Every job or career demands a particular set of skills necessary to pursue that career. Without having those skills you cannot excel in your career; the same goes for artificial intelligence and machine learning. 

Today, we are going to discuss: 

• The skillset required to become a successful AI and ML personnel
• What are the nuts & bolts required to flourish a career in AI and ML

But first, let’s have a look at the basics of ML and AI.  

Machine Learning

Machine learning is an application of artificial intelligence that is used to teach the machine and algorithms. Machine learning aids major tasks, like the self-learning of algorithms.

It also helps the statistical models perform various tasks like learning from previous data, identifying different patterns that will further help in decision making. Machine learning makes the most out of what we call artificial intelligence. 

For Instance, have you ever noticed how amazon recommends similar products or products you like again and again? Yes! That's how machine learning works. The algorithms of amazon are learning from your previous data i.e, your purchase and surfing history. 

Artificial Intelligence

If I had to explain artificial intelligence in the simplest way, I would say that it is a concept where we make machines that can imitate humans or can do work instead of humans in a fast and efficient way. With artificial intelligence, machines/computers can self-learn, self-analyze, and again self-learn, and finally correct themselves on their own without human interference. 

Artificial intelligence machines/computers are equipped with smart coding so that they can learn from previous data and make smarter decisions. The major goal of artificial intelligence is to reduce human efforts and automate processes for a seamless experience. 

Now, let us talk about the skillsets that are required by AI/ML engineers for a successful career –

Technical Skills

Programming Languages

If you want to even start your career in artificial intelligence and machine learning you need to have a good understanding of programming languages, preferably python, R, Java, C++. These languages are easy to learn, and their applications have more scope than any other language out there. And as for Python, it is the undisputed king when it comes to machine learning.  

Linear Algebra, Calculus, Statistics 

You should also have good knowledge of a few mathematical and statistical concepts like Matrix Multiplication, Matrices, Vectors, Linear Algebra, and Calculus. Knowing Derivatives and Integrals and their applications are equally essential.

You must also know about important statistical concepts like Mean, Standard Deviations, and Gaussian Distributions along with algorithms and models like Gaussian Mixture Models, Naive Bayes, and Hidden Markov Models to thrive in the industry. 

Signal Processing Techniques

Knowledge of Signal Processing and the ability to solve different problems using Signal Processing techniques is essential for feature extraction, a crucial slant of machine learning. Then comes the Advanced Signal Processing Algorithms like Shearlets, Curvelets, Wavelets, and Bandlets and time series analysis. Profound knowledge of these will help you solve complex situations. 

Applied Math and Algorithms 

Solid expertise in algorithm theory is certainly a must for AI/ML. This will help you understand subjects like Convex Optimization, Gradient Descent, Quadratic Programming, Lagrange, Summations, and Partial Differential equation.  

Neural Network Architectures 

Machine learning is basically used for tasks that are far beyond human capability to code. Neural networks are proven to be by far the most explicit way of countering many problems like Speech Recognition, Translation, and Image Classification that play a crucial role in artificial intelligence. 

Non-Technical skills 

Communications Skills

Having great communication skills is a must in every industry and artificial intelligence and machine learning are no exception. Explaining highly technical concepts like artificial intelligence and machine learning to a layman can be possible by only communicating fluently and clearly. An AI and ML expert works alongside a big team of engineers and non-technical departments like the Sales or Marketing departments. 

Domain Knowledge 

Projects need to be finished without any flaws. AI/ML engineers work for different industries throughout their careers. So an AI/ML must have profound knowledge of how the industry (that they're working in) works. 

For instance, if you have to implement artificial intelligence in the banking industry, then you need to have a good understanding of how banking sectors work. 

Conclusion

Every professional out there is fascinated by the power and growth of artificial intelligence and machine learning.  More and more people are stepping into artificial intelligence and machine learning every day.

Both the fields are making human life easier, serving businesses to grow and taking us on a new level of evolution. So, if you want to get started in AI and Ml, this is the best time, and believe me, the growth in this field is immense.