Name: Data Mining
Availability: InStock

Data Mining

Embark on an in-depth exploration of Data Mining over an intensive course. Delve into the core of the Knowledge Discovery in Databases (KDD) process, uncovering patterns from vast data sets using methodologies from AI, machine learning, and statistics. Whether you're using open-source tools or enterprise software, this course equips you with the knowledge to extract actionable insights from data.

What will you learn?

Dive into the Fascinating World of Data Mining with Our Comprehensive Workshop. This course is designed for those with a foundational understanding of relational data structures and SQL. In this immersive journey, participants will:

• Understand the KDD Process: Grasp the significance of data mining as the primary analysis step in Knowledge Discovery in Databases.

• Delve into Data Mining Foundations: Explore its origins from AI, machine learning, statistics, and database systems.

• Master the Core Tasks: Learn about anomaly detection, association rule learning, clustering, classification, regression, and summarization.

• Optimize the Data Mining Process: Familiarize with pre and post-processing techniques, visualization strategies, and online updating.

• Explore Real-world Applications: Understand how data mining shapes various industries, from agriculture to meteorology, and its role in advanced analytics scenarios.By the end of the course, you will be adept at leveraging various data mining methodologies to drive decision-making and gain insights.

Requirements:

• Relational Data Proficiency: A good understanding of relational data structures.

• SQL Knowledge: Familiarity with SQL and its primary operations.

Course Outline*:

*We know each team has their own needs and specifications. That is why we can modify the training outline per need.

1. Introduction to Data Mining

Understanding the Role of Data Mining in KDD
Its Origins in Computer Science and Related Fields
Key Principles: Discovering Patterns in Large Datasets

2. Foundations and Methodological Sources

Drawing from Artificial Intelligence
Insights from Machine Learning and Statistics
Database Systems' Influence on Data Mining

3. Deep Dive into Data Mining Processes

Database and Data Management Aspects
Steps in Data Pre-processing
Model Considerations and Inference Techniques
Metrics for Assessing Interestingness and Complexity
Post-processing Techniques and Strategies

4. Visualization and Data Updating

Techniques for Visualizing Discovered Structures
The Role and Importance of Online Updating

5. Core Tasks of Data Mining

The Art of Anomaly Detection
Association Rule Learning and Dependency Modeling
Techniques in Clustering and Classification
Data Summarization and Regression

6. Exploring Applications of Data Mining

Data Mining in Various Sectors: Agriculture, Meteorology, and More
The Role of Data Mining in Business, Customer, and Behavioral Analytics
Insights into Java Data Mining, Open-source Intelligence, and More
Advanced Topics: Inference Attack, Path Analysis, and Reactive Business Intelligence.

Hands-on learning with expert instructors at your location for organizations.

4.347€*