Decompose problems into computational steps
Computing, Communication & Enterprise · Computer Science & Artificial Intelligence
CS-110Computational Thinking & Programming
Introduces programming, algorithms, data, abstraction, testing, and computational problem solving through research and applied examples.
Course outcomes
What students develop
Write, test, and document programs
Work with structured data and files
Evaluate correctness, efficiency, and limitations
Course content
Topics and questions
- Variables, control flow, and functions
- Data structures
- Files and data processing
- Testing and debugging
- Algorithms and computational reasoning
Methods & resources
Tools and environments
- Python development environment
- Version control
- Notebook and command-line tools
Evaluation
Demonstration of learning
- Programming exercises
- Data project
- Documented final application
Program relationships
Where this course fits
Core
Electrical Systems, Sensing & Robotics
Integrates electronics, embedded systems, sensors, controls, robotics, field automation, data acquisition, and engineering design.
Core
Computational Intelligence & Data Systems
Combines computer science, AI, data engineering, research computing, visualization, systems thinking, and responsible application.
Core
Robotics, Sensors & Field Automation
Electronics, sensing, embedded systems, robotics, controls, autonomy, field testing, and engineering documentation.
Core
Research Computing & Visualization
Programming, reproducible analysis, data systems, scientific visualization, computational notebooks, and research software practice.
Core
Research Computing Bootcamp
A concentrated workflow in programming, data management, notebooks, visualization, version control, and reproducible research.
Course inquiry
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