Advanced Machine Learning and Signal Processing course

 

Advanced Machine Learning and Signal Processing

coursera.org/learn/advanced-machine-learning-signal-processing

Advanced Machine Learning and Signal Processing

 About  Course

By enrolling in this course you agree to the End User License Agreement as set out in the FAQ. Once enrolled you can access the license in the Resources area. 

This course, Advanced Machine Learning and Signal Processing, is part of the IBM Advanced Data Science Specialization which IBM is currently creating and gives you easy access to the invaluable insights into Supervised and Unsupervised Machine Learning Models used by experts in many field relevant disciplines. 

We’ll learn about the fundamentals of Linear Algebra to understand how machine learning modes work. 

Then we introduce the most popular Machine Learning Frameworks for python Scikit-Learn and SparkML. SparkML is making up the greatest portion of this course since scalability is key to address performance bottlenecks. 

We learn how to tune the models in parallel by evaluating hundreds of different parameter-combinations in parallel. 

We’ll continuously use a real-life example from IoT (Internet of Things), for exemplifying the different algorithms. 

For passing the course you are even required to create your own vibration sensor data using the accelerometer sensors in your smartphone. So you are actually working on a self-created, real dataset throughout the course. 

If you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging.

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What is  IBM

IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. 

Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. 

IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. 

Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.

This course is scheduled in 4 Weeks.

WEEK 1 -- 6 hours to complete

Setting the stage -- 10 videos (Total 59 min), 2 readings, 3 quizzes

WEEK 2 --  10 hours to complete

Supervised Machine Learning -- 26 videos (Total 131 min), 1 reading, 10 quizzes

WEEK 3  -- 5 hours to complete

Unsupervised Machine Learning -- 13 videos (Total 67 min), 1 reading, 3 quizzes

WEEK 4 -- 6 hours to complete

Digital Signal Processing in Machine Learning -- 13 videos (Total 108 min)

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This Course Plus the Full Specialization

Shareable Certificates

Self-Paced Learning Option

Course Videos & Readings

Practice Quizzes

Graded Assignments with Peer Feedback

Graded Quizzes with Feedback

Graded Programming Assignments

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