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PODCAST

Certified - Advanced AI Audio Course

The Advanced Artificial Intelligence Audio Course is a focused, audio-first series that takes you deep into the technical foundations and emerging challenges of modern AI systems. Designed for professionals, students, and certification candidates, this course explains advanced AI concepts through clear, structured narration—no slides, no filler, just direct, practical learning. Each episode unpacks core topics such as neural architectures, model embeddings, optimization, interpretability, and

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All Episodes

26:56

Episode 11 — ML 102: Unsupervised Learning and...

Certified - Advanced AI Audio Course ·

2025/09/14

This episode introduces unsupervised learning, a key machine learning paradigm that does not rely on labeled data. Instead of mapping known inputs to known outputs, unsupervised methods search for patterns, groupings, or structures hidden in raw datasets. Clustering is a central technique within this category, where data points are grouped based on similarity metrics such as distance or density. Other approaches include dimensionality reduction, which simplifies high-dimensional data while

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29:30

Episode 10 — ML 101: Supervised Learning in Plain...

Certified - Advanced AI Audio Course ·

2025/09/14

This episode explains supervised learning, one of the most fundamental approaches in machine learning and a cornerstone for certification exams. Supervised learning relies on labeled datasets where each input is paired with a correct output. The model learns to map inputs to outputs through examples, producing predictions for new, unseen cases. Key concepts include training, testing, generalization, and error measurement. Supervised learning underpins many widely used applications such as

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31:43

Episode 9 — Data Bias Preview: Sources, Signals,...

Certified - Advanced AI Audio Course ·

2025/09/14

This episode introduces the concept of data bias, a topic that often appears in certification exams because of its impact on fairness, accuracy, and compliance. Bias arises when datasets reflect distortions, either because of sampling limitations, historical inequities, or measurement errors. Signals can include uneven representation across demographics, systematic omissions, or proxies that inadvertently encode sensitive information. Understanding how bias enters at the data stage is

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29:00

Episode 8 — Data for AI: Collection, Labeling, and...

Certified - Advanced AI Audio Course ·

2025/09/14

This episode explores the critical role of data in artificial intelligence, focusing on collection, labeling, and quality considerations. Data is the foundation of any machine learning system, and exam objectives frequently test understanding of how datasets are assembled and validated. Collection involves gathering information from sources such as sensors, logs, or user interactions, while labeling assigns the correct categories or outcomes to examples. Data quality covers issues like

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25:14

Episode 7 — Problem Framing: Turning Goals into AI...

Certified - Advanced AI Audio Course ·

2025/09/14

This episode introduces problem framing, the skill of converting a business or operational goal into a question that an AI system can realistically address. For certification purposes, this is vital because many questions hinge on identifying whether AI is the right tool, and if so, how to structure the problem. Framing involves specifying objectives, defining measurable outcomes, and understanding constraints. For example, a broad statement like “reduce churn” must be translated into a

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29:59

Episode 6 — Types of AI: Narrow vs. General, Symbolic...

Certified - Advanced AI Audio Course ·

2025/09/14

This episode examines the main types of artificial intelligence, clarifying distinctions that are essential for both exams and real-world comprehension. Narrow AI, also called weak AI, is built to perform specific tasks such as image recognition or speech transcription, while general AI is a theoretical concept aiming to replicate the full range of human cognition. On the other axis, symbolic AI relies on explicitly programmed rules and logic, whereas statistical AI, the foundation of

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28:45

Episode 5 — Glossary Deep Dive I: Core Terms You’ll...

Certified - Advanced AI Audio Course ·

2025/09/14

This episode serves as a glossary immersion, focusing on the terminology that certification candidates will encounter repeatedly in AI-related exams. Terms like algorithm, dataset, training, inference, supervised, unsupervised, and reinforcement learning are introduced with precise yet accessible definitions. By grouping these words and showing how they relate to one another, the learner develops fluency in the vocabulary that forms the basis of exam questions. A clear understanding of

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28:05

Episode 4 — How AI Systems Work: Data, Models,...

Certified - Advanced AI Audio Course ·

2025/09/14

This episode introduces the structural mechanics of AI systems, breaking them into three interrelated components: data, models, and feedback loops. Data is the raw material, collected and processed into training sets that shape model behavior. Models are the algorithms that learn from this data, ranging from decision trees to deep neural networks. Feedback loops ensure continuous improvement, where model outputs are evaluated, corrected, and fed back to refine performance. For certification

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27:23

Episode 3 — A Short History of AI: Booms, Winters,...

Certified - Advanced AI Audio Course ·

2025/09/14

This episode provides context for the development of artificial intelligence by tracing its history across cycles of optimism, disappointment, and eventual breakthroughs. We begin with early pioneers like Alan Turing, who framed the question of machine intelligence, and the Dartmouth Conference of the 1950s, which formally launched AI as a research field. Learners are introduced to the alternating periods known as “AI booms,” when funding and interest surged, and “AI winters,” when

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28:55

Episode 2 — What Is AI? Definitions, Scope, Everyday...

Certified - Advanced AI Audio Course ·

2025/09/14

This episode introduces the learner to the essential definitions and scope of artificial intelligence, a foundational step in any exam or certification path. AI can mean different things depending on context, ranging from symbolic rule-based reasoning to modern machine learning systems. We cover the distinctions between artificial intelligence as a broad field, machine learning as a subset, and deep learning as a further specialization. The scope also includes understanding the spectrum

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23:23

Episode 1 — Orientation: How to Learn AI by Listening

Certified - Advanced AI Audio Course ·

2025/09/14

This opening episode sets the foundation for the entire PrepCast by guiding learners on how to approach the subject of artificial intelligence in an audio-first format. Many certification seekers are used to textbooks or slide decks, but learning through listening requires slightly different habits. In this session, we emphasize how to engage with the material actively, focusing on repetition, recall, and conceptual linkage between topics. We outline the series flow, beginning with the

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51 results

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