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Artificial Intelligence: Learn Everything About AI in These Online Courses (Including AI Programming)

In this overview, we will show you what AI is and how to learn more about it. Train yourself and become an AI programmer!

Artificial Intelligence: Learn Everything About AI in These Online Courses (Including AI Programming)
Picture: ArkhipovAleksey/shutterstock

Artificial Intelligence (AI) is not only relevant for science fiction writers. 

Robots, automated translations and self-driving cars impressively show what possibilities arise with AI.

But what is AI exactly? And how can you learn more about it – and become an AI software developer yourself?

(Jump directly to the online courses about AI here.)

Keep reading to find out:

1. What AI is

2. Why AI is important today

3. How you can learn more about AI and become an AI programmer 

1. What Is Artificial Intelligence? And What Is It About?

The aim of AI research has always been to artificially emulate human intelligence. This is, however, extremely difficult for a variety of reasons. (The problem starts with the definition of "intelligence".)

We speak about Artificial Intelligence today when computer systems solve problems independently.

In contrast to a traditional algorithm ("if problem X, then solution Y"), the machine independently chooses the solution for a given problem.

To be able to do this, a computer system's self-learning ability is particularly important. The computer first needs to learn how certain tasks are solved.

So how can computers learn?

Simply put, by being trained using large data sets. For this, the system is organized as an "artificial neural network", which works in a way similar to the human brain.

The learning process with training data is called Machine Learning or Deep Learning. Thus knowledge is generated from experience – for example, by pattern recognition. Modern statistical methods are used to achieve this.

In summary:

--> AI systems are no longer being instructed by their programmers with a fixed algorithm for a single solution.

--> The AI system learns independently from huge data sets how problems are best solved.

--> To do that, the system needs to be programmed appropriately.

Artificial Intelligence: Learn Everything About AI in These Online Courses (Including AI Programming)
Picture: geralt/pixabay

2. Why is AI Important Today? Why the Hype?

Recent developments have led to an enormous increase in the importance of Artificial Intelligence:

  • Technological progress: The programming of Machine Learning / Deep Learning systems with artificial neural networks is now well advanced.
  • Data volume: There are many areas with incredibly large amounts of data (Big Data) that are available for training purposes of AI systems (for example, image data, voice data, search queries).
  • Computing power: The computing capacity to process large amounts of data is now available.
  • Relevant applications: AI applications for the mass market became possible, for example, in the areas of:

- Internet search (e.g., Google RankBrain)

- E-mail spam filters

- Speech recognition (for example, Siri, Amazon Echo/ Alexa)

- Automated translation (e.g., Google Translate)

- Image recognition (e.g., in radiology)

- Robotics and self-driving cars (connects AI technology and mechanical components)

The AI machines are far superior to human experts in many areas. Reports about achievements in chess and pokerlipreading, and mind reading prove this point. Already pieces of music and paintings can be created independently by computer systems. And even chatbots are beginning to sound natural.

According to experts, Artificial Intelligence will affect many areas of life and most industries in the years to come. Therefore, serious critics like Professor Russel from UC Berkeley begin to consider a possible future threat from "superintelligent" robots (see this speech).

Currently, there are many companies and organizations that require people to fill jobs and projects that arise in the development and application of AI software. IT professionals with relevant skills are, of course, in great demand.

The AI expert says: "Artificial Intelligence is the New Electricity":

(From 2:30, neural networks from 25:30)

3. How Can You Learn More About AI Programming?

We list various books and online courses below that deal mainly  with the programming of AI systems. (Some of them are even free.) These are mostly for computer science students or software developers who want to grow their skills. But other interested learners can gain insight in AI as well!

(Note: Basic prior knowledge in certain areas is sometimes required. If you want to brush up on these subjects, check out these courses for example: Essential Mathematics for AI (Microsoft), Mathematics for Machine Learning (Imperial College London), and coding skills in the Python programming language.)

Basic AI Books

Even if they do not replace a university seminar or an online course, textbooks may be a useful addition and learning aid for AI learners. Here are two well-known books:

  • Artificial Intelligence: A Modern Approach: A classic textbook by well-known Professors Russell and Norvig. At approximately 1,000 pages and on the professional level of an undergraduate study program, the "intelligent agent" is explored in great detail.
  • Deep Learning: This book gives a comprehensive explanation of machine learning with artificial neural networks for students and practitioners.  lt also includes sections about the required linear algebra and statistics knowledge.

