- Teacher: Admin User
In this course, students will learn how to transform raw data into meaningful knowledge by exploring the fundamental concepts, methods, and applications of data mining. They will gain hands-on experience with data preprocessing, classification, clustering, association rule mining, and anomaly detection, while also developing skills to evaluate and validate models for accuracy and reliability. By working with real-world datasets and modern tools, students will not only understand the theory behind data mining algorithms but also learn to apply them effectively in solving practical problems across diverse domains.
This training course, Introduction to Machine Learning, provides a comprehensive overview of fundamental concepts and techniques in the field. You'll learn the core principles of how machines learn from data, distinguishing between different types of learning, such as supervised and unsupervised learning. The course covers key algorithms like linear regression, decision trees, and clustering, explaining their practical applications. You'll also gain hands-on experience by building your own basic machine learning models, exploring data preprocessing, model evaluation, and the essential tools used by data scientists. This course is ideal for beginners looking to build a solid foundation in machine learning.
- Teacher: Admin User