Artificial intelligence (AI) is a sub-division of computer science. The main goal is to enable a smart device (e.g. computer, smartphone) to perform activities that are normally done by people. First mentioned back in the 50s in the paper “Computing Machinery and Intelligence”, written by mathematician Alan Turing, artificial intelligence is now a very popular field, and we have advanced technology to “blame” for that. This article is about learning Artificial Intelligence and we will give you a comprehensive guide that you can use as a starting point towards learning artificial intelligence.
Today’s AI-based computers can beat chess champions, so it’s safe to say that little by little the world is taking a turn. Whether it’s for the better or for the worse, that’s all a matter of personal opinion. Some people say that artificial intelligence will save humanity; others, claim it will destroy it. The truth is, we don’t really know what AI is capable of. Artificial intelligence is a fascinating area of computer science we all want to know more about. We’ve seen cars drive by themselves and computers understand our basic needs and wants. Robotics is yet another sub-field of computer science that depends entirely on AI. Advanced technology has gotten to a whole new level; a level that some people just can’t accept.
Artificial intelligence studies how people’s brain think, learn, work, and make decisions. At the core of AI, we have intelligent software. Tech-savvy individuals and computer science aficionados are spellbound by what it can do. If you’re one of them, the following guide will help you learn more about how to start learning artificial intelligence and understand its basic principles.
Why should you start learning artificial intelligence?
Artificial intelligence is a field that opens a wealth of opportunities. Aren’t you just a bit curious to understand the tools and systems that you connect with daily? But then again, not everyone can do it. Before you get into the nitty-gritty of Google’s attempt to craft quantum processors, you must start with the basics – programming.
In the meantime, here are some excellent resources to help you get started:
Codecademy.com – a totally free website with interactive courses on various programming languages. Join over 25 million learners from all over the world, and master the tricks of the trade
Udacity – featuring lots of innovative courses on programming, Udacity is a must-try. Some of the tutorials are free, which is great for newbie developers.
Clean Code, by Robert C. Martin – for bookworms we have Clean Code, a book with lots Java examples that are applicable in other programming languages too. Focused on good program organisation and style, Clean Code should become your step by step guide to marketing code and learning the ins and outs of programming.
Next, get friendly with BOTs. Web crawlers that search engines such as Google use are the best example of an advanced and sophisticated bot. The following guides might clear things out, so make sure to check them out.
Xpath – an excellent resource that helps you build bots and inspect HTML
Regex – an online tool that teaches learners all about bot data processing
Requests – HTTP made easier; an excellent non-GMO HTTP library for web developers fond of Python programming language
The Complete Beginner’s Guide to Chatbots – learn everything there is to know about chatbots, how they are and how to build one.
After you’ve decided on a programming language that matches your abilities and befriended a BOT, it’s time to learn about machine learning (link to the machine learning article). We’ve laid out some nice tutorials, books and guides to help you get started. Make sure that you know at least the basics of Advanced Math and Stats before jumping into machine learning. It will help you understand ML algorithms.
Programming Collective Intelligence, by Toby Segaran – written long before machine learning attained the level of popularity it has today, this book describes machine learning in a very soothing and easy to digest way. Some key topics: search engine features, collaborative filtering techniques, support vector machines, and Bayesian filtering. Python is used to describe machine learning (extremely creatively we might add).
[PDF] Machine Learning, by Tom Mitchell – an excellent introductory book that provides a detailed overview of ML theorems. There are several case studies presented, and basic examples to make readers understand the algorithms a lot easier.
Machine Learning: The New AI, by Ethem Alpaydi – a book about the way digital technology advanced from basic number-crunching mainframes to smart mobile devices, thus putting machine learning at the top of computer science. Readers will also learn about machine learning basics and how the technology applies to applications.
To summarise, here’s what you need to master before being able to learn and understand artificial intelligence:
- Advanced Math (e.g. correlation algorithms) and Stats
- Programming language
- Machine Learning
- PATIENCE – yes, on top of everything you need lots of patience
Steps to help you learning Artificial Intelligence
Learning and understanding artificial intelligence is something most software developers and programmers strive to achieve. They can understand the potential of the industry; what it can do, but also what it might be able to do 10 or 20 years from now. Lots of misconceptions surround AI. Will robots take over the job market? Will computers be able to outsmart humans? Will intelligent machines replace people or merge with them? Should we fear that the age of artificial intelligence will completely change the way people see computers? Now all these are great questions, and hopefully our grandchildren’s children can answer them. One thing’s for sure. With advanced technology comes great responsibility, and computer science fanatics know that. To learn more about AI, there are the steps you should be following.
