Learning Outcomes:

1. Organize MATLAB projects using structured directories and naming conventions

2. Implement MATLAB’s project management tools to streamline file access

3. Demonstrate best practices for script and function organization

4. Evaluate folder structures to ensure efficient file retrieval and maintenance

Learning Outcomes:

1. Identify common MATLAB workspace errors and interface glitches

2. Apply systematic troubleshooting techniques to resolve layout issues

3. Demonstrate recovery strategies from interface malfunctions

4. Verify the stability and performance of the MATLAB workspace post-troubleshooting

Learning Targets:

1. Develop modular and reusable code using script files, functions, and anonymous functions.

2. Incorporate appropriate commenting, code indentation, and documentation to enhance code readability.

3. Implement parameter validation and error handling to ensure code reliability.

4. Apply version control practices by integrating MATLAB projects with external repositories when applicable.

Modules

Learning Targets:

1. Utilize loops, conditional statements, and vectorized operations to implement algorithmic logic.

2. Employ MATLAB’s built-in debugging tools (e.g., breakpoints, the profiler) to identify and resolve code errors.

3. Optimize performance through efficient memory management and algorithm refinement.

4. Validate algorithm outputs through systematic testing and comparison with theoretical expectations.

Modules

Learning Targets:

1. Formulate mathematical models and translate them into MATLAB code using matrices and arrays.

2. Apply numerical methods, such as integration and differentiation, using built-in MATLAB functions.

3. Implement simulation routines using solvers (e.g., ODE solvers) to analyze dynamic systems.

4. Interpret simulation results and refine models based on quantitative analysis.

Modules

Learning Targets:

1. Generate a variety of 2D and 3D plots using built-in functions such as plot, scatter, and surf.

2. Customize graphs by adjusting axes, labels, legends, titles, and color schemes to enhance data clarity.

3. Employ data analytics techniques, including statistical analysis and regression, to interpret datasets.

4. Export visualizations in multiple formats for reporting and further analysis.

Modules

Learning Targets:

1. Identify and select appropriate MATLAB toolboxes, such as Signal Processing, Image Processing, and Control System toolboxes.

2. Demonstrate tool-specific functions and applications through practical examples and projects.

3. Integrate multiple toolboxes to develop comprehensive solutions for interdisciplinary STEM problems.

4. Leverage official documentation and community resources to troubleshoot and extend toolbox functionality.

Modules

Learning Targets:

1. Utilize MATLAB debugging tools (e.g., breakpoints, the profiler) to systematically identify performance bottlenecks.

2. Analyze and interpret profiling data to refactor and optimize code for improved execution speed.

3. Apply best practices in algorithm design and data structure selection to improve efficiency.

4. Benchmark MATLAB functions and scripts against performance metrics to ensure optimal resource utilization.

Modules