Data Mining with SQL

This course on Data Mining with SQL is designed to equip participants with the essential skills needed to extract valuable insights from large datasets. Through a project-based and interactive approach, learners will engage in hands-on activities that emphasize real-world applications of SQL in data mining. Participants will not only gain proficiency in SQL but will also learn to apply machine learning techniques effectively, culminating in a final project that showcases their ability to analyze and interpret data.
The curriculum is structured to provide a comprehensive understanding of data mining concepts, tools, and methodologies. Participants will explore various data mining techniques, including clustering, classification, and association rules, while utilizing SQL for data manipulation and retrieval. The course encourages collaboration and knowledge sharing, with opportunities for learners to publish their findings in Cademix Magazine, enhancing their professional visibility and credibility.
Syllabus:
Introduction to Data Mining Concepts
Overview of SQL and Database Management Systems
Data Preprocessing Techniques for Mining
Exploratory Data Analysis using SQL
Clustering Techniques: K-Means and Hierarchical Clustering
Classification Techniques: Decision Trees and Random Forests
Association Rule Learning: Market Basket Analysis
Performance Evaluation of Data Mining Models
Implementation of Machine Learning Algorithms with SQL
Final Project: Data Mining Case Study using SQL

To develop proficiency in data mining techniques using SQL and to apply these skills in real-world scenarios.

Graduates, job seekers, business professionals, and optionally researchers or consultants.

Basic understanding of databases and SQL. Familiarity with programming concepts is beneficial but not mandatory.