In 1996 and 1997, chess player Garry Kasparov competed in a series of six intense chess games. However, his opponent wasn’t human. An IBM supercomputer called Deep Blue put Kasparov through the wringer, becoming the first piece of artificial intelligence to play chess against a human opponent. Both Kasparov and Deep Blue walked away with victories.
The series of chess matches was the first moment when many saw the potential of AI to take over the world. When speaking of the future, many people imagine flying cars or robot housemaids. But these ideas are coming straight from pop culture and science fiction.
We might not have flying cars soon, but self-driving cars are already being tested. How is this possible? Through artificial intelligence and rapid technological advancement. Right now, Tesla is attempting to roll out its self-driving cars using neural networks and automation algorithms.
It’s not a stretch to say that AI is a fascinating development. So, naturally, many people are interested in learning what goes into programming machines. Let’s look at all the foundations of becoming an AI master.
What Is Artificial Intelligence?
The term artificial intelligence refers to the intelligence of machines and software. It stems from the use of the phrase “natural intelligence” to describe the way that humans and animals think.
AI first popped up as an educational discipline in the mid-1950s, where it was met with criticism and an overall lack of support. The main schools teaching AI were Stanford University, Carnegie Mellon, and MIT. The term “artificial intelligence” was the brainchild of computer scientist John McCarthy.
However, AI has never been more popular than it is now. Computer scientists and philosophers alike often theorize upon the benefits and dangers of advanced AI.
Tesla’s aforementioned self-driving cars may soon be a reality, and other creative advances in tech have opened the floodgates to further expansion in the field.
What Is Artificial Intelligence Used For?
AI systems hold much more potential for our daily lives than just helping robots to mimic human expressions and behaviors. It is one of the most important parts of the future of technology in our society.
- Having machines and software perform specific tasks. This is general, but it covers nearly all the main facets of AI. If you’ve ever used Siri or Alexa, you’ve directly interacted with a robust artificial intelligence program.
- Navigation. Besides Tesla’s self-driving cars, many other GPS and navigation resources derive their power from AI. For example, when you take a wrong turn and Google Maps automatically plans an alternate route, this is a form of reactive AI.
- Assist in sales. This is also a general function of AI but is extremely powerful and widespread. AI is now used to assist in customer service, product automation, customer engagement, and predicting a customer’s buying habits.
- Security and Cybersecurity. With advanced AI comes opportunities for advanced security measures. AI can mitigate crime through facial recognition software and things like firewalls. There are many jobs related to AI in the field of cybersecurity.
Types of Artificial Intelligence
Unsurprisingly, there are many subsectors of AI. Below are a few of the main types.
Weak AI
Often described alongside narrow AI, weak AI is the general field of artificial intelligence concerning the performance of simple tasks. Weak AI systems cannot act of their own free will and cannot transcend their prewritten, preprogrammed duties.
Playing chess against an AI opponent on the computer is one example. The computer reacts to your moves and calculates its own. The program can calculate its actions and respond to the player, but it exists only to play chess.
Narrow AI
As you can probably surmise, narrow AI is narrow in scope. Essentially, narrow AI exists to perform a singular, straightforward task. Good examples of narrow AI are Siri and Cortana.
While they possess the power to access information, their tasks are simple. They have no cognitive functions, and they operate under a strict set of predefined rules.
Artificial General Intelligence, or ‘Strong AI’
If you’re looking for a modern comparison to your favorite use of AI in sci-fi, strong AI is probably the closest you’ll come.
The phrase strong AI refers to what is currently a more hypothetical form of artificial intelligence. This is where a machine can learn and perform the same cognitive and physical tasks as humans.
While not thoroughly researched or implemented anywhere currently, many AI experts predict that strong AI may become a part of our daily lives within decades. Many major companies are actively exploring how to program strong AI.
A Quick Note on the Turing Test
A famous example of strong AI is the Turing test. The Turing test, named after Alan Turing, is a way of determining if a computer is capable of human thoughts. A person speaks to two respondents, one a human and the other a machine.
