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Course Description

The AI & Data Mining Training provides participants with a comprehensive understanding of artificial intelligence concepts and data mining techniques used to extract meaningful patterns, predictions, and insights from large and complex datasets. The program bridges theory and applied analytics, enabling participants to leverage AI-driven models and data mining methods to support smarter decision-making and business intelligence initiatives.

Course Objectives

Upon completion of this course, participants will be able to:

  • Understand core AI concepts and data mining methodologies.
  • Identify suitable AI and data mining techniques for different business problems.
  • Prepare, clean, and transform data for analytical modelling.
  • Apply classification, clustering, and prediction concepts.
  • Interpret analytical results and translate them into actionable insights.
  • Understand ethical, governance, and risk considerations in AI initiatives.

Who Should Attend?

This course is designed for data analysts, business analysts, IT professionals, engineers, managers, and decision-makers involved in data-driven and AI-enabled projects.

Course Agenda

Registration

Welcome & Introduction

Pre-Test

Day 1: Foundations of AI & Data Mining

  • Introduction to Artificial Intelligence and Data Mining
  •  AI vs. Machine Learning vs. Data Mining
  • Types of data: structured, semi-structured, unstructured
  •  Data mining process models (CRISP-DM)
  •  Business problem identification and analytical framing

Day 2: Data Preparation & Exploratory Analysis

  • Data collection and integration from multiple sources​
  • Data cleaning, preprocessing, and transformation techniques
  • Handling missing data and outliers
  • Exploratory data analysis (EDA) concepts
  • Feature selection and dimensionality reduction overview

Day 3: Data Mining Techniques & AI Models

  • Classification techniques (decision trees, rule-based models)
  • Clustering methods (k-means, hierarchical clustering)
  • Association rule mining and pattern discovery
  • Introduction to predictive modeling
  • Model evaluation and validation concepts

Day 4: Applied AI Analytics & Business Use Cases

  • AI-driven analytics for forecasting and prediction
  • Anomaly and fraud detection concepts
  • Text and sentiment analysis overview
  • Recommendation systems concepts
  • Interpreting and communicating analytical results

Day 5: AI Strategy, Ethics & Implementation

  • AI and data mining implementation roadmap
  • Model deployment concepts and lifecycle management
  • AI governance, ethics, and bias considerations
  • Data privacy, security, and regulatory compliance
  • Measuring business value and ROI from AI initiatives

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.