UNIDAD DIDÁCTICA 1. DATA MINING OR DATA MINING AND AUTOMATIC LEARNING

1. Introduction to Data Mining and Machine Learning
2. KDD Process
3. Data Mining Models and Techniques
4. Application Areas
5. Text Mining and Web Mining
6. Data mining and marketing

UNIT DIDACTIC 2. HADOOP ECOSYSTEM

1. What is Hadoop? Relationship with Big Data
2. Installation and configuration of Hadoop infrastructure and ecosystem
3. HDFS file system
4. MapReduce with Hadoop
5. Apache Hive
6. Apache Hue
7. Apache Spark

DIDACTIC UNIT 3. WEKA AND DATA MINING

1. What is Weka?
2. Data Mining Techniques in Weka
3. Weka Interfaces
4. Attribute Selection

UNIT DIDACTIC 4. 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 5. DATA STRUCTURE EXTRACTION: CLUSTERING

1. Introduction
2. Algorithms

TEACHING UNIT 6. RECOMMENDATION SYSTEMS

1. Introduction
2. Collaborative filtering
3. Clustering
4. Hybrid recommender systems

TEACHING UNIT 7. CLASSIFICATION

1. Classifiers
2. Algorithms

UNIT DIDACTIC 8. NEURAL NETWORKS AND DEEP LEARNING

1. Components
2. Learning

UNIT DIDACTIC 9. ELECTION SYSTEMS

1. Introduction
2. The process of moving from DSS to IDSS
3. Application Cases