Mastery in Advanced Machine Learning & Applied AI™

About this course

This comprehensive program is designed to transform learners into experts in advanced machine learning and applied AI, covering both supervised and unsupervised learning techniques. The course focuses on the practical application of cutting-edge methods and algorithms, enabling learners to tackle complex real-world problems across various domains.Course Outline1. Introduction to Machine LearningUnderstanding the basics of machine learning and its types: supervised, unsupervised, and reinforcement learning.2. Machine Learning - Reinforcement LearningDive deep into reinforcement learning, covering key concepts such as agents, environments, and rewards.3. Introduction to Supervised LearningLearn the principles of supervised learning, including classification and regression tasks.4. Machine Learning Model Training and EvaluationExplore how to train machine learning models and evaluate their performance using metrics like accuracy, precision, recall, and F1 score.5. Machine Learning Linear RegressionUnderstand the concept of linear regression and its application in predicting continuous values.6. Machine Learning - Evaluating Model FitTechniques for assessing how well a model fits the data, including error metrics and residual analysis.7. Application of Machine Learning - Supervised LearningHands-on application of supervised learning techniques to real-world problems.8. Introduction to Multiple Linear RegressionExplore multiple linear regression and its application when dealing with multiple predictor variables.9. Multiple Linear Regression - Evaluating Model PerformanceLearn how to assess the performance of multiple linear regression models using metrics like R² and Adjusted R².10. Machine Learning Application - Multi

Course objectives

• to transform learners into experts in advanced machine learning
• to cover practical applications of machine learning methods
• to enable learners to tackle complex real-world problems