No matter which field you belong to, machine learning is finding its way in each and every field. It has grown intensively in the past decade, however, the goal is to reach human-level artificial intelligence which is still a distant future. You can be part of reaching this goal or at least contribute a bit. It can be considered as an immense opportunity disguised as a huge challenge. In addition, many organizations want to leverage benefits from artificial intelligence, machine learning, and deep learning and spending hefty money, creating dedicated departments and teams of experts. However, still, there is a long way to go as a field lacks skilled professionals.
What is Machine Learning?
Machine learning is one of the important parts of artificial intelligence. Machine learning is a set of algorithms that help computers to learn new things themselves with minimum or no human intervention. It is achieved using advanced statistics and massive amounts of data that is created every day. The algorithm along with data helps machines to classify new data into categories such as images, sounds, and videos. Here are some of the online resources that would be helpful to begin your learning in artificial intelligence particularly in machine learning. You may opt for any of the Machine learning online courses listed below and start your journey.
Machine Learning Certification Course – Simplilearn
Simplilearn is a renowned certification training provider and its machine learning program is one of the most sought-after courses among professionals. With over 44 hours of instructor-led training, learners get a clear understanding of all the machine learning concepts like supervised, unsupervised learning, regression, classification, time series modeling, and more. The course also includes more than 25 hands-on exercises, dedicated mentoring sessions from subject matter experts, and working on four real-life industry projects with integrated labs.
Machine Learning Engineer Nanodegree Program – Udacity
This course is offered in collaboration with Kaggle and AWS and is designed for professionals willing to learn advanced machine learning techniques and algorithms. To begin with this 3 months program, you first need to have a prior understanding of intermediate Python and machine learning algorithms. You will learn how to package and deploy the machine learning models to a production environment. If you are not already familiar with machine learning algorithms, you can first enroll in Udacity’s Introduction to Machine Learning free course and learn the basics.
Machine Learning – Coursera
Coursera offers various training programs along with a certification in different fields including machine learning. This machine learning course is offered by Coursera in collaboration with Stanford University, California. The course is offered in English with subtitles in language including Hindi, Spanish and Japanese. It is designed eloquently providing sufficient focus on all aspects of learning such as machine learning concepts, practical learning, and current best practices. It starts with fundamentals and gradually builds over to greater depth and difficult levels. At the end of the course, you would be equipped with the most effective machine learning techniques that you will be able to apply to real-world problems.
Data Science: Machine Learning – edX
Since the course offered is part of the Professional Certificate Program in Data Science, one is recommended to complete preceding courses before enrolling for this course. The course covers machine learning algorithms, component analysis, and movie recommendation systems. By going through all these you will learn to explore data for predictive analysis, create and train an algorithm with data.
Artificial Intelligence Foundations: Machine Learning – Linkedin Learning
In this course, you will learn an overview of machine learning fundamentals and basics. You will start learning about algorithms, specifically, algorithms developed previously and used widely in the machine learning field. While going through algorithms such as decision trees, regression analysis, and clustering, you may observe how machines learn themselves and compare various algorithms. The course covers different types of machine learning concepts such as supervised, unsupervised, and reinforcement. Moreover, some improvement areas in machine learning need to be addressed in the future.
Conclusion
A lot of innovation is done in AI, machine learning and still, a lot has to be done. It is evolving at a rapid rate with more and more skilled professional joining. In the future, innovation could be in your field of work or field you are interested in such as aviation, automotive, medical, manufacturing, agriculture, and so on. Due to the immense potential, artificial intelligence, machine learning, and deep learning are making their way into all sectors. Sooner or later AI may cut across your domain of work and may affect you in the future. It is highly recommended for professionals and beginners to start exploring more into AI, machine learning, and deep learning. As you can see in previous paragraphs, there are many good online courses available for you to start with machine learning training. Most of them are flexible enough to allow you to learn at your schedule and pace. All you need to do is start learning based on your time availability. Moreover, you can seek certification if you like to at the end of some courses which would help you in seeking job opportunities in machine learning. If you are already working as a professional then you may opt to improve or enhance your skills. With all the information and details on machine learning hope you have a better picture of where and how to start for machine learning.
