Data Mining, Artificial Intelligence, and Machine Learning

TEACHING UNIT 1. DATA MINING 1. Data Mining 2. What Can We Do with Data Mining? 3. What Are the Applications of Data Mining? 4. Data Mining Methodology 5. Some Statistical Techniques Used in Data Mining 6. Decision Trees 7. Induction Rules 8. Bayesian Networks 9. Genetic Algorithms TEACHING UNIT 2. THE DATA MINING CYCLE 1. The Data Mining Cycle 2. Text Mining and Web Mining 3. Data Mining and Marketing TEACHING UNIT 3. INTRODUCTION TO ARTIFICIAL INTELLIGENCE 1. Introduction to Artificial Intelligence 2. History 3. The Importance of AI TEACHING UNIT 4. ALGORITHMS APPLIED TO ARTIFICIAL INTELLIGENCE 1. Algorithms Applied to Artificial Intelligence TEACHING UNIT 5. RELATIONSHIP BETWEEN ARTIFICIAL INTELLIGENCE AND BIG DATA 1. The Relationship Between Artificial Intelligence and Big Data 2. AI and Big Data Combined 3. The Role of Big Data in AI 4. AI Technologies Currently Used with Big Data TEACHING UNIT 6. EXPERT SYSTEMS 1. Expert Systems 2. Structure of an Expert System 3. Inference: Types 4. Phases of Building a System 5. Performance and Improvements 6. Domains of Application 7. Creating an Expert System in C# 8. Adding Uncertainty and Probabilities TEACHING UNIT 7. INTRODUCTION TO MACHINE LEARNING 1. Introduction 2. Classification of Machine Learning Algorithms 3. Examples of Machine Learning 4. Differences Between Machine Learning and Deep Learning 5. Types of Machine Learning Algorithms 6. The Future of Machine Learning TEACHING UNIT 8. DATA STRUCTURE EXTRACTION: CLUSTERING 1. Introduction 2. Algorithms TEACHING UNIT 9. RECOMMENDATION SYSTEMS 1. Introduction 2. Collaborative Filtering 3. Clustering 4. Hybrid Recommendation Systems TEACHING UNIT 10. CLASSIFICATION 1. Classifiers 2. Algorithms TEACHING UNIT 11. NEURAL NETWORKS AND DEEP LEARNING 1. Components 2. Learning TEACHING UNIT 12. DECISION SUPPORT SYSTEMS 1. Introduction 2. The Transition from DSS to IDSS 3. Application Cases