Coursera releases updated Machine Learning Specialization course

The web studying platform’s new course teaches the basics of ML with much less emphasis on math.

On-line studying platform Coursera lately introduced the launch of its new Machine Studying Specialization course. This beginner-level program teaches the basics of machine studying and find out how to use these methods to construct real-world AI functions. The category was developed as a collaboration between DeepLearning.AI and Stanford College. Taught by AI visionary Andrew Ng, the Machine Studying Specialization course is an up to date introductory program, expanded from his authentic Machine Studying course, which was taken by almost 5 million individuals.

Andrew Ng is the founder and CEO of DeepLearning.AI, an training expertise firm that allows the worldwide workforce to study and deploy AI methods. Ng can be basic accomplice at AI Fund, an adjunct professor at Stanford College’s Pc Science Division, and chairman and co-founder of Coursera. He was beforehand the founding lead of the Google Mind group and chief scientist at Baidu. He’s the writer or co-author of over 100 analysis papers on machine studying, robotics and different AI-related topics.

The up to date Specialization programs examines advances in machine studying in the course of the decade since Ng created the unique course. Machine Studying Specialization includes three complete modules introducing machine studying, supervised studying and unsupervised studying. Lectures and graded assignments educate Python reasonably than Octave or MATLAB. Code notebooks and interactive graphs help learners in understanding the ideas offered within the class.

SEE: Synthetic Intelligence Ethics Coverage (TechRepublic Premium)

Within the Machine Studying Specialization course, learners will construct ML fashions with NumPy and scikit-learn, develop and practice supervised fashions for prediction and binary classification duties, construct and practice a neural community with TensorFlow to carry out multi-class classification, construct and use choice timber and tree ensemble strategies, apply finest practices for machine studying improvement and extra.

Learners who full this system will grasp key ideas and achieve sensible information that may permit them to use machine studying quickly to difficult real-world issues. The brand new Machine Studying Specialization is the perfect beginning place for individuals who want to break into AI or construct a profession in machine studying.

The Machine Studying Specialization course ought to take roughly two months to finish, with a workload of about eight hours per week. Whereas the course is geared towards newcomers, members might want to perceive primary coding and excessive school-level math.

In his announcement video, Ng defined that he designed the brand new program to attenuate the quantity of math mandatory.

Upon completion of this system, learners will obtain a certificates that they will share with potential employers {and professional} networks.