| Title | Winter | Spring | Summer | Fall |
| Data Management |
Designing Relational Databases (3.00 Units)
I&C SCI X426.81
If you need to learn more about the design of relational database systems, this course is for you. You'll explore how the relational database approach is used in both open and closed systems and on both mainframe and client/server platforms, and learn about the design of systems of all sizes including standalone, workgroup, departmental, and enterprise-wide applications. You'll also learn how to incorporate data from legacy systems as well as how to develop entirely new systems. You'll have the opportunity to design a rational database model in class and refine it for a real-world system or case study. Topics include an overview of database systems, defining business entities, entity relationship modeling (ERM) for top-down analysis, defining relational database tables and attributes, conversion of logical design to physical design, normalization of tables, and using structured query language (SQL) to process data and generate reports. Prerequisites: Coursework or experience in programming using a high-level programming language.
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Data Integration, Modeling, and ETL (2.50 Units)
I&C SCI X425.32
This course provides both introductory and advanced concepts and techniques for developing effective dimensional models, data integration, and the ETL process. Learn how to build a high performance dimensional data model. A good dimensional model and its physical database form the hub of a business intelligence data warehouse, serving as the target of the data integration and as the source of business intelligence data. Learn how to design dimensional models for extensibility, employ a proven dimensional design process, apply the process to several representative situations, and understand a variety of advanced dimensional modeling techniques. The Extract, Transform, and Load (ETL) process is typically the most time-consuming, misunderstood, and underestimated task in building a data warehouse and other data integration applications. The ETL process addresses and resolves the challenges of extracting data from disparate operational source systems, storing it in the data staging area, profiling data for errors, cleaning and transforming the data, and mass loading it into the target enterprise data warehouse, data marts, or operational systems. Prerequisite: Experience using a relational database (as a minimum, Microsoft Access or similar product) is highly desirable.
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to be scheduled
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Online
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Data Management (2.50 Units)
I&C SCI X425.35
Data may be an organization's most underrated asset. Organizations often invest a very small percentage of their budget on maintaining the health of their data, which may over time lead to decreasing competitiveness, loss of market share, and even violations of regulatory requirements. This course presents data management from an organizational perspective with the goal of using data management methodologies as a foundation for enterprise data architecture. The course concentrates on data definition and specification, data quality, data organization, data integration, and data equilibrium.
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| Data Analysis |
Introduction to Big Data (2.00 Units)
I&C SCI X425.80
Web 2.0 has changed the way we conduct business. It affects consumer interactions, information sharing, success measurement in terms of business revenue and customer wallet share, and brand management. Most importantly, it has created a revenue channel like none other. Personalization of products and services by enterprises have increased data volumes and the velocity of data production while creating a variety of data formats. We are now well and truly in the world of Big Data. The key value of this data is the vast amount of intelligence that can be found when data is modeled with geographic and demographic information. This introductory course will help students navigate through the complex layers of Big Data and Data Warehousing while providing information on how to effectively think about using these technologies and architectures to design the next-generation data warehouse. Concepts covered include an introduction to Big Data, discussion of Big Data Processing Architectures, explanation of the integration of Big Data and Data Warehouses, and fundamentals of Big Data Analytics. Examples will be used to step students through an implementation of a Big Data solution.
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to be scheduled
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R Programming (2.00 Units)
I&C SCI X425.20
R is a scripting language for statistical data manipulation and analysis. R is an open source package available under GNU license at no cost. R competes with SPSS, another very well-known statistical package used heavily in many industries. Statistics is used in every part of business data processing and prediction. Data captured by web analytics services need statistics. Statistics is also the foundation of predictive analytics. R business applications include correlation, regression, hypothesis testing, and all inference testing. This course will focus on R programming which is used for solving business problems related to basic math and statistics. First, all relevant math concepts will be reviewed. This will include functions, regression, descriptive and inferential statistics, and matrix operations. All these basic math problems will be solved using R. The programmatic interface and graphic capabilities of R will also be explored. In the end, several real-world business problems will be solved using R. Prerequisites: I&C SCI X414.13 Math Review for Data Science and Analytics or basic math, statistics, functions matrix and basic programming.
