Certified Artificial Intelligence Practitioner (CAIP)

The Artificial Intelligence Practitioner Training Course is designed to equip professionals with the knowledge and hands-on skills needed to harness the power of AI for solving complex business challenges.

As organizations strive for greater efficiency and agility, Artificial Intelligence emerges as a transformative force enabling smarter decision-making, automation, and innovation across various industries.

This Artificial Intelligence Practitioner Course offers a comprehensive foundation in the core concepts of AI, including machine learning, neural networks, fuzzy logic, probabilistic reasoning, and genetic algorithms.

Participants will explore real-world applications of AI in sectors such as finance, healthcare, operations, and media, learning how to implement AI-driven solutions that enhance performance and reduce operational inefficiencies.

Through a practical and interactive approach, this training course prepares delegates to design, develop, and evaluate intelligent systems.

Whether you're an executive, data specialist, or aspiring AI professional, the course will empower you to become a certified AI practitioner capable of driving digital transformation and delivering measurable results.

Training Course Objectives

By attending this training course, delegates will be able to:

• Develop many AI skills necessary to get work completed in less time
• Understand how to plan using logic
• Explain how to imitate human neural network in classification
• Understand how to design a Machine Learning based applications
• Analysis and Design AI Application

Designed for

This training course is suitable to a wide range of professionals but will greatly benefit:

• Project Managers
• Office Managers
• Leaders
• All professionals who need to fill the gap between the current business situation and the very near AI era
• Anyone who is interested in enhancing the current business using wide steps

Day One: An Overview of Artificial Intelligence

• Introduction to AI and Success Stories
• Human Intelligence vs Artificial Intelligence
• History of AI
• Intelligent Agents and Their Roles
• Limits of Artificial Intelligence
• Intelligent Decision Making

Day Two: Intelligent Agents

• Introduction to Agents
• Different Types of Agents
• Knowledge-base and Data Base
• Logic Reasoning
• Unification
• Deduction Processes

Day Three: Machine Learning

• Supervised and Unsupervised Learning
• Classification and Clustering
• Artificial Neural Networks
• Learn by Examples
• Object Recognition
• Features and Classes

Day Four: Fuzzy Logic

• Introduction to Fuzzy Thinking
• Fuzziness vs Probability
• Fuzzy set and Fuzzy Rules
• Importance of Fuzzy logic
• Real example of Fuzzy Controllers
• Building a Tiny Machine Learning Application

Day Five: Genetic Algorithm

• Overview of Genetic Algorithms
• The Need for Optimization, Maximization, and Minimization
• How GA Work and Evolve
• Genetic Algorithm Chromosomes, Genes, Selection, Mutation and Crossover
• Dimension to Use Genetic Algorithm
• Real Genetic Algorithm Examples to Optimize Business Processes