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Artificial Intelligence

Understand the core concepts of Artificial Intelligence and its real-world applications. Learn AI models, tools, and techniques to build intelligent solutions across industries

Course Outline

Prerequisites for AI

  • Basic knowledge of Mathematics, Computer Science, and Programming.
  • Since it’s a beginner-level course, therefore programming skill is not mandatory.

Chapter 1 : Introduction to Artificial Intelligence

  • What is AI? History, scope, and applications

  • Types of AI: Narrow, General, and Superintelligence

  • Real-world use cases of AI in industries

Chapter 2 : Fundamentals of Intelligence

  • Understanding natural vs artificial intelligence

  • Types of intelligence (emotional, logical, cognitive)

  • Role of data in intelligence

Chapter 3 : Intelligent Agents

  • Agents and environments

  • Types of agents (reflex, model-based, goal-based, learning agents)

  • Structure of an intelligent agent

Chapter 4 : Problem Solving & Search Techniques

  • Problem-solving approaches in AI

  • Uninformed (blind) search strategies

  • Heuristic search strategies

  • Applications of heuristic methods

Chapter 5 : Knowledge Representation & Reasoning

  • Representation techniques: logic, rules, and semantic networks

  • Propositional & predicate logic basics

  • Rules of inference and reasoning

  • Tools for logical problem solving

Chapter 6 : Machine Learning Foundations

  • Overview of learning in AI

  • Supervised Learning: classification and regression basics

  • Unsupervised Learning: clustering and dimensionality reduction

  • Reinforcement Learning: agents, environments, and reward systems

Chapter 7 : Introduction to Artificial Intelligence

  • What is AI? History, scope, and applications

  • Types of AI: Narrow, General, and Superintelligence

  • Real-world use cases of AI in industries

Chapter 8 : Course Wrap-up & Evaluation

  • Recap of AI concepts

  • Real-world problem-solving using AI approaches

  • Preparation for advanced AI & ML learning paths

Note :

  • This is a theory-focused course with problem-based learning.

  • Course material (slides, assignments, and references) will be provided via Google Classroom (GCR).

  • No hands-on coding is required at this level.

Yousuf Kamal

AI Instructor

Our AI instructor is a skilled professional with expertise in artificial intelligence, machine learning models, and real-world applications. With a passion for teaching, they simplify complex AI concepts into practical, easy-to-learn lessons.

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