After conversing with the two respondents, the questioner tries to determine which is the computer. The Turing test has raised philosophical and ethical issues in the field of AI.
Learning Artificial Intelligence
Maybe you’re thinking that AI is just for the computer experts at Tesla and Apple. However, this couldn’t be further from the truth. There are many paths you can take to learn AI, and the unfettered access to some of these resources is unprecedented.
How Long Does It Take to Learn Artificial Intelligence?
While it does not take a definitive number of months or years to learn AI, you will be able to gauge your progress once you begin studying. Experts say it can take anywhere from one year to five years to learn artificial intelligence.
You can become more familiar with the basics through online courses, by getting a degree in data science, or by attending in-person training.
Let’s explore the most straightforward way to learn artificial intelligence step-by-step.
How to Learn Artificial Intelligence: Step-by-Step
There is no certain pathway to a career in AI. Some people will go into it with no prior computer science knowledge, while others will have a knack for all things tech. Let’s look at one way you can achieve a working knowledge of artificial intelligence.
- Take AI classes. Tech classes, especially dealing with AI, are in abundance. There are both free and paid versions of courses you can take online at any time. Below, we’ll show you the best classes to check out.
- Do your research. You won’t get anywhere in AI without some serious technical reading. Luckily, there are a ton of different materials that will help you better understand AI. Books, articles, peer-reviewed research pieces, and video lectures will all give you valuable information as you strive to become an AI expert.
- Pursue a computer science degree. If you’re passionate about all things tech, it may be appropriate to pursue higher education. Computer science degree programs will offer insight and improve your career prospects. Immersing yourself in multiple curriculums based around AI courses and learning from industry experts will give you an excellent foundation for your future endeavors.
The Best Artificial Intelligence Courses and Training
So what AI courses can you take to enhance your technical knowledge? While there may be a lack of in-person artificial intelligence courses due to the ongoing COVID-19 pandemic, this doesn’t mean that learning has to stop.
Online Artificial Intelligence Courses
What better place to learn about computer science concepts and computer systems than in front of your computer? There are some fantastic AI courses that you should take advantage of. Let’s review some that can help you break into the industry.
Stanford University Machine Learning
- Provider: Coursera
- Time: 60 hours
- Prerequisites: None
This course is offered by one of the original artificial intelligence research hubs, Stanford, via massive open online course website Coursera. If you’re looking to dedicate your life to becoming a machine learning engineer, this AI course is perfect for you.
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Taught by Landing AI CEO and founder Andrew Ng, this class will equip both rookies and experts alike with essential machine learning skills. Participants will experience how it is possible for machines to act without explicit programming and learn many fundamentals of computer science.
Participants in this AI course will delve into machine learning algorithms, logistic regression, and artificial neural networks.
Artificial Intelligence: Implications for Business Strategy
- Provider: MIT Sloan
- Time: Six weeks
- Prerequisites: None
This AI course is the perfect marriage of business and tech.
This certificate program from tech giant MIT teaches the basics of artificial intelligence and how it can be implemented in business. This course is aimed at business leaders who want to learn advanced tech tools, but non-business owners can also attend to glean valuable AI knowledge.
This course is taught via MIT’s Sloan School of Management and its Computer Science and Artificial Intelligence Laboratory. This unique combination means participants will be on the cutting edge of the ever-evolving field of tech-based business strategies.
Over six modules, participants will learn the basics of the future of AI. They will then earn an impressive MIT Sloan certificate upon finishing the course.
This MIT course is very flexible because it is fully online, so you can learn the modules at your own pace throughout the week.
UC Berkeley: Artificial Intelligence Strategy Online Short Course
- Provider: UC Berkeley School of Information
- Time: Six weeks
- Prerequisites: None
This is a more advanced form of the MIT course and is also aimed at business professionals who want to expand the use of technology in their business model.
UC Berkely recommends that those who sign up for the short course already be well-versed in business tactics and practices. It is not a technical course and does not require advanced knowledge of programming languages or algorithms. Instead, it strikes a balance between data science and business.