Online Courses on Artificial Intelligence

Introductory Courses for Beginners

These courses are often designed for students or programmers who want to approach the field of AI. The mechanics of artificial intelligent systems are explained step by step. Some of the courses can be taken for free, while an (optional) certificate may have a nominal cost.

  • Beginners can get an overview of artificial intelligence in the AI for Everyone course offered by Andrew Ng, who is one of the leading AI experts. This course was not only designed for programmers and tech experts, but also for business executives and other learners with not technical background.
  • In the basic Intro to Artificial Intelligence course by provider Udacity, participants will also get a broad overview of the subject. From statistics and the functioning of artificial neural networks to image processing, speech recognition, and robotics, many important areas are covered. Participation is free, but basic prior knowledge in statistics and linear algebra is required.
  • In the AI course from Columbia University (via edX), the foundations of AI can be studied as well. Since practical AI problems are being addressed, knowledge in Python is beneficial. The course is free, and an optional certificate can be purchased.
  • Artificial Intelligence AZ is the hands-on course by Udemy. Here, participants can learn how to program an AI sytem in more than 100 short video lessons. No prior coding skills are required (only high school knowledge in maths).
  • Machine Learning by Stanford University is one of the most famous introductory courses on the subject. Professor Andrew Ng was the leading AI expert at Google and Baidu, and he is the founder of Coursera. Course participation is free (an optional certificate can be purchased), and the necessary algebra basics are included in the course.
  • Microsoft teaches Principles of Machine Learning (via edX). Here participants learn how ML models in the programming languages R and Python can be created with the Microsoft Azure cloud computing platform.
  • Google also offers a free ML Crash Course. More than 18,000 Google employees have already taken the course, which also includes an introduction to Google's TensorFlow platform.

Longer Course Series for a Career Start in AI

These paid course series are usually made up of 4-6 individual online courses (MOOCs). They comprehensively prepare you for a career in this field. You should allow some time in your schedule for these courses over several months. After successful completion, you can receive certificates recognized by potential employers. ("Are the Certificates Worth It?")

This series of courses offers comprehensive training in the field of artificial intelligence, which should enable immediate real-world programming activity. The courses and practical projects were created with industry partners such as IBM and Amazon. The Nanodegree certificate from Udacity is well known by industry experts. Duration: approx. 6 months.

The MOOC series at Columbia University contains 4 courses. In addition to the basics, machine learning and robotics play an important role. The program contains approximately 25% of the content from a master's degree program at Columbia.

This course sequence by leading AI expert Andrew Ng gives a detailed introduction to Deep Learning. The various video courses and projects can be completed within a few months. However, prior coding knowledge is an advantage.

This Nanodegree program from Udacity explains the technical details of machine learning. The lecturer is Professor Sebastian Thrun, who is also the founder of Udacity. The program lasts about 6 months.

Other Interesting AI Courses

  • A Python Bootcamp for ML applications is included in this online course from Udemy.
  • Four individual MOOCs are available in this course series – which covers robotics – from the University of Pennsylvania.
  • The AI application of self-driving cars is taught in these Nanodegree courses co-created by Daimler, BMW and Uber.
  • This Coursera Specialization shows how recommender systems can be programmed by means of ML.
  • Deep Learning as a special field of Machine Learning is explained in great detail in this free video course, which was developed with AI experts from Google. There is also another free course program available from an IBM-sponsored learning platform. The advanced concept of Deep Reinforcement Learning is explored in this course series.
  • Key for modern machine learning systems are artificial neural networks, which are the main focus of this Coursera-MOOC.
  • This short video course shows how ML models in the Google Cloud with the open source platform Tensorflow can be implemented (1 week).
  • Those who want to approach the field of artificially replicated intelligence by a study of the human mind can learn with these MIT video lectures, which explore the borders between computer science and philosophy.
  • Selected aspects of AI philosophy are being discussed in the podcast series of MIT's Lex Fridman. This includes Gary Kasparov remembering the moment when he realized the superiority of AI chess computers.

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