What is Artificial Intelligence?

Artificial intelligence is the simulation of intelligent, human-like processes by machines. The applications for it are nearly limitless and the industry is growing fast. Really fast! The AI market is forecast to grow from $419.7 million in 2014, to $5 billion by just 2020! Demand for AI specialists has never been greater, and top companies are competing for AI talent.

Industries Using AI Today

Finance

The use of AI in the financial services sector has many consumer benefits, from improving customer service to enhancing security. AI algorithms increase the speed and accuracy of credit applications, monitor your accounts for signs of fraud, and help manage your investments in the stock market.

Consumer Goods

AI is already in use in the gadgets you touch everyday. Think, for example, of the face detection on your smartphone, the smart speakers that answer your weather questions, and the home security cameras that send a text when your kids get home from school.

Transportation

Transportation has seen great leaps forward in the use of AI. There are autonomous vehicles that don’t require a human driver; smart traffic systems that can reduce congestion; and fleet optimization technology to improve the reliability of deliveries.

Healthcare

From algorithms that can examine different treatment alternatives and recommend the most effective cancer drugs, to helping identify medical issues in x-rays and CT scans—AI in healthcare has incredible applications.

Legal

AI is used to review lengthy legal contracts, draft legal documents, and provide a first screening of personal injury claims. AI bots have even been use to predict legal outcomes at the US Supreme Court, outperforming legal experts!

Agriculture

Major uses of AI in agriculture include applying computer vision and machine learning to monitor crop conditions, and using predictive analytics to forecast the impact of weather changes on crop yield.

Finance

The use of AI in the financial services sector has many consumer benefits, from improving customer service to enhancing security. AI algorithms increase the speed and accuracy of credit applications, monitor your accounts for signs of fraud, and help manage your investments in the stock market.

Consumer Goods

AI is already in use in the gadgets you touch everyday. Think, for example, of the face detection on your smartphone, the smart speakers that answer your weather questions, and the home security cameras that send a text when your kids get home from school.

Transportation

Transportation has seen great leaps forward in the use of AI. There are autonomous vehicles that don’t require a human driver; smart traffic systems that can reduce congestion; and fleet optimization technology to improve the reliability of deliveries.

Healthcare

AI has incredible healthcare applications—from algorithms that can examine different treatment alternatives and recommend the most effective cancer drugs, to helping identify medical issues in x-rays and CT scans..

Legal

AI is being used to help review lengthy legal contracts, draft legal documents, and provide a first screening of personal injury claims. AI bots have even been use to predict legal outcomes at the US Supreme Court, outperforming legal experts!

Agriculture

Major uses of AI in agriculture include applying computer vision and machine learning to monitor crop conditions, and using predictive analytics to forecast the impact of weather changes on crop yield.

Computer Vision

Computer vision involves helping computers identify and process images in the same way humans do. You’ll see computer vision principles at work when a photo app organizes your snapshots by recognizing the different people in your photos. And computer vision is also used to help diagnose medical conditions, and enables a space rover to navigate the rocky surface of a planet it’s never seen.

Computer Vision Experts Need to Know

Computer Science & Programming

  • Python
  • OpenCV
  • C++
  • GPU/Parallel Computing

Math

  • Statistics and Probability
  • Calculus
  • Linear Algebra

Algorithms & Deep Learning Architectures

  • Image transformations and filtering
  • Feature detection
  • Simultaneous localization and mapping (SLAM)
  • Convolutional Neural Networks (CNNs)
  • Region-based CNN’s
  • Single-shot detection
  • Recurrent Neural Networks (RNNs)

AI Frameworks and Libraries

  • PyTorch
  • TensorFlow
  • Keras

Computer Vision in Action

Social Media Face Filters

Lane Detection

Crop Monitoring

Jobs in Computer Vision

Sample job titles: Computer Vision Scientist, Computer Vision Engineer, Perception Software Engineer

Low

$80,000

Average

$132,000

High

$200,000

$50,000

$150,000

$300,000

Average yearly salary range

From the AI Experts

Dr. Rana el Kaliouby founded Affectiva to bring emotional intelligence to the world of technology. In her own words: “We use computer vision and machine learning to recognize emotions as they manifest on your face. By observing how your eyebrow, your mouth, and your cheeks move. Once an app recognizes emotions, it can respond to them in real time. This creates a lot of opportunity for personalizing how we and machines interact together.”

