Live Course Module: MATLAB Course for Data Science

Total Duration: 36 Hours (6 Weeks)

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Week 1: Foundations of MATLAB & Data Science (6 Hours)

1. Introduction to MATLAB for Data Science (2 hrs)

   • MATLAB environment, IDE & workspace

   • Scripts vs Functions

   • Basic syntax & operations

   • Data types (arrays, tables, structures, cells)

2. Data Importing & Preprocessing (2 hrs)

   • Reading CSV, Excel, JSON, SQL, and web data

   • Handling missing values

   • Data cleaning techniques

3. Exploratory Data Analysis (EDA) with MATLAB (2 hrs)

   • Summary statistics

   • Data visualization (scatter, histogram, boxplot)

   • Detecting outliers

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Week 2: Data Manipulation & Visualization (6 Hours)

4. Working with Large Datasets (2 hrs)

   • MATLAB tables & timetable

   • Data indexing & filtering

   • Grouping, joining & merging datasets

5. Advanced Data Visualization (2 hrs)

   • Heatmaps, bar charts, pie charts

   • 3D plots, surface & contour plots

   • Interactive dashboards with MATLAB apps

6. MATLAB for Data Wrangling (2 hrs)

   • String manipulation

   • Feature engineering

   • Handling categorical data

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Week 3: Statistics & Probability in MATLAB (6 Hours)

7. Descriptive & Inferential Statistics (2 hrs)

   • Measures of central tendency & dispersion

   • Hypothesis testing (t-test, ANOVA, chi-square)

8. Probability Distributions (2 hrs)

   • Normal, binomial, Poisson distributions

   • Random number generation & simulations

9. Correlation & Regression Analysis (2 hrs)

   • Correlation coefficients

   • Simple & multiple regression models

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Week 4: Machine Learning with MATLAB (6 Hours)

10. Introduction to Machine Learning in MATLAB (2 hrs)

    • Supervised vs Unsupervised learning

    • MATLAB Machine Learning Toolbox

11. Supervised Learning Models (2 hrs)

    • Linear & logistic regression

    • Decision trees, SVM, KNN

12. Unsupervised Learning Models (2 hrs)

    • Clustering (K-means, hierarchical)

    • Dimensionality reduction (PCA)

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Week 5: Deep Learning & AI with MATLAB (6 Hours)

13. Neural Networks Basics (2 hrs)

    • Perceptron, MLP basics

    • MATLAB Neural Network Toolbox

14. Deep Learning Models (2 hrs)

    • CNN for image data

    • RNN/LSTM for sequential data

15. MATLAB & AI Integration (2 hrs)

    • Pre-trained models

    • Transfer learning

    • GPU acceleration

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Week 6: Big Data, Cloud & Capstone Project (6 Hours)

16. MATLAB & Big Data Tools (2 hrs)

    • Working with tall arrays & distributed computing

    • Integration with Hadoop & Spark

17. MATLAB with Cloud & Databases (2 hrs)

    • MATLAB Online & MATLAB Drive

    • Connecting with SQL/NoSQL databases

18. Capstone Project & Presentation (2 hrs)

    • End-to-end Data Science project in MATLAB

    • Data preprocessing → ML model → Visualization

    • Group project presentation

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Course Outcomes

✅ Strong foundation in MATLAB for data science workflows
✅ Ability to preprocess, analyze, and visualize data efficiently
✅ Practical experience in building ML & AI models in MATLAB
✅ Exposure to big data and cloud integration with MATLAB
✅ Completion of a capstone project for portfolio