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6 Best Online Machine Learning Engineering Courses & Classes of 2020

Machine Learning Engineering Courses

It is incredibly difficult to meet the requirements for students with so many Machine Learning Engineering courses. Learners often ask if each scenario has a course in Machine Learning Engineering. The answer is YES. Below you can find popular courses. Registration for the correct course is an important element in your career development. In this article, experts selected the best courses in Machine Learning Engineering in 2020.

Highlighting the best-known courses in all categories is the main objective.

Based on your preferences, select one that best suits your needs. But let us look at the best courses on the market for Machine Learning Engineering.

1. Become a Machine Learning Engineer (Coursera)

Duration: Self-paced

Rating: 4.5 out of 5

This complete Machine Learning Tutorial facilitates the collection of several courses related to Machine Learning, organized step by step to make you a pro from a beginner. You can enroll whether you have almost no experience. These classes are divided into 4 categories: the prerequisite, the beginner, the Intermediate and the advanced parts. Every section consists of several mini-courses, which can be followed by your level of ability.

Key Highlights:

  • Practice advanced machine learning, network analysis, text mining, deep learning, cloud integration and system recommendation.
  • You can learn how to create applications powered by data and neural networks.
  • You can browse contents on mobile and PC course at your own speed.
  • You can begin from any point, follow the simple structured way, customize and monitor your learning plan.
  • Get a certificate of completion on your CV or LinkedIn profile.
  • Work on practical projects that are ready for work. Take part in the global peer forums to clarify your doubts.

You can Sign up Here

2. Machine Learning Course by Stanford University (Coursera)

Duration: Self-paced

Rating: 4.9 out of 5

Coursera offers this Stanford University Machine Learning tutorial. The speaker, Andrew Ng, is an associate professor at Stanford University and also the co-founder of Coursera. Andrew teaches Machine Learning, Statistical Pattern Recognition and Data Analysis in this course. As a result of enrolment in this course, you will understand the practical methods of machine learning and how to use them to do things. The course provides not only a theoretical overview but also helps you learn through practices.

Key Highlights:

  • Learn the Linear Regression, its implementations and the method of learning Gradient Descent.
  • Find the best machine learning innovations and practices in Silicon Valley.
  • This courses will allow you to apply your algorithm learning to build smart robots following several case studies and implementations.
  • This course offers 56 hours of English video lessons and a certificate of completion given at the end of the course.
  • Learn Linear Algebra, Logistic Regression, Regularization, Neural Networks, Machine Learning System Design, Unsupervised Learning, Reduction in the Dimensionality, Anomaly Detection, Recommender Systems, etc.

You can Sign up Here

3. Machine Learning (Stanford Online)

Duration: Self-paced

Rating: 4.5 out of 5

Artificial intelligence is digital technology future. And Stanford stands high in engineering research with high-end research. The Stanford School of Engineering’s on-line machine learning curriculum teaches you the fundamentals of artificial intelligence , machine learning and data science. The instructors in this program are industry leaders with huge experience in communicating sophisticated software concepts efficiently. The registration option opens every quarter and the application for the Non-Degree Option must be completed for registration. If you are a computer science student, it would be best to participate in this course. It is also essential to have basic programming knowledge in Java , Python and C++. For software developers, mathematicians, Statistics experts, data miners, market analysts and other related professionals, this course is advantageous.

Key HIghlights:

  • Explore useful data science and machine learning applications for designing and developing machine algorithms.
  • Discover the basics of supervised learning, Unsupervised learning, deep learning, Reinforcement learning.
  • Learn about creating autonomous navigation computer systems, data mining, probabilistic artificial intelligence models, the representation of knowledge, robotic control and other exciting tools.
  • Learn how to quickly extract information from massive databases such as online document repositories, social network graphs, major websites, etc.

You can Sign up Here

4. Machine Learning Engineering Courses (edX)

Duration: Self-paced

Rating: 4.5 out of 5

edX offers a variety of exclusive training courses on machine learning and artificial intelligence. In this list of Machine Learning courses compiled by edX experts, real university courses from MIT, Harvard, Microsoft, IBM, Caltech, Columbia and other leading universities are included. All such courses are thoughtfully intended to give you the necessary skills to undertake a highly profitable technical career. Whether you are a machine learning student or want to develop your engineering skills to a new level, edX offers courses to meet all your requirements. You will also be able to try a path before you pay for it.

Key Highlights:

  • Get acquainted with the concepts of computer science, Python, artificial intelligence, data analytics, data structure, automotive technology, linguistic analysis, reinforcement, speech recognition, etc.
  • Practice basic data science like machine learning and R with real-world case studies and practical machine learning.
  • Learn to design and develop smart agents that use Artificial Intelligence to solve complex problems.
  • Learn how to use applications for machine learning, its tools, techniques, and how to publish a report after project completion.
  • You can use the contents of the course as you please.
  • Learn to program robots to conduct physical tasks in real-time.

You can Sign up Here

5. Professional Certificate Program in Machine Learning (MIT Professional Education)

Duration: 5-day

Rating: 4.5 out of 5

MIt is Professional Education division offers a comprehensive Professional Certificate Program in Machine Learning and Artificial Intelligence. The introduction of machine learning created an entirely new category of job opportunities. MIT has always been the pioneer of machine learning and artificial intelligence. This class is here to help you increase your understanding of deep learning, prescriptive analytics, natural language processing, and many more, if you want to be an active player in this evolving industry. In order to enter this programme, you need a bachelor’s degree in any professional area and a minimum of three years’ professional profile work experience.

Key Highlights:

  • This is an on-site training course on MIT campus. In addition to the core courses, you have the option of choosing from the optional courses.
  • There are two main courses you need to take, one for Big Data Machine Learning and Text Processing Foundations, and the other for Big Data Machine Learning and Advanced Text Processing.
  • Get a worldwide accredited MIT professional certificate and get opportunities to network with MIT alumni.
  • Learn to implement advanced technology and industry-specific know-how to develop efficient AI systems.

You can Sign up Here

6. Become a Machine Learning Engineer (Udacity)

Duration: 3 months

Rating: 4.6 out of 5

This Udacity Nanodegree Program teaches you advanced machine learning algorithms that help you become a professional machine learning engineer. This course allows you to learn the best techniques, such as packaging and deploying your creations in a production environment. The instructors are very competent experts in machine learning. The pre-requisites for admission are the intermediate knowledge of machine learning algorithms like deep learning, supervised and Unsupervised models, Python programming knowledge and a minimum of 40 hours of programming experience.

Key Highlights:

  • You will receive advice on preparing for interviews, technical coaching sessions and revisions to sharpen your career path.
  • You will be able to work on realistic projects with leading experts in the industry to develop your professional skills.
  • Get your mentors and the global learning community resource suggestions and constructive feedback.
  • You will receive one-on-one coaching from a professional mentor to answer your questions, clarify your concerns and keep you on track.
  • If you spend 10 hours a week studying, the length of the course is three months. But you can pick those 10 hours as scheduled.

You can Sign up Here

Wrapping Up

This is the list of the 6 Best Online Machine Learning Engineering Courses & Classes of 2020. They are popular and loved by many experienced Machine Learning Engineers. You will find between these courses what you need to learn in order to continue your Machine Learning journey.

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