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Introduction to AI & Machine Learning Foundations

A foundation in Artificial Intelligence and Machine Learning, covering key types of AI, core learning methods, real-world applications, and the essential data and mathematics behind intelligent systems.

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    What to Expect From This Introduction to AI & Machine Learning Course?

    By the end, you will be able to:

    • Understand the core concepts of Artificial Intelligence and Machine Learning.
    • Differentiate between key types of AI, including Narrow and General AI.
    • Apply knowledge of supervised, unsupervised, and reinforcement learning.
    • Identify and analyze real-world use cases of AI in business and daily life.
    • Recognize the importance of data in building intelligent systems.
    • Strengthen foundational mathematics skills essential for AI (linear algebra, calculus, probability).

    Who Should Enroll in this Introduction to AI & Machine Learning Course?

    • University students and fresh graduates seeking a strong foundation in AI and Machine Learning.
    • Professionals in IT, engineering, or data fields aiming to expand their technical skillset.
    • Business professionals interested in understanding AI applications in real-world and business contexts.
    • Researchers and academics are beginning their journey into AI and data science.
    • Anyone aspiring to enter the AI field or strengthen their career prospects with future-ready skills.

    What are the acquired skills from this Introduction to AI & Machine Learning Fundation Course?

    • Fundamental understanding of Artificial Intelligence and Machine Learning concepts
    • Differentiating between key AI types (Narrow vs General AI)
    • Applying supervised, unsupervised, and reinforcement learning methods
    • Identifying and analyzing AI use cases in business and real life
    • Data literacy and understanding the role of data in AI systems
    • Strengthening mathematical foundations (linear algebra, calculus, probability)

    Introduction to AI & Machine Learning Fundations Course  Self-Study

    • Reading Learning Materials. 
    • Pre and Post Course Questions.  
    • Modules Exercises. 
    • The language will be English. 
    • Module 1: What is AI? What is Machine Learning? 
    • Module 2: Key Types of AI (Narrow vs General AI) 
    • Module 3: Supervised, Unsupervised & Reinforcement Learning. 
    • Module 4: AI Use Cases in Real Life & Business. 
    • Module 5: Basics of Data for AI. 
    • Module 6: Mathematics Essentials for AI (Linear Algebra, Calculus, Probability Basics). 

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