Free Machine learning certifications online is becoming one of the most exciting and rapidly evolving fields of computer science. There are an infinite number of industries and applications that machine learning can make more efficient and intelligent.
Although the concept of machine learning is a mystery among non-specialists, those who know are well aware of its importance. The ability to learn in all aspects of this field can be a vital turning point between a career in IT and a career that is extremely exciting!
What is machine learning?
Machine learning is the process of learning machines to learn from experience so that their productivity improves over time. You would notice that your referral systems improve over time because they work with the data. The more data you provide, the more it learns, and the better the algorithm works. As a result, machine learning has found its way into industries that need to profile consumers and provide an improved customer experience.
From machine learning come concepts such as neural networks and deep learning. These technologies are still very young. However, thanks to constant research and achievements, innovators around the world use the latest technologies to create innovative solutions and products.
Can I get machine learning certifications online?
Artificial intelligence training has become very accessible thanks to a variety of courses and trainings available online. They are taught by the best AI teachers, researchers and experts, and they are often much cheaper than a regular course in college. Some of these courses are very comprehensive and include a curriculum equivalent to a college degree. Some of them are even available for free and are perfect to look into the world of artificial intelligence.
15 Best free machine learning certifications online 2021
· Practical machine learning with Scikit-Learn
This is another free course from Udemy for learning machine learning, which focuses on SciKit-Learn. In case you didn’t know, Scikit is one of the popular Python machine learning libraries. It was originally developed by David Cournapo as a Google Summer of Code project in 2007, and has since become a de facto machine learning library for many programmers.
Scikit-Learn is especially great for beginners, as it offers a high-level interface for many tasks, allowing beginners to practice the entire machine learning workflow and better understand the big picture. After learning about Sci-kit, you will be able to explore more powerful libraries, such as TensorFlow. In any case, in this course you will learn several machine learning algorithms, as well as pre-processing, and all this in less than an hour. You will learn about regression, classification, component analysis and improvement of everything in sci-kit-learn, one of the most popular machine learning libraries for python.
· Machine learning course A-Z ™: Python and R in data science (Udemy)
Let’s start with the fact that 411,800+ students have taken this course and it has an average grade of 4.5 out of 5. We consider it one of the best machine learning courses and developed by Kirill Ermenko, Data Scientist & Forex Expert and Hadeline de Ponteves , Data researcher.
This course will help you master machine learning in Python and R, make accurate predictions, develop excellent intuition of many machine learning models, work with specific tools such as reinforced learning, NLP and deep learning. Most importantly, it will teach you to choose the right model for each type of problem. Basic high school math is all you need to know to take this course. With 40 hours of study + 19 articles, we don’t know what else to say to get you to check it out.
· Machine learning course by Andrew Ng
This is a course sponsored by Stanford University that is offered through Coursera. The online machine learning course is led by Andrew Ng, who is the founder of Google’s Deep Learning division. He is also the head of the AI division at Baidu. The course is available online for free. However, you can pay for a certification that will help you when it comes to finding a job.
It covers a number of key machine learning topics that are applicable in the real world. You will also learn how to implement machine learning when developing web applications, mobile applications, data analysis, etc.
· Learn with Google AI
This is a free machine learning resource owned by Google. The company launched it to promote machine learning and artificial intelligence among the population. This resource contains very valuable information that may appeal to those who are just beginning to work in the arena of artificial intelligence.
Since its purpose is to be easy for beginners, you will learn some basics of AI, such as designing neural networks and using TensorFlow. The course is also suitable for those who have some machine learning experience. All you have to do is choose the module that suits your interests and continue it.
· Columbia University Machine Learning Course
This is another free university-sponsored machine learning course. It also gives students the opportunity to pay for a certification that will be used as proof of competence. The course will teach you methods and models that you can use to create machine learning programs to solve real problems. Some of the methods you will study include controlled, uncontrolled, probabilistic and non-probabilistic teaching methods.
