Understanding AI Concepts: Gain a strong foundation in AI and Machine Learning principles. • Data Preparation: Learn techniques to preprocess, clean, and prepare data for ML models. • Model Building: Develop models using linear regression, forecasting, classification, clustering, decision trees, random forests, support vector machines, and neural networks. • Model Evaluation and Tuning: Train, evaluate, and fine-tune ML models to achieve optimal performance. • Operationalization of Models: Deploy and maintain ML models in production environments. • Real-World Applications: Apply learned techniques to solve practical business problems using AI and ML.