The director of the UC Berkeley School of Information, Alberto Todeschini, will imbue students with skills such as risk management, AI strategies, and how to plan for the use of tech in your business.
Free AI Courses
What if you don’t want to drop a lot of money on an artificial intelligence course? If you’re struggling to justify the cost of the AI courses above, don’t let it discourage you from learning AI.
There are some great free AI courses and seminars that are available to anyone. Let’s see the most notable examples.
Intro to Artificial Intelligence
- Provider: Udacity
- Time: Four months
- Prerequisites: None
If you’re hesitant about jumping into a paid course or degree program, this free intro to AI course is an ideal opportunity. Based on self-paced learning and an excellent student community, this Udacity course is worth taking.
It will explain modern AI and its many possible applications in the near future.
This is an intermediate AI course, but anyone can join if they wish.
AI for Everyone: Master the Basics
- Provider: IBM
- Time: Four weeks
- Prerequisites: None
Crafted by the experts who created the famous supercomputer Deep Blue, this intro to AI covers all the basics. The instructors at IBM will show you what AI is, how it affects our world and the possibilities that exist within complex programs. A significant aspect of this AI course is the career advice offered by IBM.
This program is for everyone. You don’t need any prior experience in computing, programming, or anything tech-related to join.
Students have the option of obtaining a certificate at the end of this free AI course for an optional fee of $50.
Artificial Intelligence Books
Since AI has been a part of our society for decades, it’s no surprise that there’s a lot of written material on it. However, let’s cut out some older material to see what new educational resources have been published by AI researchers. These cover everything from hands-on learning to AI theory.
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron
Géron provides the basis for most of the current advancements in artificial intelligence in this remarkable book. He outlines machine learning examples and how to create your own intelligent system.
This book goes easy on the theory and instead shows you the practice of AI, with each chapter including different theories and problems to solve. You’ll cover everything from the basics to the most meticulous details of neural networks.
Superintelligence: Paths, Dangers, Strategies by Nick Bostrom
What happens when the knowledge and capabilities of machines surpasses that of humans? Mixing biology, anthropology, and technology, Nick Bostrom uses history as a tool to measure the potential of machine intelligence.
While this book does not teach you how to program machines, it is an excellent introduction to what AI can do. It also shows the possible ways humans can interact with machines in the future, and what technological advancements will mean for us as a species.
Deep Learning (Adaptive Computation and Machine Learning series) by Ian Goodfellow
Endorsed by Elon Musk, this text is an extremely comprehensive resource for deep learning and AI. This book goes into extreme detail, including all the math you need to integrate deep learning and machine learning.
This book caters mostly to undergraduate and graduate degree level students, but anyone can take advantage of the authors’ information and insight.
Online Artificial Intelligence Resources
If you aren’t too keen on taking an AI class, there is no shortage of other valuable online resources.
There are blog posts, online forums, and other applications to help you parse out the intricacies of AI.
Using AI with Google
The AI researchers at Google have set up a great set of personalized guides for AI. You can delve into the details of machine learning algorithms, clustering, and AI practices.
This free set of guides and AI crash courses is a great resource. It allows students, data scientists, software engineers, and business professionals to harness the basics of computer systems.
MIT Deep Learning and Artificial Intelligence Lectures
This is a set of fantastic and detailed lectures from the talented Lex Fridman, a research scientist at MIT. Fridman offers insight into the basics and future of AI.
Specifically, Fridman reviews deep learning and its relation to our current tech landscape. Each lecture is chock-full of relevant information that is easy to retain. He starts from the very beginning of the history of AI and analyzes how it has impacted society.
If you finish these in-depth lectures, Fridman also has a companion series of lectures dealing primarily with self-driving cars.
Should You Study Artificial Intelligence?
If you want a glimpse of what the future of tech holds, then yes, you should. While it may not be for everyone, learning AI can have many benefits for those who are technologically-inclined.
Likewise, it’s also a sound career choice for those who have a vested interest in advancing a business, or anyone curious about how machine learning will affect our world. While we may not seem like sci-fi yet, we may very well get there sooner than you think.
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