Please be informed that this site uses cookies.

+971 56 800 6744

+971 2 622 2605

Course Description

This intensive 5-day program offers a practical and comprehensive introduction to Data Mining and Analytics. Participants will explore key concepts, methods, and technologies used to extract meaningful insights from large data sets. The course covers the complete data mining process—from data cleaning to model building to actionable insights—combined with modern analytics techniques using real-world examples. Whether you’re aiming to drive smarter decisions, discover hidden patterns, or predict future outcomes, this training will equip you with essential tools and frameworks for effective data-driven leadership.

Course Objectives

Upon the successful completion of this course, each participant will be able to:

  • Understand the fundamentals of data mining processes and analytics methodologies
  • Prepare, clean, and transform data for mining and modeling activities
  • Apply supervised and unsupervised learning techniques (e.g., classification, clustering, association rules)
  • Evaluate, validate, and interpret data models effectively
  • Leverage analytics tools and visualization techniques to communicate findings and insights
  • Integrate ethical considerations and best practices into data mining projects

Who Should Attend?

This course is designed for Data Analysts, Business Intelligence Professionals, IT Professionals interested in Data Science, Marketing Analysts, Operations Managers, Research Analysts & Anyone seeking foundational skills in data mining and analytics for decision-making.

Course Agenda

Day 1

Registration, Welcome & Introduction

Pre-Test

Introduction to Data Mining and Analytics

  • What is Data Mining?
  • The Data Mining Process (CRISP-DM framework)
  • Types of Data: Structured, Semi-structured, Unstructured
  • Key Analytics Concepts: Descriptive, Predictive, Prescriptive
  • Tools Overview: (Excel, RapidMiner, Python basics)

Day 2

Data Preparation and Exploration

  • Data Cleaning and Preprocessing
  • Handling Missing Values, Outliers, and Noise
  • Feature Engineering and Feature Selection
  • Exploratory Data Analysis (EDA)
  • Data Visualization Principles

Day 3

Key Data Mining Techniques

  • Supervised Learning: Classification and Regression
  • Decision Trees, k-Nearest Neighbors (k-NN)
  • Unsupervised Learning: Clustering (K-Means, Hierarchical Clustering)
  • Association Rule Mining (Apriori Algorithm)

Day 4

Model Evaluation and Interpretation

  • Training, Validation, and Testing Splits
  • Performance Metrics (Accuracy, Precision, Recall, F1-Score, ROC)
  • Overfitting and Underfitting
  • Model Tuning and Cross-Validation
  • Interpreting Results and Deriving Insights

Day 5

Advanced Topics and Real-World Applications

  • Introduction to Big Data and Machine Learning in Analytics
  • Text Mining and Sentiment Analysis Basics
  • Ethics in Data Mining (Bias, Privacy, Responsible Use)
  • Analytics Strategy for Organizations

Post-Test

End of the Course

Assessment Methodology

All courses conducted by EdTech will begin with a Pre-evaluation and end with a Post-evaluation. The instructor will evaluate the knowledge and skills of the participants according to the feedback given by participants. This will help to recognize the benefits and the level of knowledge gained by participants through the course.

Training Methodology

Facilitated by a highly qualified specialist, who has extensive knowledge and experience; this program will be conducted using extensively interactive methods, encouraging participants to share their own experiences and apply the program material to real-life work situations in order to stimulate group discussions and improve the efficiency of the subject coverage.

Percentages of the total course hour classification are:

  • ​40% Theoretical lectures, Concepts and approach
  • 20% Motivation to develop individual skill and Techniques
  • 20% Case Studies and Practical Exercises
  • 20% Topic General Discussions and interaction

Course Manual

Participants will be provided with comprehensive presentation material as reference manual. This presentation material is a compilation of core valuable information, references, presentation methods and inspiring reading which will be used as a part of the material guide.

Course Certificate

At the completion of the course, all participants who successfully accomplished the required contact hours will receive an EdTech Training Participation Certificate as a testimony to their commitment to professional development and further education.

Why Edtech ?

  • Industry Experienced; Internationally Qualified Trainers
  • Hands-on Practical Sessions & Assignments
  • Intensive Study materials
  • Flexible Schedules
  • Realistic training methodology
  • High-Quality Training in Affordable Course Fees
  • Achievement Certificate, as approved by the Ministry of Education (Abu Dhabi Center for Technical and Vocational Education Training - ACTVET), HABC, AWS, IAOSHE, SHRM, etc.