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Complete Introduction to Artificial Intelligence course
Rating: 3.9 out of 5(27 ratings)
241 students

Complete Introduction to Artificial Intelligence course

Artificial intelligence Bootcamp, Definition, business, example, technique for kids, engineers, students...with benefits
Created byMERAH Nasreddine
Last updated 1/2021
English

What you'll learn

  • The meaning behind common Artificial Intelligence terminology, including neural networks, machine learning, deep learning, and data science
  • What Artificial Intelligence realistically can and cannot do
  • How to spot opportunities to apply AI to problems in your own organization
  • What it feels like to build machine learning and data science projects
  • How to work with an AI team and build an AI strategy in your company
  • How to navigate ethical and societal discussions surrounding AI
  • Workflow of Machine Learning projects
  • AI terminology
  • AI strategy
  • Workflow of Data Science projects

Course content

4 sections • 34 lectures • 4h 39m total length

  • Welcome0:14
  • Introduction8:52
  • Machine Learning8:29

    Explore supervised learning, mapping inputs to outputs with examples like spam filtering, speech recognition, translation, and self-driving cars, and how data and neural networks boost performance with deep learning.

  • What is data ?13:34
  • The terminology of AI12:21

    Explore AI terminology by contrasting machine learning and data science, illustrated with house price examples, neural networks, and deep learning, and show how input output mappings drive business insights.

  • What makes an AI company ?9:40
  • What machine learning can and cannot do (Part 1)10:09
  • What machine learning can and cannot do (Part 2)10:18
  • Non-technical explanation of deep learning (Part 1)7:44
  • Non-technical explanation of deep learning (Part 2)4:28

    Explore how neural networks turn pixel brightness values into numbers, detect edges and facial features from grayscale or color images, and predict the identity of people in pictures.

  • Section 1 Quiz

Requirements

  • Have a PC with browser connected to the internet

Description

AI is not only for engineers, and computer science engineers. If you want your organization to become better at using AI, this is a course to tell everyone, especially your non-technical colleagues to take , you will learn:

- The meaning behind common AI terminology, including neural networks, machine learning, deep learning, and data science

- What AI realistically can and cannot do

- How to spot opportunities to apply AI to problems in your own organization

- What it feels like to build machine learning and data science projects

- How to work with an AI team and build an AI strategy in your company

- How to navigate ethical and societal discussions surrounding AI

- Get a real Artificial intelligence Bootcamp and understand AI for begginers

- Understand what's Artificial intelligence future (a complete vision)

- Make a good overview in order to target an Artificial Intelligence careers ( many career paths)

- Understand Artificial Intelligence Business

- See Examples from worldwide Artificial intelligence companies ( Apple, Amazon...) and in many fields as in medicine, healthcare, .... etc

- See example of Artificial Intelligence in business with examples of can and cannot do to avoid past mistakes

Though this course is largely non-technical, engineers can also take this course to learn the business aspects of AI.

Who this course is for:

  • Anyone interested in Artificial Intelligence, Machine Learning or Deep Learning
  • Both students and professionals

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