Introduction to Artificial Intelligence

Introduction to Artificial Intelligence

In this lesson, you will gain a clear understanding of what artificial intelligence is and its three forms—artificial narrow intelligence, artificial general intelligence, and artificial superintelligence. You'll also see how AI is already part of our everyday lives, sometimes in ways, you may not even realize, and differentiate real-world and science-fiction AI.

Artificial Intelligence in Business Today

Now you will take a closer look at how we interact with AI as consumers in both pre-and post-purchase applications such as chatbots, recommendation engines, virtual reality, and shopping assistants. You'll see how other AI applications can gather business-related data and use it to inform decisions within an organization, yielding business forecasting, and analytics. Finally, we'll consider industries that may be transformed or even disrupted by AI implementations, such as healthcare and the financial and transportation sectors.

Machine Learning

This lesson delves into machine learning—how computers can "learn" by mapping input to output using complex mathematical and statistical models. Suitable algorithms plus useful training data can enable computers to improve their production over time, effectively learning as humans do. With just a little math, you'll find out about supervised learning, including regression and classification, unsupervised learning, and reinforcement learning as they apply to computers. You will understand the importance of useful data in getting good results and how programmers avoid algorithmic bias.

Neural Networks and Deep Learning

In this deeper dive into how AI works, you'll learn about artificial neural networks—basically computational models that loosely replicate the biological brain structure. You'll see how an artificial neuron mimics a biological one and understands the specific training processes with a little more math. Then, you'll examine deep learning, a specialized subset of machine learning, including convolutional neural networks, recurrent neural networks, and long short-term memory.

Computer Vision

Computer vision is a subset of artificial intelligence focusing on how computers can extract useful information from digital images or videos—easy for us, hard for them. You'll learn about how computers store and interpret images, along with some of the most advanced AI applications involving facial and object detection and recognition, autonomous vehicles, and triage and early diagnosis in healthcare.

Natural Language Processing

You've probably seen natural language processing in action on your phone or digital home assistants such as Alexa, Google, or Siri. In this lesson, you'll consider the intricate steps the computer must execute to understand and then carry out your commands, converting words into machine-usable numbers using natural language processing techniques and back into words using natural language generation. You'll get a look at exactly how processes such as one-hot encoding, bag-of-words, term frequency, inverse document frequency, and word embedding work, as well as some applications of NLP in businesses today, including sentiment analysis and AI-powered surveys.

Time Series Forecasting

One beneficial application of AI is in forecasting. In this lesson, you will learn about time series analysis, which attempts to find the patterns in data. The pattern components are the trend, seasonality, cyclic patterns, and randomness (noise). Time series forecasting can involve univariate analysis (a single variable changing over time) or multivariate analysis. Many industries use time-series data analysis and forecastings, such as healthcare, sales, and weather prediction.

Robotics

Robots are a well-known AI application. Unlike humanoid robots from science fiction movies, many real-life robots around us today in factories, warehouses, agriculture, and even in homes don't look much like people at all. You will learn about the kinds of tasks robots excel at, repetitive tasks with limited variability in a well-controlled environment. You will also learn about the challenges robotic projects face, such as high variability in the environment and high failure costs. Finally, you will see how robots are used today in two industries: logistics and agriculture.

Implementing AI

In this lesson, you will look at the AI development process and a typical AI project workflow, along with the low-level languages commonly used for AI programming. You will also learn about machine learning framework software and software suites that can help with AI development. In addition, you will discover pre-made AI services that you can buy r