IT - Data (156)
IT - Data (156)
156-101. .Net Database Programming. (3 Credits)
Learn basic C# methodologies, including classes, objects, types and the difference between value and reference. Apply object-oriented methodologies and utilize constructors, inheritance and class hierarchies. Also become familiar with Object Relational Models (ORMs) and database manipulation.
Prerequisites: (152-112 with a minimum grade of C or 152-134 with a minimum grade of C or 152-107 with a minimum grade of C or 152-138 with a minimum grade of C) and (156-109 (may be taken concurrently) with a minimum grade of C or 152-115 with a minimum grade of C)
156-102. Advanced SQL. (3 Credits)
Learn various advanced SQL topics for SQL Server, including temporary tables, triggers, advanced stored procedures and user-defined functions. Develop skills in optimization, indexing and other performance-tuning tools and techniques. Explore advanced database design, implement windowing functions, perform data integration using triggers and merge statements, and create and parse JSON and XML.
Prerequisites: 156-109 with a minimum grade of C or 152-115 with a minimum grade of C
156-103. Database Administration. (3 Credits)
Learn to install, configure and secure Microsoft SQL Server. Discuss recurring maintenance needs and perform common maintenance tasks. Plan server configurations for various database environments and implement high availability/disaster recovery configurations. Explore methods for monitoring server performance and identify and resolve common security and performance issues.
Prerequisites: 150-190 with a minimum grade of C
156-104. Data Analysis and Reporting. (3 Credits)
Learn to create and manage reports in a variety of reporting tools, explore the uses of data visualizations, implement self-service BI solutions, and query a variety of data sources, including data cubes. Draw business insights from data analysis, and evaluate data for accuracy and objectivity.
Prerequisites: (152-115 with a minimum grade of C and 804-189 with a minimum grade of C)
156-105. Advanced Topics in Database. (3 Credits)
Research current database trends in the industry. Topics covered may include big data, cloud solutions such as Azure or AWS, in-memory databases, mobile databases, or other emerging database technologies.
Prerequisites: (156-103 with a minimum grade of C and 152-115 with a minimum grade of C and 107-119 with a minimum grade of C)
156-106. Data Warehouse Development. (4 Credits)
Discuss data cleansing; ETL and data synchronization strategies; data warehouse design/implementation, including star and snowflake schemas; and the creation of business intelligence (BI) solutions. Work collaboratively to implement a functional data warehouse from start to finish, including design implementation, ETL and a self-service BI solution.
Prerequisites: (156-102 with a minimum grade of C and 156-110 with a minimum grade of C) and 156-107 with a minimum grade of C
156-107. Data Modeling. (2 Credits)
Discover concepts of relational databases through data modeling. Learn about entities, attributes, relationships and the different types of keys in a database, and create conceptual, logical and physical data models for a variety of data types. Get an in-depth explanation of relational and dimensional models, and use Microsoft Access to query data.
Prerequisites: 156-108 (may be taken concurrently) with a minimum grade of C or 156-119 (may be taken concurrently) with a minimum grade of C
156-108. Intro to Databases & Reporting. (1 Credit)
Gain an introduction to relational databases, queries and reports. Use Microsoft Access to build queries and reports. Gain an understanding of SELECT queries, joins, reporting and the basics of relational database design.
156-109. Intro to SQL. (2 Credits)
Gain an introduction to Structured Query Language (SQL) through real-world scenarios. Learn SQL, including joins, aggregate functions, subqueries and the basics of security and permissions. Revisit database design and use table creation/data management commands.
Prerequisites: 156-108 (may be taken concurrently) with a minimum grade of C or 156-119 (may be taken concurrently) with a minimum grade of C
156-110. Data Visualization. (2 Credits)
This course introduces the principles and practice of effective data visualization, combining theory with hands-on application. Students will learn how to select and design charts, graphs and infographics that communicate insights clearly and persuasively. Emphasis will be placed on using Power BI to build interactive, impactful visualizations and dashboards. By the end of the course, students will be able to transform data into compelling stories that drive informed decision-making.
Prerequisites: 156-119 with a minimum grade of C and 156-109 with a minimum grade of C
156-111. Intro to Data Analytics. (2 Credits)
Learn to draw business insights from data. Explore descriptive and diagnostic data analytics. Identify trends and patterns within data using Power BI. Perform statistical analysis with Excel to determine causes and correlations.
Prerequisites: 804-189 with a minimum grade of C and 156-110 (may be taken concurrently) with a minimum grade of C and 156-109 (may be taken concurrently) with a minimum grade of c
156-112. Predictive Analytics. (2 Credits)
Gain an introduction to predictive analytics. Learn how to use standard Python libraries to prepare and load data for predictive models, create basic visualizations, and run machine learning algorithms to predict outcomes.
