Our last blog post outlined the government plans that intend to continue the UK’s path to AI superstardom. In line with this, it is safe to say that both Machine Learning (ML) and Artificial Intelligence (AI) are two tech trends that show no sign of losing momentum. These technologies have the power to completely revolutionise how a business operates.
As more and more organisations harness the power of AI and ML, many professionals are choosing a career in these 2 disciplines.
As more and more candidates join the talent pool, it will become harder to stand out among the masses.
This post discusses the skills you will require to help you establish a successful and long career in ML and AI.
The skills required for a career in ML and AI.
You will need a heavy combination of both educational, technical and so called ‘soft skills’ to enter the AI and ML domain.
Educational qualifications are a must, with a graduate, masters or doctorate degree in computer science or related subject needed to enter the AI work-space.
AI and ML entail the development of algorithms, so both problem-solving and analytical skills are necessary if you are considering a career in this field.
An AI professional will be expected to have a strong understanding of statistics and probability to understand complex algorithms.
Even in their most simple forms, AI models depend on finding patterns and relationships amid large data samples.
As an architect of these systems, you must have considerable working knowledge of the statistical methods used to derive insights from data.
In addition, you should have a familiarity with common AI models, Gaussian Mixture Models, Naïve Bayes, Hidden Markov Models for example.
These principles are founded upon complex statistical proofs and theorems. AI developers must have considerable knowledge of their subject to understand the working of them.
It is easy to see why a detailed understanding of statistics is required for programmers wanting to become better AI professionals.
Mathematical skills and probability.
Being an expert in applied mathematics is crucial for anyone wanting to pursue a career in AI and ML.
Statistics aside, AI is a field that relies on many mathematical concepts to create artificial intelligence. One of the most dominant is probability. Probability determines a variety of outcomes in AI, so it is vital that AI professionals have a profound understanding of this mathematical principle.
Maths and mathematical principles is just one of the skills needed for a career in AI. Another is the requirement to have an expertise in programming languages such as Java, C++, Python and R.
C++ helps engineers increase the speed of their coding while Python will help them understand and create complex algorithms.
Python is also the first choice for ML developers. It offers various libraries and frameworks which ease the process of creating an AI model.
R helps professionals understand stats, while Java helps implement mappers. These are critical when considering that visualisation has a role in explaining AI.
Advanced Signal Processing Techniques.
One integral characteristic of ML is Feature Extraction. The ability to understand the next feature and how to implement it is an important part of managing a model’s deployment. As such, Ai and ML engineers are expected to be versed in a variety of advanced signal processing techniques.
As AI has become more dominant, digital signal processing has seen a revolution. It has enabled techniques such as layered signal representation, non-linear function approximation and nonlinear signal prediction. This means that aspiring AI professionals need to have a strong working knowledge of algorithms; curvelets, bandlets and shearlets for example to master feature extraction.
Pretty much every AI job description requires professionals to be able to work with large and complex datasets. These are difficult to process using a single machine.
AI and ML professionals are expected to be distributed computing experts as these large datasets need to be distributed equally across an entire cluster.
Those considering an AI or ML career will need to have expertise in Mongo DB along with experience in creating and operating cloud environments.
Companies using ML focussed cloud services are on the rise so individuals who have experience of them are in demand.
AI and ML professionals should also have a grip on Unix tools and have data modelling and evaluative skills. In explanation, Unix is one of the most common working environments for AI/ML pros and form the base of many cloud services.
Do you have these AI and ML must-haves as part of your skillset?
Are you looking to begin a career in Artificial Intellingence or AI? Perhaps you have had a few years experience and are now looking for your next opportunity?
Ignite Digital use our vast network and industry expertise to place IT, tech, digital and data professionals in roles that go on to define careers.
Get in touch today!