AI & Machine Learning

What Will You Learn?

• Understand the fundamentals of Artificial Intelligence, Machine Learning, and Deep Learning
• Differentiate between Supervised, Unsupervised, and Reinforcement Learning
• Apply Linear Regression and Logistic Regression for prediction problems
• Use Decision Trees, Random Forest, and SVM for classification tasks
• Handle missing data, outliers, and categorical encoding using Python
• Perform Feature Engineering to improve model performance
• Split data into training and testing sets properly
• Detect and prevent Overfitting
• Evaluate models using Confusion Matrix, Precision, Recall, and Accuracy
• Implement Machine Learning models using Scikit-Learn in Google Colab
• Understand Gradient Descent and how AI models learn
• Apply Hyperparameter Tuning for better accuracy
• Understand AI Ethics, Bias, and real-world risks
• Build and evaluate a real Loan Prediction project