Prerequisites: 156-113 with a minimum grade of C and 804-189 (may be taken concurrently) with a minimum grade of C
156-113. Python Data Manipulation. (2 Credits)
Learn techniques to manipulate a variety of sources of data using standard Python libraries, including Pandas. Parse text and CSV files, extract data from a database, and clean and manipulate the data. Data will be output to either files or a database.
Prerequisites: 152-150 (may be taken concurrently) with a minimum grade of c or 152-101 (may be taken concurrently) with a minimum grade of C
156-114. Business Applications of AI. (3 Credits)
Learn about the field of artificial intelligence through the lens of various industry verticals. This course explores the various types of AI, how different industries leverage AI solutions, ethical uses of AI, and the benefits and risks of using AI to solve business problems.
156-115. Computer Vision. (2 Credits)
Explore various use cases of computer vision. Use common, pre-built machine learning algorithms to perform basic image processing and classification.
Prerequisites: 156-112 with a minimum grade of C and 156-114 with a minimum grade of C
156-116. Natural Language Processing. (2 Credits)
Explore the applications of natural language processing. Utilize machine learning models to perform sentiment analysis.
Prerequisites: 156-112 with a minimum grade of C and 156-114 with a minimum grade of C
156-117. Big Data Engineering. (3 Credits)
Explore big data architecture and systems. Build data pipelines with industry standard languages to ingest structured and unstructured data. Utilize the big data system to perform data mining and machine learning.
Prerequisites: 156-112 with a minimum grade of C and 156-102 with a minimum grade of C
156-118. AI/Data Capstone. (4 Credits)
Demonstrate mastery of program knowledge by working with a team to create a proof-of-concept AI solution or a data solution for a business problem. Learn to complete a project as a virtual team using industry-standard tools. Due to the nature of this course, you must be registered for this course a minimum of 2 weeks prior to the first day of class.
Prerequisites: 156-115 with a minimum grade of C and 156-112 with a minimum grade of C and (152-150 with a minimum grade of C or 152-101 with a minimum grade of C) and (156-106 with a minimum grade of C or 156-116 with a minimum grade of C)
156-119. Data Concepts. (2 Credits)
Gain an introduction to foundational concepts in data, information and data presentation/reporting. Learn basic spreadsheet concepts in Excel, including table creation, formulas, functions and cell formatting. Explore the basics of relational databases and queries in Microsoft Access. Learn the basics of data presentation through Excel pivot tables, charts and Access reports.
156-120. Data Analytics with Python. (2 Credits)
This course introduces students to the core techniques of exploratory data analysis using Python. Students will learn to visualize and interpret data patterns, examine relationships through correlation and design simple experiments. The course also covers key statistical concepts such as sampling and hypothesis testing to support data-driven decision-making. Hands-on projects will reinforce practical skills in preparing and analyzing data for real-world applications.
Prerequisites: 156-109 with a minimum grade of C and 156-111 with a minimum grade of C and 156-113 with a minimum grade of C
156-170. Management Information Systems. (3 Credits)
Explore how organizations use information systems to support operations, decision-making, and strategic goals. Examine systems design, data management, and the role of IT in organizational performance and competitive advantage.
156-171. Prescriptive Analytics & Opt. (3 Credits)
Learn to apply mathematical and computational techniques to recommend optimal decisions. Focus on optimization models, scenario analysis, and tools used to support business planning and resource allocation.
Prerequisites: 156-113 with a minimum grade of C and 804-189 with a minimum grade of C
156-172. Ethical & Societal Issues - AI. (3 Credits)
Examine the ethical, legal, and societal implications of artificial intelligence. Apply ethical frameworks to real-world AI applications and explore responsible use, fairness, transparency, governance, and the impact on individuals and communities.
Prerequisites: 156-114 with a minimum grade of C
156-173. Applied AI Strategies. (3 Credits)
Gain practical experience designing and implementing AI solutions in business and organizational settings. Emphasize strategic planning, implementation approaches, and alignment with business goals and workforce needs.
Prerequisites: 156-114 with a minimum grade of C
156-174. Digital Transformation. (3 Credits)
Examine how technology reshapes business models, processes, and organizational culture. Develop a governance plan to guide digital initiatives, incorporating innovation frameworks, change management principles, and digital strategy to lead transformation efforts effectively.
Prerequisites: 156-170 with a minimum grade of C
156-175. Generative AI Applications. (3 Credits)
Explore the business-focused use of generative AI tools such as large language models, image generators, and AI agents. Learn to design, implement, and evaluate generative AI solutions that enhance productivity, automate workflows, and support creative and strategic functions across business domains.
