Most of the Machine Learning, Deep Learning, Computer Vision, NLP job positions, or in general every Artificial Intelligence (AI) job position requires you to have at least a bachelor's degree in Computer Science, Electrical Engineering, or some similar field. If your degree comes from some of the world's best universities than your chances might be higher in beating the competition on your job interview. But looking realistically, not most of the people can afford to go to the top universities in the world simply because not most of us are geniuses and don't have thousands of dollars, or come from some poor country (like we do). No with the high demand of skilled professionals from these fields, there are exceptions being made, so we can see that people who don't come from these fields, are learning and adjusting themselves in order to get that paycheck. In this article, we are going to list some of the free Artificial Intelligence courses that come from Harvard University, MIT University, and Stanford University that anyone can attend, no matter where they live.
Many programmers are moving towards data science and machine learning hoping for better pay and career opportunities -- and there is a reason for it. The Data scientist has been ranked the number one job on Glassdoor for last a couple of years and the average salary of a data scientist is over $120,000 in the United States according to Indeed. Data science is not only a rewarding career in terms of money but it also provides the opportunity for you to solve some of the world's most interesting problems. IMHO, that's the main motivation many good programmers are moving towards data science, machine learning, and artificial intelligence. If you are in the same boat and thinking about becoming a data scientist in 2019, then you have come to the right place.
If you don't know, Keras is a both powerful and easy-to-use Python library for developing and evaluating deep learning models. It wraps the efficient numerical computation libraries like Theano and TensorFlow and allows you to define and train neural network models in a few short lines of code, which is just awesome. In this course, you will learn how to build an end-to-end Python machine learning project using Keras and tune a deep learning model and neural network. The best part of this course is that n the course, we will walk through every line of code so you'll be able to understand the model and the process.
With strong roots in statistics, Machine Learning is becoming one of the most interesting and fast-paced computer science fields to work in. There's an endless supply of industries and applications machine learning can be applied to to make them more efficient and intelligent. Chat bots, spam filtering, ad serving, search engines, and fraud detection, are among just a few examples of how machine learning models underpin everyday life. Machine learning is what lets us find patterns and create mathematical models for things that would sometimes be impossible for humans to do. Unlike data science courses, which contain topics like exploratory data analysis, statistics, communication, and visualization techniques, machine learning courses focus on teaching only the machine learning algorithms, how they work mathematically, and how to utilize them in a programming language.