AI and Machine Learning Fundamentals

Study sheet excerpt

Course Outline

  1. Artificial Intelligence Foundations
  2. Machine Learning Principles
  3. Core Machine Learning Types
  4. Supervised and Unsupervised Learning
  5. Reinforcement and Deep Learning
  6. Predictive and Generative AI
  7. AI Applications in Networks
  8. Cisco Catalyst Center AI Features

1. Artificial Intelligence Foundations

Key Concepts & Definitions

  • Artificial intelligence : uses computers to simulate intelligence, enabling behaviors typically associated with humans, including recognizing patterns, learning, making decisions, and solving problems

★ Must-know

📌 AI has grown in importance because of increased computing power, the availability of big data, and breakthroughs in AI research.

Further detail

  • Examples of AI applications include: virtual assistants such as Siri, Alexa, and Google Assistant, recommendation systems such as Netflix, YouTube, and Amazon product recommendations, self-driving cars and robotics such as Tesla FSD and Waymo, chatbots such as ChatGPT and virtual concierges, game analysis systems such as Stockfish and AlphaGo

Memory Hook

AI: recognize, learn, decide, solve

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Quiz preview

1. Which network task is a direct application of predictive AI?

2. A system receives customer records without category labels and discovers groups of customers with similar behavior. Which learning type is being used?

3. What distinguishes deep learning from machine learning more generally?

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Flashcards preview

What does artificial intelligence (AI) use to simulate intelligence?

Computers.

Which human behaviors does AI simulate?

Recognizing patterns, learning, making decisions, and solving problems.

Name one example of AI in virtual assistants.

Siri.

What is an example of AI in self-driving cars?

Tesla FSD.

Why has AI grown in importance?

Because of increased computing power, big data availability, and AI research breakthroughs.

What is machine learning (ML)?

A subset of AI that enables computers to learn from data and improve without explicit programming.

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The study sheet covers the essential concepts of AI and Machine Learning Fundamentals. It is organized by topic to facilitate learning and memorization, with key definitions, explanations and summaries.

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The quiz contains 21 multiple-choice questions with detailed corrections and explanations for each answer. Ideal for testing your knowledge and identifying gaps.

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