Understanding Artificial Intelligence for a successful career in AI
Artificial intelligence is a wide and complex area that can take someone many years to master. The area comprises of so many topics that are sometimes not easy to understand if the wrong resources are used for learning. Given the vast time you are required to invest in learning, experimenting, researching and working towards a successful career, it is always prudent to first identify what you love most and focus your career on that.
Your passion may be on cars, sports, health care, finance etc, but there is always that dilemma which AI can come in to resolve. Knowing what you want will also help you in making a decision on the branch of artificial intelligence you should concentrate on.
To start with, you need to first understand that Artificial Intelligence is a very general term. AI is classified into two sub-topics of machine learning and deep learning. This means that, you need to decide on which area you want to specialize in before you start any course in Artificial Intelligence. Now, let’s look at the topics covered in each of these two areas and how each of them can be applied to solve social and business problems.
1. What is Machine Learning Learning ?
Machine learning is a branch of Artificial intelligence which focusses on the scientific study of algorithms and statistical models that computer systems use to perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence
If you decide to narrow down artificial intelligence to machine learning. There are many online resources that can take you to the next level. But before you enroll on any course, you must reflect on your learning style. That is, do you learn best with videos, books or audio?
I will focus on useful resources for each type of learning methods but let’s first break machine learning into its different sub-topics that will help you understand the most used machine learning algorithms that you can concentrate your efforts on. The objective here is to make sure that you don’t focus on irrelevant things. One thing you need to keep in mind is that the general field of Machine learning is best applicable if you have a lot of text and/or statistical data/numeric data about the problem you want to solve. The bigger the volume of data you have, the better the result you get in machine learning.
4. How and where to learn Artificial Intelligence online
There are many platforms you use to learn Artificial online. Additionally, there are unlimited online courses that can take you to the next level and there are others that will just waste your time. If you are the type of person that prefers to start with advanced topics, you can read scholarly papers on google scholar, arxiv.org, techArvix.org, research gate, and IEEE among other reputable journals and open source publishing platforms.
Depending on your method of learning, we have put some carefully selected resources on the right side of the website that can help kick-start your career in Artificial Intelligence
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