Artificial intelligence is a wide field with a lot of new happening on daily basis. Therefore, it can be quite overwhelming for a non-technical person to actually start off with the learning path. To make it a bit easier for you, I have accumulated some of my top learning recommendations together with direct links to the sources to start with. After going through the materials listed below, you should definitely have much more confidence when it comes to understanding the underlying principles and the business approaches towards AI. And hopefully, you would be wanting more!
I started off with YouTube videos and lots of reading about that field. Youtube videos are a great way to catch the basic overview and knowledge of what AI is all about. You can find quick 5-minute videos, series of more in-depth learning while as well, documentaries.
One course that I found very valuable was called “Deep Learning SIMPLIFIED”. It’s a series of 30 short videos and I guess that it’s my top recommendation to watch when it comes to YouTube videos. It helped me a lot while investigating this field, so if you don’t have enough time right now, feel free to get back here anytime to check out the series with the first video accessible below.
On the other hand, I personally wouldn’t recommend spending too much time on YouTube videos. It’s very easy to get stuck on similar content for a long time without gaining any additional knowledge. By the time I finished writing the theoretical overview of my master thesis in the AI field, it was very hard to find new videos that I haven’t seen yet while inserting “artificial intelligence” or “machine learning” to the YouTube search engine. However, only a small part of those videos generated new knowledge to me, which thinking back, was clearly a misuse of valuable time. Therefore, in my opinion, a few hours of videos about artificial intelligence seems to be sufficient at the beginning of the learning path before it’s the right time to move to the new knowledge source.
After investigating how AI actually works, it’s time to get into the business! A global consulting firm McKinsey issued in 2017 a very good report on the topic of how businesses are ready for AI adoption. It shares extremely valuable insights and statistics on how companies are actually using AI, what industries are leading the technological development and also how the profit margins differ between companies using or not using AI. In my opinion, it’s a must read for all business people interested in AI!
I was learning the field of AI for over a year without actually becoming technical. Even if you don’t plan to become an engineer, but are planning a career in artificial intelligence, then understanding how AI is created is crucial. Looking into technical tools will give you so much more actual understanding of how this world works.
What do I mean by technical tools? Simply said, to create solutions based on artificial intelligence, you would need two main things – code and data. The most popular programming languages in the field of artificial intelligence are currently Python and R. While the preference can be very individual, Python is considered to be easier to pick up and therefore often recommended to learn as the first programming language. Python is also more popular when it comes to quotes in job descriptions – for example from a graph below we can see that since 2013, skills in Python (yellow line) have become almost twice more in demand in job postings compared to R (blue line).
Many of you might think now about the difficulties of such a dedicated learning process alongside the job you are currently doing. Fortunately, there are a lot of ways to learn on a budget with the schedule that suits your needs – even if can do that for 10 minutes a day, it’s something. There are amazing online courses available in Udemy, Coursera or Udacity. I will be focusing mainly on Udemy as this is the place where I have done most of my learning. Udemy provides online courses on almost any topic possible – from public speaking to hardcore reinforcement learning (a subfield of artificial intelligence). They usually offer the courses for very good prices as most courses I have seen are priced between €12-15. For that money, you can get tens of hours of teaching materials with a very hands-on approach from top-rated instructors.
I personally find very easy to follow the courses taught by Kirill Eremenko. He has a very nice online course of Python for data science (see below). It’s perfect for beginners in programming as it explains both all the relevant programming principles as well as teaches to analyze and visualize data with Python. At the time of making this post, the course cost €11.99 and offered 11 hours of videos. However, this time indicates only to the length of the video, but as Udemy courses usually are always very hands-on, this means that you might spend half of the time doing exercises on your own. This course doesn’t relate to machine learning yet, but it’s strongly recommended to start off with basic Python before moving to the full world of machine learning for which Kirill has a course as well.
Another skill required to work with big datasets is SQL. Even though SQL has become quite a common skill among business people, there are still a lot of people unfamiliar with that. SQL is a language for communicating with rationale databases and extracting data out of those. It’s a relatively easy skill to master and I’ve heard stories from people who have watched a 1-hour YouTube video of SQL and after that became confident to start working with it. The course I can recommend about SQL is around 4 hours and I completed that on the same day I started. It gave good basics to perform data analysis with MySQL and what’s the best – you can always get back to your notes made during the course. However, don’t hesitate to look after other courses depending on your skill level!
There are many other tools used in a world of artificial intelligence, but those mentioned above should give a non-technical person a good starting point to enter that field. The start of the learning path is always the hardest – both due to the lack of motivation and also due to the overwhelming amount of new skills to be learned. However, you become more knowledgeable with every minute spent on learning – so why not to give yourself a promise to learn something new for 30-minutes every day?
