Machine learning can be your best bet to transform your career

Meta- Machine learning is also booming as a field of study. While virtual courses on AI and machine learning can be a pricy affair, the very attempt in learning machine learning can be done otherwise as well.

This is the best time to learn machine learning as the trends in the market suggest. The global machine learning market is estimated at US dollar 8.43 billion in 2019, and is expected to reach 117 billion by 2027, at a CAGR of 39.2%. Thus, job opportunities in this sector are going to grow with a boom in the coming years.

AI and machine learning are not only used in machine learning applications but also in Internet of things, like self-driving cars, smart homes, digital assistants, etc. In fact during COVID-19, statistical machine learning had played a significant role in generating advanced models for predicting virus spread, and aided in the management of the pandemic across the world. Machine learning in finance has also secured a respectable place among the business leaders using the technology for generating automatic models for stock management.

While this article will guide you through some of the best ways of finding machine learning courses online, we will also give you some tips for learning machine learning at your own pace through books and other resources.

And even before to choose the right course for yourself, you need to decide, which language you want to use. If you have an existing competency in using R, you should be looking for courses which focus machine learning with R or if you are a python user, you should focus on machine learning using Python.  Java script machine learning or PHP ML are equally good choices based on your requirements and background.

Secondly, you need to figure out which kind of specialisation you want to develop, for example whether, you want to work with supervised machine learning algorithms, which are very commonly used in applications and tools, or you want to work with more sophisticated deep learning algorithms, which help you create neural networks which are capable of taking decisions on its own. On the other hand, if you are still a beginner, you can look for courses which provide an introduction to machine learning or start with introductory books like "Deep Learning" by Goodfellow, Bengio and Courville.

Next, you need to figure out how what kind of certification you require. If you are self-employed and are going to use it for your own intellectual growth, you might want to check out free courses like Intro Machine Learning on Udacity or audit popular courses like the Stanford machine learning course Andrew Ng on Coursera. However, if you want to use  it to land a job, you will probably have to spend big bucks on purchasing courses such as the one mentioned above or look for more budget friendly options on other online learning sites which cover similar topics and supplement them with the books and more popular courses.

Along with the courses, Erich Jang, a research engineer at Google Brain, suggests, one of the best ways to learn machine learning is to implement some of the papers on your own on a specific sub-field of machine learning like Bayesian deep learning, computer vision, natural language processing etc. Later having picked up the fundamentals, it will become easier to dive into the other branches of deep learning. Another important suggestion from Erich for beginners is that, you should not start by implementing your own models right away and rather improve on existing models, as this is less time consuming and will keep you motivated to try out newer things constantly. 

Finally, given it is a complicated field, patience is key!