Coursera Releases Machine Learning Specialization Course Update

The e-learning platform’s new course teaches the basics of ML with less emphasis on math.

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Online learning platform Coursera recently announced the launch of its new Machine Learning Specialization Classes. This entry-level program teaches the basics of machine learning and how to use these techniques to build real-world AI applications. The class was developed in collaboration between DeepLearning.IA and Stanford University. Taught by AI visionary Andrew Ng, the Machine Learning Specialization course is an updated introductory program, developed from his original Machine Learning course, which has been taken by nearly five million people. people.

Andrew Ng is the founder and CEO of DeepLearning.AI, an educational technology company that enables the global workforce to learn and deploy AI systems. Ng is also a general partner at AI Fund, an adjunct professor in the Department of Computer Science at Stanford University, and president and co-founder of Coursera. He was previously the founding manager of the Google Brain team and chief scientist at Baidu. He has authored or co-authored over 100 research papers on machine learning, robotics, and other AI-related topics.

The updated specialization courses examine advances in machine learning over the decade since Ng created the original course. The Machine Learning specialization comprises three comprehensive modules introducing Machine Learning, Supervised Learning and Unsupervised Learning. Lectures and graded assignments teach Python rather than Octave or MATLAB. Code notebooks and interactive graphics help learners understand the concepts presented in class.

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In the Machine Learning Specialization course, learners will build ML models with NumPy and scikit-learn, develop and train supervised models for prediction and binary classification tasks, build and train a neural network with TensorFlow to perform classification multi-classes, will create and use the decision. trees and tree ensemble methods, apply best practices for machine learning development, and more.

Learners who complete the program will master key concepts and gain practical knowledge that will enable them to quickly apply machine learning to complex real-world problems. The new Machine Learning specialization is the perfect starting point for those looking to get into AI or pursue a career in machine learning.

The Machine Learning Specialization course is expected to take around two months, with a workload of around eight hours per week. Although the course is aimed at beginners, participants will need to understand basic coding and high school level math.

In his announcement videoNg explained that he designed the new program to minimize the amount of math required.

At the end of the program, learners will receive a certificate that they can share with potential employers and professional networks.

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