How to Get a Job in Machine Learning in 2020
Machine learning is not just the latest fad. It is the path to success. Get these key machine learning skills to succeed in this competitive field.
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You have completed your engineering degree and are now looking for a break in the intensely slow job market. Unlike a decade ago when an engineering degree would inevitably be followed by a cushy job, the focus today in the job market has shifted from traditional jobs to technology-focussed roles. As more companies adopt artificial intelligence technologies and transform virtually every industry, there has been a marked increase in the demand for engineers and data scientists who know how to work with a wide range of machine learning platforms and languages.
The Artificial Intelligence and Machine Learning market are expected to grow to a staggering $8.8 billion by 2022. Unfortunately, companies are finding it very difficult to find people with relevant experience. This has resulted in a huge deficit in the number of qualified machine learning (ML) developers. In this article, we look at some of the factors that can help you become a sought-after machine learning expert.
How to Become a (Marketable) Machine Learning Professional
Learn the “Right” Languages
If you need to build a career in machine learning, it’s important to get a good grip on programming languages such as C++, R, Python, Java, and SQL. Among these, Python and R are the most popular programming languages for machine learning and is often a prerequisite for most machine learning courses.
Build a Solid Foundation in Data Modelling
For becoming a machine learning professional, you do not need to be a data scientist. However, you do have to learn about data modeling and evaluation to identify and analyse the unstructured data models. Machine learning engineers need data modeling to find data patterns, predict properties of unseen instances and determine the accuracy/error measure.
Hone Your Math Skills
A good understanding of statistics and probability is the cornerstone of machine learning. Statistical concepts like Mean, Standard Deviations and Gaussian Distributions are required along with probability theory for algorithms like Naive Bayes, Gaussian Mixture Models, and Hidden Markov Models.
Learn Machine Learning Algorithms
Machine learning professionals need to have a firm grasp of algorithm theory and how algorithms work. This includes knowledge of subjects such as partial differential equations, convex optimization language, quadratic programming and more.
Other technical skills that a machine learning professional must be proficient with include UNIX tools and Advanced Signal Processing Techniques.
While mastering technical skills is extremely important, it’s also vital to have good soft skills. Machine learning professionals need to have good domain knowledge, excellent communication and problem-solving skills. Most importantly, a machine learning engineer needs to keep pace with the rapidly changing technology. With new technologies and paradigms exploding on the scene, you need to stay current and enhance your knowledge regularly. This could be achieved by subscribing to online courses, subscribing to the latest technology blogs and regularly following research papers.
According to Analytics India Magazine, in 2017, around 78,000 jobs in the Data Science and Machine Learning space were lying vacant in India. By becoming proficient in key machine learning skills, you can find excellent opportunities in this domain. Moreover, considering the rapid rise of AI and machine learning, no matter what industry you’re in, the new-age technologies will be impacting your job soon if they haven’t already. This is why raising the skillsets to keep up with these groundbreaking trends is key to remaining competitive in the AI-run world.
edu plus now’s Certificate in Machine Learning is one of the best machine learning course online that has been specially designed by industry experts and the professors to make sure that students are not just primed for success but ready to excel. It is designed to help you learn complex theory, algorithms and coding libraries in a simple way. It will show step-by-step developments of Machine Learning algorithms that are used to solve real-world problems.