Get a degree, attend a course or class on AI
Intro to Artificial Intelligence – subdivided into 10 lessons, this online course introduces learners to the world of AI. You’ll be introduced to concepts such as computer vision, machine learning, natural language processing, robotics, and game theory. To understand it, make sure you have some basic knowledge of linear algebra and probability theory.
Artificial Intelligence – use the edx.org course to learn the basics of AI. The focus is the decision-theoretic and statistical paradigm. Prior programming knowledge and experience is required (they use Python as a main programming language), as well as a background in Math. During the course, students will learn to build autonomous intelligent agents programmed to make random decisions; and you’ll learn about machine learning applications too. How cool is that?
MIT OpenCourseWare – Artificial Intelligence – MIT’s course on AI teaches attendees everything they need to know about different AI learning methods. Upon completion, you should be capable of assembling solutions, and understanding human intelligence from a more high-tech, computational perspective.
Artificial Intelligence Course at Saylor.org – the course introduces students to the advanced field of artificial intelligence. Major study areas include topics such as machine learning, AI programming, game playing, robotics, and language understanding.
Stanford University: Artificial Intelligence: Principles & Techniques – an excellent curriculum for students interested in learning more about AI. The course focuses on foundational principles of artificial intelligence, and it included topics such as machine learning, Markov decision processes, logic, constraint satisfaction, and graphical models. The goal is to equip student with tools to implement AI into daily practices and solve problems that people find difficult to tackle.
Read books and articles on Learning Artificial Intelligence
Apart from courses on artificial intelligence, passionate programmers, software developers, and computer science students can also read books on the topic. There are quite a few out there that are both puzzling and incredibly interesting. All of them will help broaden your knowledge on AI and its potential. Here are some good reads to check out.
[PDF] Artificial Intelligence: A Modern Approach, by Stuart J. Russell and Peter Norvig – in the first part, the book teaches readers about intelligent agents. Then it introduces the notion of problem solving, knowledge and reasoning, and more. At the end, it reveals a conclusion that sums up AI’s potential and attempts to change the future of technology.
The AI Revolution: Road to Superintelligence – a very detailed, unbiased article on artificial intelligence that tries to explain some of the most common misconceptions surrounding the artificial intelligence field.
[PDF] Simply Logical: Intelligent Reasoning by Example, by Peter Flach – learn the basics of AI programming. The book is a combination of artificial intelligence, Logic and Prolog. Every technique presented is accompanied by an implementing program, and there are lots of examples to make concepts easier to understand.
[PDF] Practical Artificial Intelligence: Programming in Java , by Mark Watson – targeted at both hobbyists and professional programmers, the book teaches readers how to make AI practical. Each chapter has a learning technique, some theoretical insight about that techniques, and a Java example that can be used to experiment and practice.
[PDF] The Quest for Artificial Intelligence, by Nils J. Nilsson – everything you need to know about artificial intelligence is in this book; from the early beginning (back when AI was a mere concept) up to the present day (pioneers in the industry and today’s AI engineers).
Attend meetings, conferences and watch presentations on artificial intelligence
We’ve mentioned the courses and classes you can attend to learn about artificial intelligence, as well as the books you can read to help expand your knowledge and broaden your understanding of the field. Now it’s time for some deeper reasoning on AI. One of the best ways of learning more is by attending meetings and conferences, and listening to live talks. Some interesting debates and presentations are:
Elon Musk talks about Artificial Intelligence at MIT – this 1-hour discussion was held in 2014 at MIT, when the Department of Aeronautics and Astronautics celebrated its 100th anniversary; a very interesting presentation that covers a wealth of topics, from Mars exploration and NASA’s role to AI warnings and Tesla’s collaborations with the electronic vehicle industry.
Davos 2016, The State of Artificial Intelligence – a detailed debate with the purpose of answering a very important question. “How close is advanced technology from overhauling human intelligence and what implications does AI have in today’s modern industries?”