Prerequisites: 156-112 with a minimum grade of C
156-176. AI Implementation Capstone. (4 Credits)
Apply knowledge and skills from across the certificate by working on a real-world AI project or strategic initiative provided by an industry, campus or community partner. Students will contribute to the development of an AI-driven solution or implementation plan, incorporating ethical considerations, stakeholder impact and alignment with organizational goals. Final deliverables may include a prototype, strategic roadmap or business case, culminating in a presentation to peers and project stakeholders. Due to the nature of this course, you must be registered for this course a minimum of 2 weeks prior to the first day of class.
Prerequisites: 156-170 with a minimum grade of C and 156-171 with a minimum grade of C and 156-172 with a minimum grade of C and 156-173 with a minimum grade of C and 156-174 with a minimum grade of C and 156-175 with a minimum grade of C and 156-117 with a minimum grade of C
156-401. AI and the 21st Century Worker. (0.6 Credits)
Gain a foundational understanding of AI and how to integrate it into business operations. Explore fundamental concepts, practical applications, future trends and personal upward mobility strategies. Break down the mechanics and structures of AI technologies to help envision the role AI plays in the field. Leave inspired with practical ideas of how to integrate AI at work.
156-402. Everyday AI. (0.4 Credits)
Gain a foundational understanding of AI and its impact on daily life. Discover real-world applications in our everyday experiences and engage with AI through hands-on activities and demonstrations.
156-403. AI for Productivity. (0.4 Credits)
Explore practical applications of artificial intelligence to help you leverage AI for workplace productivity. Gain foundational knowledge, learn to apply AI tools (such as CoPilot, ChatGPT and Gemini) to everyday work scenarios, and develop skills to integrate AI into your regular workflows seamlessly.
156-404. Lean AI. (0.4 Credits)
Designed for AI practitioners, project managers and business professionals interested in lean methodologies, this workshop explores the intersection of lean principles and artificial intelligence. Learn to identify waste, streamline workflows and foster continuous improvement in AI projects through practical sessions and discussions.
156-405. Developing an AI Strategy. (0.4 Credits)
Designed specifically for owners and executives of small-to medium-sized businesses. Leverage AI for a competitive edge, evaluate your business's readiness for AI, and craft a strategic plan to integrate AI into your operations. Transform your business with actionable strategies and a clear path forward.
156-406. AI Strategy Development. (0.7 Credits)
Leverage AI for a competitive edge, evaluate your business's readiness for AI, and craft a strategic plan to integrate AI into your operations. Transform your business with actionable strategies and a clear path forward.
156-407. Artificial Intelligence 2-Hr. (0.2 Credits)
Explore practical applications of artificial intelligence (AI). Gain foundational knowledge, learn to apply AI tools (such as CoPilot, ChatGPT and Gemini) to everyday work scenarios, and develop skills to integrate AI into your regular workflows seamlessly.
156-408. Transactional Lean AI. (1.2 Credits)
Explore the intersection of lean principles and artificial intelligence. Learn to identify waste, streamline workflows and foster continuous improvement in AI projects.
156-409. Artificial Intelligence 3hr. (0.3 Credits)
Explore practical applications of artificial intelligence (AI). Gain foundational knowledge, learn to apply AI tools to everyday work scenarios, and develop skills to integrate AI into your regular workflows seamlessly.
156-410. Product Mgmt in the LLM Era. (0.3 Credits)
AI is shaping the future of product management, streamlining tasks, enhancing market research and improving decision-making. This workshop helps current or aspiring product managers, startup founders and technical leads understand how LLMs transform the product development lifecycle. Participants will learn to write PRDs optimized for AI-assisted development teams, evaluate build-vs-buy decisions and distinguish AI-native product opportunities from AI-enhanced features.
156-411. AI 101: AI & Machine Learning. (0.2 Credits)
Learn fundamental AI and machine learning concepts and real-world applications. This hands-on workshop provides participants with a clear understanding of AI fundamentals, machine learning concepts, and real-world business applications to help your organization leverage AI effectively. It will introduce you to foundational AI knowledge and engage you in hands-on activities using generative AI tools. Participants will learn practical applications for enhancing daily productivity and apply best practices for prompt engineering. This workshop demystifies artificial intelligence and empowers teams to integrate AI tools into their workflows confidently.
156-412. AI for Productivity 2hr. (0.2 Credits)
AI can assist with making our workload more manageable and efficient. This workshop explores practical applications of artificial intelligence to help you leverage AI for workplace productivity. You will gain foundational knowledge, learn to apply AI tools (such as CoPilot, ChatGPT and Gemini) to everyday work scenarios and develop skills to seamlessly integrate AI into your regular workflows.