AI and Machine Learning Fundamentals

From the study guide

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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Practice 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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Flashcard 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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Frequently asked questions

What does the AI and Machine Learning Fundamentals study guide cover?

It covers the core concepts of AI and Machine Learning Fundamentals, organized by topic with the key definitions, explanations and takeaways, so it's easier to learn and remember.

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How many questions are in the AI and Machine Learning Fundamentals quiz?

The practice quiz has 21 multiple-choice questions, each with an explanation. Use it to check what you know and find your gaps.

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How do I study AI and Machine Learning Fundamentals with flashcards?

There are 48 flashcards on AI and Machine Learning Fundamentals, with a question on the front and the answer on the back. Try to recall each answer before you flip, and let spaced repetition bring back the ones you miss.

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