Core Skills Required By AI/ML Experts To Succeed In Their Careers

Each career demands a particular skill set, be it data science, digital marketing, or anything else. Today, we are going to talk about the skills that you need to pursue a career in Artificial Intelligence and machine learning.

Before going any further, let us have a quick overview of what machine learning and artificial intelligence is.

What is machine learning?

Machine Learning is a technique of teaching machines automatically from previous data with the help of algorithms, fundamentally making a machine smart enough to learn its own. Machine Learning is a part, or you could say, an application of artificial intelligence.

For example,  let us say you are watching Netflix and you’ve declined a few recommendations of the “comedy” genre. So, from now on, Netflix’s algorithm (working on machine learning) will not suggest to you any movie or show that is of the comedy genre.

Here, you would see that the machine automatically learned from previous data and decided based on that.

While in Artificial Intelligence, machines are programmed to be as intelligent as humans. With Artificial Intelligence, a machine can self-learn, self-analyze, and again self-learn and self-correct itself without any human interference.

For example-  T-1000 from terminator or self-driving cars.

Now, let us look at the skill sets and knowledge required to become a machine learning and artificial intelligence expert.

1) CS Fundamentals and Programming Knowledge

Having a solid command of fundamentals and hard-core knowledge of programming languages is a must for any aspiring machine learning and artificial intelligence personnel. Your day-to-day tasks will ask for the implementation of both of these things.

You have to be well-versed with various Computer Science concepts like data structures, different types of algorithms, space and time complexity, etc. Simultaneously, you must have hands-on experience in programming languages like Python, R, L and statistics, Spark and Hadoop, SQL, Apache Kafka, etc.

Related- Logistic Regression using R

2) Natural Language Processing

Natural Language Processing is the most important part of Machine Learning and Artificial Intelligence. In simple words, Natural Language Processing aims to teach the human language to computers so that machines can understand and interpret the human language. The aim behind this is to make better communication between machines and humans.

3) Applied Mathematics

Mathematics is an essential skill in the armory of an ML and AI engineer. Mathematics has various uses in ML & AI when playing around with algorithms, data, or statistical data. Important maths topics that you need to learn are linear algebra, statistics, calculus, probability, distributions like Poisson, normal, binomial, etc.

Conclusion-

Machine Learning & Artificial Intelligence have become more widespread and are used in every field these days. So, I would say that stepping into the field of ML & AI is indeed a great idea. So make sure you get your grip tight on all these concepts mentioned above.