AIMLFLGLogical OperationsLG-AIMLF1.0<ul> <li>Understand the importance, principles, and fields of AI</li><li>Implement basic artificial intelligence concepts with Python</li><li>Apply regression and classification concepts to real-world problems</li><li>Perform predictive analysis using decision trees and random forests</li><li>Carry out clustering using the k-means and mean shift algorithms</li><li>Understand the fundamentals of deep learning via practical examples</li></ul><h5>1: Principles of Artificial Intelligence </h5> <ul> <li>Introduction</li><li>Fields and Applications of Artificial Intelligence</li><li>AI Tools and Learning Models</li><li>The Role of Python in Artificial Intelligence</li><li>Python for Game AI</li><li>Summary</li></ul><h5>2: AI with Search Techniques and Games </h5><ul> <li>Introduction</li><li>Heuristics</li><li>Pathfinding with the A* Algorithm</li><li>Game AI with the Minmax Algorithm and Alpha-Beta Pruning</li><li>Summary</li></ul><h5>3: Regression </h5><ul> <li>Introduction</li><li>Linear Regression with One Variable</li><li>Linear Regression with Multiple Variables</li><li>Polynomial and Support Vector Regression</li><li>Summary</li></ul> <h5>4: Classification </h5><ul> <li>Introduction</li><li>The Fundamentals of Classification</li><li>Classification with Support Vector Machines</li><li>Summary</li></ul><h5>5: Using Trees for Predictive Analysis </h5><ul> <li>Introduction to Decision Trees</li><li>Random Forest Classifier</li><li>Summary</li></ul><h5>6: Clustering </h5><ul> <li>Introduction to Clustering</li><li>The k-means Algorithm</li><li>Mean Shift Algorithm</li><li>Summary</li></ul><h5>7: Deep Learning with Neural Networks </h5><ul> <li>Introduction</li><li>TensorFlow for Python</li><li>Introduction to Neural Networks</li><li>Deep Learning</li><li>Summary</li></ul> <h5>8: Appendix A </h5><ul> <li>Lesson 1: Principles of AI</li><li>Lesson 2: AI with Search Techniques and Games</li><li>Lesson 4: Classification</li><li>Lesson 5: Using Trees for Predictive Analysis</li><li>Lesson 6: Clustering</li><li>Lesson 7: Deep Learning with Neural Networks</li></ul>- Understand the importance, principles, and fields of AI - Implement basic artificial intelligence concepts with Python - Apply regression and classification concepts to real-world problems - Perform predictive analysis using decision trees and random forests - Carry out clustering using the k-means and mean shift algorithms - Understand the fundamentals of deep learning via practical examples1: Principles of Artificial Intelligence - Introduction - Fields and Applications of Artificial Intelligence - AI Tools and Learning Models - The Role of Python in Artificial Intelligence - Python for Game AI - Summary 2: AI with Search Techniques and Games - Introduction - Heuristics - Pathfinding with the A* Algorithm - Game AI with the Minmax Algorithm and Alpha-Beta Pruning - Summary 3: Regression - Introduction - Linear Regression with One Variable - Linear Regression with Multiple Variables - Polynomial and Support Vector Regression - Summary 4: Classification - Introduction - The Fundamentals of Classification - Classification with Support Vector Machines - Summary 5: Using Trees for Predictive Analysis - Introduction to Decision Trees - Random Forest Classifier - Summary 6: Clustering - Introduction to Clustering - The k-means Algorithm - Mean Shift Algorithm - Summary 7: Deep Learning with Neural Networks - Introduction - TensorFlow for Python - Introduction to Neural Networks - Deep Learning - Summary 8: Appendix A - Lesson 1: Principles of AI - Lesson 2: AI with Search Techniques and Games - Lesson 4: Classification - Lesson 5: Using Trees for Predictive Analysis - Lesson 6: Clustering - Lesson 7: Deep Learning with Neural Networks3 days1990.00