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Student Learning Outcomes

Discipline: Degree: AS - Big Data Analytics - S0845
Course Name Course Number
Big Data Integration and Processing CISD 42
  • Use various Big Data frameworks and tools.
  • Use various sources and techniques to retrieve, acquire, and ingest Big Data.
  • Integrate Big Data.
  • Process Big Data at rest and in motion.
  • Get value out of Big Data by using a 5-step process to structure an analysis.
Big Data Modeling and Analysis CISD 43
  • Use various tools and programming language to perform Big Data graph analytics.
  • Use various tools to perform Big Data modeling.
  • Differentiate between data mining and predictive analytics.
  • Use various tools and programming language to perform Big Data mining and text mining.
  • Use various tools and programming language to perform Big Data predictive analytics.
Computer Information Systems CISB 11
  • Students completing CISB 11 - Computer Information Systems will be able to identify five ways to protect a computer from harmful attacks.
  • Students completing CISB 11 - Computer Information Systems will know the six phases of the system development life cycle and two activities that occur in each phase.
  • Students completing CISB 11 - Computer Information Systems will know the four primary operations of a computer and the hardware that performs these operations.
  • Students completing CISB 11 - Computer Information Systems will be able to define the following Internet terms: Internet, World Wide Web, browser, IP address, URL
Database Management - Microsoft SQL Server CISD 21
  • Students completing CISD21 - SQL Server Lecture will be able to understand functions for simplifying daily database tasks.
  • Students completing CISD21 will be able to understand the summary queries and know how to use the aggregate functions.
  • Students completing CISD 21 - Database Management - Microsoft SQL Server Lecture will be able to update database data using the SQL Server Data Manipulation Language commands.
  • Students completing CISD 21 - Database Management - Microsoft SQL Server Lecture will be able to create a program using scripts and stored procedures.
Database Management - Microsoft SQL Server Laboratory CISD 21L
  • Students completing CISD21L - Microsoft SQL Server Lab will be able to use the aggregation functions to create summary queries for database tables.
  • Student completing CISD21L - SQL Server Lab will be able to create database triggers to enforce referential integrity.
Database Management - Oracle CISD 31
  • Students completing CISD31 will understand exception handling and know how to take the actions when exceptions are raised.
  • Students completing CISD 31 will be able to understand subqueries.
  • Students completing CISD 31 - Database Management - Oracle Lecture will be able to create queries to retrieve data from multiple tables using Oracle functions, views, and scripts.
  • Students completing CISD 31 - Database Management - Oracle Lecture will be able to use decision making statements, loops, and cursors in order to create a business application.
Database Management - Oracle Laboratory CISD 31L
  • Students completing CISD 31L will be able to create queries to retrieve data from multiple tables using Oracle functions, views, and scripts.
  • Students completing CISD 31L will be able to use decision making statements, loops, and cursors in order to create a business application.
Elementary Statistics Math 110
  • Demonstrate an understanding of, and ability to use, basic ideas of statistical processes, including hypothesis tests and confidence interval estimation.
  • Assess how data were collected and recognize how data collection affects what conclusions can be drawn from the data. Identify appropriate graphs and summary statistics for variables and relationships between them and correctly interpret information from graphs and summary statistics.
  • Identify appropriate statistical techniques and use technology-based statistical analysis to describe, interpret, and communicate results. Evaluate ethical issues in statistical practice.
  • Describe and apply probability concepts and distributions.
Elementary Statistics -Honors Math 110H
  • Describe and apply probability concepts and distributions.
  • Assess how data were collected and recognize how data collection affects what conclusions can be drawn from the data. Identify appropriate graphs and summary statistics for variables and relationships between them and correctly interpret information from graphs and summary statistics.
  • Identify appropriate statistical techniques and use technology-based statistical analysis to describe, interpret, and communicate results. Evaluate ethical issues in statistical practice.
  • Students will be able to use sample statistics to develop a confidence interval for population parameters. Using sample statistics from one or more samples, students will be able to test a claim made about a population parameter.
Introduction to Data Science CISD 41
  • Use Programming language and other tools to scrape, clean, and process data.
  • Use data management techniques to store data locally and in cloud infrastructures.
  • Use statistical methods and visualization to quickly explore data.
  • Apply statistics and computational analysis to make predictions based on data.
  • Effectively communicate the outcome of data analysis using descriptive statistics and visualizations.
Programming in Python CISP 71
  • Recognize and appropriately use Python packages.
  • Evaluate appropriate use of abstract classes, methods, or both as they apply to inheritance.
  • Apply the most current version of event handlers and methods to projects.
  • Utilize the appropriate programming constructs including selection, sequence, and iteration in programming projects.
  • Write, organize, and assemble program documentation.
  • Design programs leading to reusable code through the concepts of encapsulation, inheritance, and polymorphism.
  • Incorporate exception handling in Python projects.
Programming in Python Laboratory CISP 71L
  • Create object-oriented programs in Python.
  • Evaluate when to use various Python constructs for decision-making (if and switch statements), iteration
  • Create user interfaces with various components and incorporate event handling.