The world of AI(Artificial Intelligence) can be a little overwhelming for people who have no idea about the nitty-gritty of the vast upsurge of AI in the modern world. I cannot promise that you will become a master of AI by the end of this article but, what I can promise is that you’ll have a basic roadmap and understanding of the world of AI. By the end, I’ll provide links to the places which can take you forward in your journey into this new world.
We come across various terms when we talk about AI, words like Deep Learning, Machine Learning, Data Science etc. These words and their worlds are intertwined. To dive deeper into one, you will have to master the rudiments of the other. Let me explain with a simple Diagram.
As you can see in the Venn-Diagram above. Data Science is a small part of AI. If we dive deeper into the world of data science, we get to know machine learning. Now machine learning can only explore and analyze the numerical data, what about the images and videos data, that is where deep learning comes into play. AI is a confirmation of all these worlds.
Today AI and ML are the talks of the town, every 1st year engineering student wants to become a Data Scientist or a Machine Learning expert. Most catalogue of courses today are teaching AI and ML the 4 words that are making online learning platforms more money than we can comprehend. But, thanks to YouTube we have a lot of free knowledge, more than a person is capable of consuming. The crowd today is learning these skills from an online or physical institution because they give you a certificate that you now have a new skill and proof. We feel a sense of accomplishment and trigger a release of dopamine. Our dopamine makes people more money than we can imagine.
Now that we have a general overview of this field we can move forward to busting some myths-
· We can learn just Data science (or one part of AI) and be done with it- All the fields of AI are interconnected. You can’t just start at one or end with one. When I started, I started with the thought I was just gonna learn Data science and add a new skill to my resume, and I ended up working with Deep Learning. There is no Deep learning if you can’t master the basic concepts of DS and ML.
· You can get a job in AI learning from online courses- The jobs in core AI require a background in complex statistics. Remember? The topic you thought was easy in school? yeah, bad news, it does not stop at mean median and mode. These courses can help you find an internship but then it's up to you to build a career in it.
· The AI field is too complex to master- Yes, the top-level innovators who are working with Google in voice recognition, face recognition and all sorts of AI are very experienced, but I can assure you that if you have decent coding knowledge and are willing to put in the hours you can create your own AI projects and code in 6-9 months. You can’t become an innovator at tesla directly but yes, the experts too started somewhere.
· AI will replace most jobs and the ones who know how to build it will be the only jobs in demand- This statement is partially incorrect, every machine needs human supervision and control, no matter how complex. AI has indeed taken the world by a storm, but when you step into the world of AI you will see how much improvement AI needs.
To tread into the field of AI we need to first have a good hold on any one of the programming language, you can choose from Python or R. I prefer python because of its flexibility. You can type python on YouTube, you will get 7-12 hours of videos that you can learn from. But programming can only be learnt by practising. You can use Hackerrank.com to practice your Coding Skills.
Once you have a decent amount of coding knowledge you can start learning AI and ML either from YouTube or from any online course websites and start making your own projects which can further lead to various Internships and Career paths.
Soon everyone would be making AI-based products, only the quality ones will succeed so go for the quality and not for quantity.
by Shaswat Tripathy