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Section outline

  • Module 1: Introduction to AI and ML (3 hours)

    • AI vs. ML vs. Deep Learning, industry applications

    Module 2: Python for Data Analysis (5 hours)

    • Pandas, NumPy, Matplotlib, and data preprocessing
  • Module 3: Supervised Learning (7 hours)

    • Regression, classification, and model evaluation metrics
  • Module 4: Unsupervised Learning (5 hours)

    • Clustering, dimensionality reduction, and association rules

    Module 5: Model Evaluation and Optimization (3 hours)

    • Cross-validation, hyperparameter tuning, and regularization
  • Module 6: Introduction to Deep Learning (5 hours)

    • Neural networks, TensorFlow, and Keras basics

    Module 7: Advanced Deep Learning Techniques (4 hours)

    • CNNs, RNNs, and transfer learning
  • Module 8: Deployment of AI Models (2 hours)

    • Saving, loading, and deploying models

    Module 9: Ethics and Future of AI (1 hour)

    • Bias, fairness, and emerging trends