Course Code: matlabproj
Duration: 49 hours
Course Outline:

Module 1: MATLAB Fundamentals (7 hours)

  • Introduction to MATLAB environment and interface
  • Basic syntax, variables, and data types
  • Vectors, matrices, and operations
  • Control flow: loops and conditional statements
  • Functions, scripts, and debugging techniques
  • Hands-on exercises and mini-project

Module 2: MATLAB for Data Processing and Visualization (14 hours – split into two sessions of 7 hours each)

Session 1

  • Data import and export (CSV, Excel, databases)
  • Data cleaning, filtering, and transformation
  • Statistical analysis and data summarization

Session 2

  • Plotting and visualization techniques (2D, 3D plots, dashboards)
  • Interactive graphics and report generation
  • Case study: Engineering data visualization

Module 3: Machine Learning with MATLAB (14 hours – split into two sessions of 7 hours each)

Session 1

  • Overview of machine learning concepts
  • Supervised vs. unsupervised learning
  • Feature selection and preprocessing for ML models

Session 2

  • Classification, regression, and clustering techniques
  • Introduction to MATLAB’s Machine Learning Toolbox
  • Hands-on project: Building and evaluating an ML model

Module 4: Signal Pre-processing and Feature Extraction for Data Analytics (7 hours)

  • Basics of signal processing in MATLAB
  • Noise reduction techniques (filtering, wavelet transform)
  • Feature extraction for time-series data
  • Fourier and wavelet analysis for engineering applications
  • Practical applications: Sensor data processing in engineering

Module 5: Predictive Maintenance with MATLAB (7 hours)

  • Introduction to predictive maintenance concepts
  • Sensor data acquisition and preprocessing
  • Anomaly detection techniques
  • Fault prediction models and remaining useful life (RUL) estimation
  • Case study: Implementing predictive maintenance for industrial equipment