the “Oracle Database 12c
Administration” course and covers the advanced
administration of multitenant container database and
pluggable databases. The course focuses on installation, configuration, and Recovery Manager (RMAN),
emphasizing the advanced backup and recovery
options to ensure 24/7 database operations. You will
learn the Oracle flashback technology used in recovery,
as well as advanced resource management and realworld solutions to improve database performance.
The course is designed to prepare you for the Oracle
Certified Professional exam.
practical implementation issues. Important topics will
be demonstrated using real-world applications and
case studies. This course includes hands-on exercises
and a project.
Course 30331
Relational Database Design and SQL
Programming
*
This course covers the concepts and design for
Relational Database Management Systems (RDMS)
and the Structured Query Language (SQL) needed
to define and manipulate data. You will learn how
to create conceptual, logical and physical designs of
relational databases. You will use an Oracle database
to design the entity-relationship diagrams (ERD) and
implement a working database. The course covers
methods for producing readable output, creating
and manipulating tables and creating and managing
constraints using SQL. The concepts and SQL
language learned here apply to all major RDMS.
Course Planning Session
for Engineering and
Technology Students
Join us for a complimentary course
planning session designed for new or
returning Engineering and Technology
students. If you’re interested in enrolling in a certificate program, this is an
excellent opportunity to get your questions answered. In one-on-one sessions,
department staff will validate your
assumptions, address common course
sequence questions, and suggest alternatives. We recommend that you first
attend an Info Session to learn program
basics and develop a draft course plan.
Register early to reserve your slot.
Course 30371
Course 30215
Course 19070
Oracle PL/SQL, Introduction
This course is applicable to Oracle8i, Oracle9i, Oracle
10g, and Oracle 11g users. It introduces students to
PL/SQL and explains the benefits of this powerful
programming language. You’ll learn to create PL/
SQL blocks of application code that can be shared by
multiple forms, reports, and data management applications, as well as anonymous PL/SQL blocks, stored
procedures, functions, packages and database triggers.
You’ll also learn to manage PL/SQL program units,
use dependencies, manipulate large objects, and use
some of the Oracle-supplied packages. The lab uses
I*SQLPLUS to develop these program units.
Course 21320
Predictive Analytics: Applications of
Machine Learning
The course provides a broad introduction to machine
learning methods including regression, classification, clustering and recommender systems, and their
application to practical scenarios. The course reviews
the steps involved in building predictive models,
including data collection, feature selection, algorithms,
and evaluation. You will learn how to fine tune the
performance of these predictive models, and plan for
Not printed or mailed at state expense. 611796-1502-2080 (05/15/15)