AI and machine learning models are thriving in the global tech market with their smart capabilities for a diverse range of industries. The educational industry has started harnessing AI and machine learning models as well as providing online courses with certificates. There are multiple machine learning online courses available on the internet for interested students and working professionals to brush up on the skills. It is gaining a wide array of recognition across the world besides the traditional five engineering courses. Let's explore some of the top machine learning online courses available for aspiring machine learning engineers, machine learning instructors, applied scientists in machine learning, machine learning researchers, machine learning consultants, and many more.
Machine Learning from Coursera is one of the top machine learning online courses available in recent times. It provides a broad introduction to machine learning specialization, AI, data mining, also statistical pattern recognition. This curriculum includes supervised learning, unsupervised learning, and the best practices in machine learning with the implementation of AI. There are multiple case studies and applications to build robots, computer vision, text understanding, and other fields. Flexible deadlines are available for interested candidates as per their schedule in 100% online mode. It will take almost 61 hours to complete the machine learning course from Coursera that covers linear regression with one variable, linear algebra review, linear regression with multiple variables, Octave or Matlab training, logistic regression, and regularization. The top instructor is Andrew Ng and the course is offered by Stanford University.
Machine Learning A-Z: Hands-on Python & R In Data Science from Udemy helps candidates to learn to create machine learning algorithms in Python and R from two Data Science experts. The course will help in having a great intuition of multiple machine learning models, strong analysis, building robust models. Manage reinforcement learning, NLP, dimensionality reduction, and many more. The curriculum contains 45 sections with 320 lectures and 73 articles for almost 45 hours. There are ten parts such as data processing, regression, K-NN, SVM, clustering, association rule learning, reinforcement learning, NLP, deep learning with AI, parameter tuning, and lots more. There are practical exercises with real-life problems and Python and R code templates for easy download.
AWS Certified Machine Learning Speciality course from Udemy provides a hands-on AWS SageMaker course with practice tests. Candidates will know how to train, optimize, deploy, and integrate machine learning in AWS Cloud, and ready-to-use AI capabilities in 28 sections with 240 lectures and 92 articles for 17.5 hours. This machine learning specialization course includes machine learning concepts, model performance evaluation, SageMaker housekeeping, SageMaker service overview, XGBoost, emerging AI trends, and many more.
Machine Learning Crash Course from Google is one of the top online courses at present that covers a practical introduction to machine learning. It is a self-study guide with a series of lessons through video lectures, real-world case studies, and practical exercises. This machine learning online course includes more than 30 exercises and 35 lessons in 15 hours. There are three steps to complete before joining this crash course— one-hour self-study course known as introduction to machine learning problem framing, the NumPy ultraquick tutorial collab exercise, and the pandas ultraquick tutorial collab exercise for a better understanding.
Machine Learning Certification Course from Simplilearn provides an exciting branch of AI with 58 hours of applied learning, interactive labs, 4 practical projects— Uber, Amazon, Mercedes-Benz as well as of IDB, over 25 exercises, and mentoring. This machine learning specialization course will help me to become a successful machine learning engineer in the nearby future. The curriculum includes working with real-time data, creating algorithms with supervised and unsupervised learning, regression, and many more. There are three options for interested candidates— self-paced learning, online Bootcamp, and corporate training.
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