Machine Learning

In machine learning, the goal is to develop algorithms that learn on their own from large datasets to make predictions and recommendations on the future use of that data. Deep learning is a really exciting form of machine learning that uses networks modeled on the structure of the human brain. It is a fast-growing field, with a wide-array of cutting-edge applications, including the creation of hyperrealistic special effects in film and gaming, the study of distant galaxies in space, and cancer detection.

Machine Learning Experts Need to Know

Computer Science & Programming

  • Python
  • C++
  • Java
  • R
  • GPU and Parallel Computing

Math

  • Statistics
  • Calculus
  • Linear Algebra
  • Numerical Analysis

Machine Learning Libraries

  • Naive Bayes Classifiers
  • Supervised and unsupervised learning
  • Linear regression
  • Reinforcement learning
  • Decision Trees
  • Clustering

Data Engineer Fundamentals

  • Data Modeling & Evaluation
  • SQL
  • Hadoop
  • Spark

Machine Learning in Action

Directions and Navigation

Credit Card Fraud Detection

Streaming Service Recommendations

Jobs in Machine Learning

Sample job titles: Machine Learning Engineer, Business Intelligence Engineer, Data Scientist

Low

$80,000

Average

$136,000

High

$250,000

$50,000

$150,000

$300,000

Average yearly salary range

From the AI Experts

"I'm excited to see that more and more businesses are starting to adopt machine learning in their non-ML applications. Thanks to easy APIs and good tutorials smaller businesses can† now make their apps and websites smarter with some basic algorithms."

- Dominic Monn, Deep Learning Engineer

Robotics and Autonomous Systems

From self-driving cars to auto-navigating drones, AI extends into many parts of robotics and transportation. The ultimate aim is to use location and sensor data to create vehicles capable of operating without human input.

Robotics Experts Need to Know

Computer Science & Programming

  • Python
  • C++
  • Object Oriented Programming
  • Programming for Embedded Systems
  • Coding Optimization
  • Linux/UNIX Development Environment

Math

  • Statistics and Probability
  • Calculus
  • Linear Algebra

Algorithms & Deep Learning Architectures

  • Object Detection and Classification
  • Control Systems
  • Filters

AI Frameworks and Libraries

  • PyTorch
  • TensorFlow
  • Robot Operating System (ROS)

Robotics and Autonomous Systems in Action

Self-Driving Cars

Agriculture Robots

Surgical Robots

Jobs in Robotics and Autonomous Systems

Sample job titles: Robotics Navigation Engineer, Autonomous Sensing Engineer, Embedded Software Engineer

Low

$75,000

Average

$92,000

High

$180,000

$50,000

$150,000

$300,000

Average yearly salary range

From the AI Experts

"I believe that we are just scratching the surface in the advances on self-driving cars. The field of reinforcement learning (an advanced AI technique) have proven how powerful it can be.”

- Willian ver Valem Paiva, AI Engineer

Natural Language Processing

Natural Language Processing (NLP) is how computers are trained to understand, process, and manipulate spoken words and text. This has many applications, from translating different languages, to controlling devices using just your voice. Famous examples of NLP voice control include Apple’s Siri, Amazon’s Alexa, and Microsoft’s Cortana.

NLP Experts Need to Know

Computer Science & Programming

  • Python
  • C++
  • C
  • Java

Math

  • Statistics and Probability
  • Calculus
  • Linear Algebra
  • Data Modeling

Machine Learning Libraries

  • Embeddings and Word2Vec
  • Naive Bayes
  • Hidden Markov Models
  • Latent Dirichlet Allocation
  • Recurrent Neural Networks
  • Long Short-Term Memory Networks
  • Sequence-to-Sequence Models
  • Deep Learning Attention

AI Frameworks and Libraries

  • PyTorch
  • TensorFlow
  • Keras
  • MxNet

Natural Language Processing in Action

Translation Apps

Legal Document Processing

Smart Assistants

Jobs in Natural Language Processing

Sample job titles: Natural Language Computer Scientist, Language Engineer, Applied Scientist, Natural Language Processing

Low

$85,000

Average

$135,000

High

$200,000

$50,000

$150,000

$300,000

Average yearly salary range

From the AI Experts

Quill is an education non-profit that uses natural language processing to help students improve grammar and writing, and simplify grading for teachers. Now they’re looking for more AI specialists to keep students learning!

© 2011–2018 Udacity, Inc.

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