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to be scheduled
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Online
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Hadoop: In Theory and Practice (3.00 Units)
I&C SCI X425.18
Today, organizations in every industry are being showered with imposing quantities of new information. Along with traditional sources, many more data channels and categories now exist. Collectively, these vastly larger information volumes and new assets are known as Big Data. Enterprises are using technologies such as MapReduce and Hadoop to extract value from Big Data. This course provides an in-depth overview of Hadoop and MapReduce, the cornerstones of big data processing. To crystalize the concepts behind Hadoop and MapReduce, you will work through a series of short/ focused exercises; you will configure and install a Hadoop cluster, write basic MapReduce programs, gain familiarity with advanced MapReduce programming practices, and utilize interfaces such as Pig and Hive to interact with Hadoop. You will also learn about real-world situations were MapReduce techniques can be used.
Pre-requisite: "This course is appropriate for developers who want to get acquainted with Hadoop concepts and who will be writing, maintaining and/or optimizing Hadoop jobs. Data Architects and IT Managers/Directors who want an in-depth look into Big Data technologies such as Hadoop and MapReduce also stand to benefit from this course.
Participants should have some programming experience; a background in Java is preferred, but experience with other programming languages such as PHP, Python, or C# is sufficient. Understanding of common computer science concepts is a plus. Prior knowledge of Hadoop is not required.
Access to a Windows PC. For example: WIndows XP, Windows 7, Windows 10 PC
Hadoop is written in Java, so you will need to have Java installed on your machine, version 6 or later. Sun’s JDK is the most widely used with Hadoop. In case you do not have Java installed, step-by-step instructions will be provided to install Java."
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to be scheduled
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Business Intelligence & The Data warehouse Development Process (2.50 Units)
I&C SCI X427.01
Learn how to make better business decisions, use fewer resources, and improve your company's bottom line by developing and using a data warehouse. This course provides an overview of business intelligence and data warehousing and gives you a look at all the major facets of developing and using a data warehouse to make effective business decisions. Students will work on a single project to develop a comprehensive project plan and business case for a data warehouse including how to develop a dimensional model, a data staging process, and a data access process. Additional topics will include information on careers working with business intelligence and data warehousing as well as the educational requirements for this field.
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to be scheduled
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Big Data Analysis (2.50 Units)
I&C SCI X427.07
Big data is one of the most important technology trends to fundamentally impact the way organizations operate and compete. As more and more companies collect large amounts of data through their daily operations, the ability to analyze and glean knowledge from big data has become an integral part of a successful business. This course will help students navigate through the complex layers of Big Data while providing insight on ways to effectively use technologies and architectures to create and manage big data workflows. Concepts covered include an introduction to Big Data and related technologies, discussion of Big Data Processing Architectures, explanation of major concepts behind Big Data Management, and how all of those topics are applied in Big Data Analysis. Students will gain an understanding of the characteristics of big data and techniques for working on big data platforms through hands-on exercises in the tools and systems used by data scientists and data engineers including Hadoop (HiveQL & PIG), Apache Spark, and SparkSQL.
Prerequisite: I&C SCI X427.05 Fundamentals of Data Science
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to be scheduled
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to be scheduled
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Online
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Online
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| Microsoft SQL Server Database |
Introduction to SQL Programming (2.50 Units)
I&C SCI X450.72
Install SQL Server to your desktop and run complex queries using the Structured Query Language (SQL). This course will cover database table structures, column data types, and the T-SQL language components that go into querying against a database. Reading data from a table, row filtering, and column based functions will be discussed. We will also write queries that combine data from multiple tables, use conditional logic, and create aggregated result sets (sum, average, min, max). Database administration features of SQL will also be discussed. Prerequisites: Familiarity with data processing concepts and techniques.