The course is detailed and well structured. It contains a lot of learning materials, and each topic is accompanied by exercises to test your understanding. You can find this course on the edX platform.
· Deep learning course (deeplearning.ai)
One of the most well-known deep learning teachers, Andrew Ng, offers you this special course, developed in collaboration with Stanford professors and the nvidia | Institute for Deep Learning as industry partners. The coach is a co-founder of Coursera and in the past led the Google Brain Project and the Baidu AI group.
In this program, which consists of 5 courses lasting several weeks, he will teach you the basics of deep learning, how to build neural networks and how to build machine learning projects. Most importantly, you’ll start working on real-time case studies related to healthcare, music making, and natural language processing among other industries. More than 250,000 students have already enrolled in the program from around the world. Without a doubt, this is the best course of deep learning.
· Design and creation of AI products and services (MIT xPRO)
This productive curriculum is designed to help you understand aspects of AI design and application in a variety of fields. In this training program, you will learn how to develop a product offering based on artificial intelligence and present it to internal stakeholders and investors. You will learn about the different stages of product development based on artificial intelligence, the basics of machines and deep learning algorithms, as well as the application of your ideas to solve practical problems.
You will work with real-world examples and industry examples to better understand the concepts. Once you’ve completed the program, you’ll understand how deploying the right artificial intelligence technologies in your organization can help you automate routine tasks and interact with customers.
· IBM Applied AI Professional Certificate (Coursera)
This program of professional certificates in artificial intelligence was created by IBM, a world leader in technology and one of the pioneers in the field of AI innovation. It is designed for those who want to learn how to work with AI developers. This gives a clear understanding of AI, its applications and uses. It introduces students to concepts and tools such as machine learning, data science, natural language processing, image classification, image processing, IBM Watson AI, OpenCV and API services.
Students also learn to start using pre-created artificial intelligence tools without having to create AI models and server programs from scratch. This is an AI certification for beginners, consisting of 6 courses, which can be passed by students with both technical and non-technical experience. The first three courses of the program also constitute a full specialization in “Fundamentals of Artificial Intelligence for All.”
· Free Machine Learning – Artificial Intelligence Course (Columbia University)
Developed by Columbia University, this micromaster program provides you with a rigorous, advanced, professional, and basic course at the level of AI graduates and their subfields, such as machine learning, neural networks, and more. With a total of 4 courses in this program, review the important concepts of this topic one by one.
Gain a solid foundation for AI guidelines and apply machine learning knowledge to real-world problems and applications. At the same time, you will also learn how to design neural networks and use them to solve problems. After completing the program, you will gain sufficient practical knowledge to expand your portfolio, apply for relevant job profiles or become a freelancer.
· Advanced Machine Learning Specialization – Coursera
This is another extended series of courses that has a very wide network. If you are interested in embracing as many machine learning techniques as possible, this specialization is the key to a balanced and expanded online training program.
The instruction in this course is fantastic: extremely well laid out and concise. Due to its advanced nature, you will need more math than any other courses listed so far. If you have already taken a beginner’s course and mastered linear algebra and calculus, this is a good choice to fill in the rest of your machine learning experience. Much of what is covered in this specialization is key to many machine learning projects.
Free machine learning certifications online Frequently Asked Questions and Answers
Yes, in fact machine learning is one of the most promising career paths that can be achieved. A career involves creating systems that can operate autonomously without being explicitly programmed or under close supervision. As a machine learning expert, you will be introduced to a new world of possibilities. Your experience in this field will always be in demand.
Unlike data science courses, which include topics such as data analysis, statistics, communication, and visualization techniques, machine learning courses focus only on machine learning algorithms, so how they work mathematically and how to use them in a programming language.
If you are looking to apply for a job in machine learning or if you are looking to explore a career in artificial intelligence and machine learning, you can expect an average salary increase of 48% from this course.