Master machine learning concepts and techniques including supervised and unsupervised learning, mathematical and heuristic aspects, and hands-on modeling to develop algorithms to prepare you for the role of Machine Learning Engineer.
This Machine Learning online course prepares engineers, data scientists and other professionals with knowledge and hands-on skills required for certification and job competency in machine learning. The demand for machine learning skills is growing quickly. The median salary of a Machine Learning Engineer is $134,293 (USD), according to payscale.com.
By the end of this Machine Learning course, you will be able to accomplish the following:
- Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling.
- Gain practical mastery over principles, algorithms, and applications of machine learning through a hands-on approach which includes working on 28 projects and one capstone project.
- Acquire thorough knowledge of the mathematical and heuristic aspects of machine learning.
- Understand the concepts and operation of support vector machines, kernel SVM, naive bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more.
- Comprehend the theoretical concepts and how they relate to the practical aspects of machine learning.
- Be able to model a wide variety of robust machine learning algorithms including deep learning, clustering, and recommendation systems