Oct 23, 2026  
2026-2027 Academic Catalog 
    
2026-2027 Academic Catalog
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CSCI 1101 - Introduction to Computer Science and Problem-Solving


Credits: 3

Catalog Description
This course provides an overview of computer science topics with an emphasis on problem-solving and algorithm development. Algorithm development will be taught using pseudocode and diagrams. Computer programs will be written utilizing one or more computer languages. Topics to be included are computer architecture, networks, Boolean logic, and computer ethics.

Prerequisite(s) (must have a grade of C or better): MATH 0240  or appropriate score on the math placement test or equivalent
Additional fee to student: No

Learner Outcomes
  1. Describe algorithms and their role in solving problems.
  2. Develop algorithmic solutions using appropriate programming structures.
  3. Express algorithms using pseudocode, flow-charts or other design notation.
  4. Demonstrate knowledge of common algorithms, such as binary search, finding the minimum/maximum value in a list, and quadratic sort.
  5. Demonstrate the ability to select an appropriate algorithm for solving a problem.
  6. Implement algorithms with a high-level programming language and provide simple documentation.
  7. Express numbers in binary format.
  8. Express and simplify Boolean expressions.
  9. Describe the Von Neumann architecture and interaction between the processor and memory.
  10. Explain how data communication works and give examples of networks.
  11. Explain the role of the operating system in a digital system.
  12. Describe emerging technologies such as cloud computing, artificial intelligence, data analytics and others.
  13. Describe different types of application software including database, internet, and games.
  14. Explain security and privacy threats and describe measures to prevent them.
  15. Describe the evolution of digital systems and their past, present, and potential future impact on human society and the ethical implications thereof.

Major Areas of Course Content
  1. Concept of an algorithm as a basis for computer science
  2. Algorithm design, use in problem-solving, and basic performance metrics
  3. Overview of programming languages and paradigms
  4. Common programming structures and their use in algorithms
  5. Introduction to binary numbers
  6. Introduction to Boolean algebra
  7. Introduction to computer system organization
  8. Introduction to data communications and networks
  9. System software (including operating systems, language translation)
  10. Emerging technologies (e.g. cloud computing, data analytics, mobile computing, internet of things, and artificial intelligence)
  11. Application software including database, internet, and electronic commerce
  12. The role of games, simulation, and virtual reality in society
  13. Overview of occupations in computing-related fields
  14. Security, privacy, ethics, and other societal and legal issues
  15. Digital systems evolution and impact on society and the economy

Credit for Prior Learning Options
Course-Specific Exam

Credit for Prior Learning Option Procedure(s)
Students must achieve an average score of 70% on all exams used to evaluate regular students.



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