Oct 23, 2026  
2026-2027 Academic Catalog 
    
2026-2027 Academic Catalog
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CNET 1000 - IT Exploration


Credits: 2

Catalog Description
This course introduces students to major IT career disciplines. It is intended for students exploring a career in IT and helps identify specific areas of interest. The four areas include systems infrastructure and networking, security, application development, and analytics. Students participate in hands-on activities that help them learn the concepts related to these career areas.

Additional fee to student: No

Learner Outcomes
  1. Explore software, hardware, and network components that make up the IT infrastructure supporting businesses and organizations.
  2. Understand the importance of cyber security and how this applies to software, system settings, and the protection of personal information.
  3. Recognize how software is a fundamental part of our digital world and learn about application development.
  4. Produce computer programs and learn about various types of software creation.
  5. Develop an understanding of the various careers related to data science and analytics.
  6. Examine the types of data-intensive skills that provide competitive advantage to businesses and use a simulation to work on analytical skills and visualization using provided dataset and worksheets.

Major Areas of Course Content
  1. Basic Computer Hardware
  2. Fundamentals of Computer Operating Systems
  3. Basic Networking Technologies
  4. Internet Computing Technologies
  5. Programming Languages Defined
  6. Command-Line Programming
  7. Introduction to Graphics
  8. Programming Techniques
  9. Introduction to Information Security
  10. Internet Privacy and Security
  11. Hardening Networks & Systems
  12. History and evolution of business intelligence, analytics, and informatics
  13. Components of Business Analytics
  14. Analytics and Competitive Advantage
  15. The D.A.T.A. Framework
  16. Data summarization using formulas and functions
  17. Data mining, organization, and classification
  18. Slicing and dicing - Data reduction and extraction
  19. Data presentation and visualization

Credit for Prior Learning Options
No credit for prior learning option is available for this course.



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