[Documentary] Artificial Intelligence and Robotics – “Looks can be deceiving” and this documentary will tell you all about that. For many decades, we’ve seen Sci-Fi movies portray robots as man’s loyal servants. However, AI and robots are no longer a matter of Sci-Fi. Robots are challenging to craft because the real world is like the Wild Wild West: rich and unforgiving. Advanced technologies such as machine learning, programming, deep learning, and pioneering software, give us some sort of hope that the industry of robotics might get robots out from the labs and out into the real world.
Elon Musk talks about artificial intelligence at Sanford University (2015) – the AI focus begins at minute 27. Elon Musk talks about advanced technology in the future, and about what we should expect to happen with artificial intelligence 25 years from now.
Bill Gates and Elon Musk talk about AI safety – both Gates and Musk talk about super-intelligence, AI, and what can the technology do for us humans. The discussion addresses matters of extreme importance, such as making artificial intelligence safe. Musk mentions that releasing AI is easy. Containing it and keeping it safe is the challenging part.
Artificial intelligence is no longer a product of our imagination. AI is real and we use it daily. Cortana, Siri, and Google Now have become our most valued virtual personal assistants. The gaming industry uses artificial intelligence to create seamless online experiences and the auto industry currently focuses on smart cars that drive themselves. Fraud detection and purchase prediction software programs are artificially intelligent products too. In layman’s terms, your house, bank, smartphone and car all use AI on a daily basis. Some of the things they can do are obvious; others might just fool you into believing that there’s a real brain at the core of your new iPhone. Let’s have a closer look at some of today’s most fascinating examples on artificial intelligence.
Super computer Watson – back in 2011, IBM’s super computer Watson managed to defeat the two best Jeopardy! champions, and collect the grand prize of $1 million. Watson harnesses and processes over 2.5 billion gigabytes daily. The computer’s machine learning capacities perfectly stimulate the human brain, but it is programmed to eliminate errors and biases out of the decision-making scenario. For 2011, Watson was an AI breakthrough.
Self-driving cars – Google came up with its first self-driving car in 2011. Four states in the US – including Washington D.C – were convinced that the autonomous car should be allowed to be tested on the streets. Things have changed a lot since, and increasingly more auto companies gained an interest in the technology. Tesla’s Model S autopilot feature is mind-blowing, and Elon Musk says this is just the beginning.
Amazon Echo – Echo is Amazon’s newest voice-activated smart home device. It is practical and accessible, and it packs a wealth of features and integrations. The compact AI device is a more advanced version of Apple’s Siri. Use it as a voice assistant, send requests and get things done around the house fast and effortless.
Autonomous: Your Personal Robot – Autonomous is the creator of Personal Robot, a really cool new product that connects to all smart devices in your home. It uses artificial intelligence software to make your home secure, and advanced algorithms to “read” your mood. Personal Robot doesn’t just understand; it actually knows what you want and need. On top of everything, it collects data being able to learn and improve on a daily basis. Some of its core features include facial recognition, emotion recognition, and deep learning.
The Internet has opened the ability to research everything within an instant, search engines such as Google allows you to input your symptoms and a number of answers pop up. Technology can improve your health and technology is certainly getting smarter to narrow down the correct health implications as described in this article – 8 ways Technology Is Improving Your Health
AI in the future
Will artificial intelligence destroy us? Or will it make us super human? Some people argue that it might solve problems such as global warming and the way we connect with people; others say it’s dangerous because it can’t be controlled. We won’t be seeing walking robots dressed as humans any time soon, but our children’s grandchildren might. Artificial intelligence is not just about robotics. The industry spans over a wealth of other industries, including business, auto, retail, medicine, and numerous others.
AI has gone mainstream, and today’s savvy software developers and programmers are fascinated by its potential. Still asking the question: ‘How to start learning Artificial Intelligence?’ , then our advice is to start with the basics first – advanced math. Move up and take a step further by learning a programming language. Get more familiar with machine learning and you’ll be ready to understand artificial intelligence too. Advanced technologies like AI slowly move out from the data centre and out into the world.
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Tags: AI, Artificial Intelligence, How to start learning Artificial Intelligence, learning artificial intelligence, machine learning