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.
Language
English
4.6 (By 5 Learners)
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About this Course
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)
Learn your way, at your pace.
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Introduction to AI & Machine Learning Foundations - Self Study
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Course Inclusions
- Definition of AI & ML
- AI in daily life (Saudi & Gulf examples: smart government apps, fintech, e-commerce)
- Difference between AI, ML, and Data Science
- Why AI matters for business & individuals
- Narrow AI applications (chatbots, fraud detection, logistics in Saudi ports)
- General AI concept (future vision)
- Comparisons & implications
- Supervised learning explained with Gulf banking fraud detection
- Unsupervised learning with customer segmentation in retail
- Reinforcement learning with Saudi autonomous vehicles/drones
- Scenario-based learning exercises
- Government services (Absher, Smart Dubai)
- Healthcare (AI in radiology in KSA hospitals)
- Retail & e-commerce (Noon, Amazon, sa personalized recommendations)
- Energy sector (Saudi Aramco predictive maintenance)
- Banking & fintech (STC Pay fraud detection, Qatar digital banking)
- Mini case study: Vision 2030 initiatives and AI adoption
- What is data? Structured vs unstructured
- Data collection in Gulf smart cities (IoT sensors in NEOM)
- Importance of data quality
- Small practical exercise: spotting data issues
- Linear Algebra in Recommendation Systems
- Probability in fraud detection & risk scoring
- Calculus in model optimization (simple visual examples)
- Visual, simplified explanations (no heavy formulas)
- Mini practical: try predicting outcomes with probability examples from Gulf retail sales
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