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to be scheduled
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Online
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Online
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Intermediate SQL Programming (2.50 Units)
I&C SCI X450.79
Expand your SQL toolkit in this Intermediate SQL course. SQL is a language used in programming and designed for managing data held in a relational database management system (RDBMS). This intermediate course will focus on using MS SQL Server and T-SQL. Topics covered in this course include: Data aggregation using aggregate functions, writing sub-queries, recursive queries, and common table expressions. Students will also gain experience creating views, stored procedures, functions, and triggers using different looping and database locking mechanisms. Specific areas in the SQL Server database using data file structures, database schemas, setting properties, snapshots, data space and type usage and identity columns will be covered. SQL tuning and use of execution plans will also be addressed. Prerequisites: I&C SCI X450.72 Introduction to SQL Programming.
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Online
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Implementing and Maintaining SQL Server Reporting Services (2.50 Units)
I&C SCI X450.77
In this course students learn how to implement a Reporting Services solution in an organization. The course discusses how to use the Reporting Services development tools to create simple reports to very complex reports, and how to use the Report Services management and administrative tools to manage a reporting Services solution. This course covers Reporting Services architecture, reporting authoring tools to dynamically modify the data set underlying a data region by allowing parameters to be sent to the underlying query, as well as will learn to use best practices to implement static and dynamic parameter lists when interacting with queries and stored procedures. Prerequisites: I&C SCI X450.72 Writing Queries Using SQL Server course or familiarity with data processing concepts and techniques.
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Implementing and Maintaining SQL Server Integration Services (2.50 Units)
I&C SCI X450.78
"In this course students learn how to implement an Integration Services solution in an organization.
The course discusses how to develop, deploy, and manage Integration Services packages.
This course covers the role that Integration Services plays in extracting, transforming, and loading data.The students will also be introduced to the tools that are used to build and manage Integration Services solutions." Prerequisites: Completed Writing Queries Using SQL Server course (Intro to SQL programming) or familiarity with data processing concepts and techniques.
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| Cloud DB Courses |
Docker Fundamentals with AWS (2.00 Units)
I&C SCI X425.42
Learn the basics of Docker and how to run Docker with AWS for more efficient containerization. Docker is an open-source platform for developers and system admins to develop, ship, and run applications. It enables application developers, network and system administrators, and others to access and deploy the latest updated images into their respective environments. It helps reduce dependencies and friction between moving parts of a deployable application. This course will cover the information needed to get started with Docker and how the Docker environment can be utilized for scalable application testing and deployment.
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AWS Cloud Foundations (2.50 Units)
I&C SCI X460.70
Understanding AWS services, pricing, and management leads to better delivery of cloud-based solutions. This course provides a detailed overview of cloud concepts, core services, security, architecture, pricing, and support available on Amazon Web Services (AWS). Explore applications of AWS through practical examples, demonstrations, and lab exercises. After completing this course, students have the fundamental skills to get started on AWS. This course also helps students prepare for the AWS Certified Cloud Practitioner exam.
Prerequisites: General IT technical knowledge including fundamentals of networking is highly recommended.
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AWS Cloud Architecting - Part1 (2.50 Units)
I&C SCI X460.73
This is course one of a two-part series in Cloud Architecting with AWS. Beginning with the fundamentals of building IT infrastructure on AWS, the course is designed to teach solutions architects how to optimize their use of the AWS Cloud by understanding AWS services and how they fit into cloud-based solutions. Although architectural solutions can differ depending on the industry, type of application, and size of the business, this course emphasizes best practices for the AWS Cloud Environment that can apply to all of them. It also recommends various design patterns to help think through the process of architecting optimal IT solutions on AWS. Throughout the course, students will explore case studies that showcase best practices for successfully designing infrastructures and the strategies and services that can be implemented. Finally, this course provides opportunities for students to build a variety of infrastructures through a guided, hands-on approach. Prerequisite: I&C SCI X460.70 AWS Cloud Foundations
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