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Applied AI with DeepLearning, IBM

4.4
256 ratings
44 reviews

About this 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, Applied Artificial Intelligence with DeepLearning, is part of the IBM Advanced Data Science Certificate which IBM is currently creating and gives you easy access to the invaluable insights into Deep Learning models used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines. We’ll learn about the fundamentals of Linear Algebra and Neural Networks. Then we introduce the most popular DeepLearning Frameworks like Keras, TensorFlow, PyTorch, DeepLearning4J and Apache SystemML. Keras and TensorFlow are making up the greatest portion of this course. We learn about Anomaly Detection, Time Series Forecasting, Image Recognition and Natural Language Processing by building up models using Keras one real-life examples from IoT (Internet of Things), Financial Marked Data, Literature or Image Databases. Finally, we learn how to scale those artificial brains using Kubernetes, Apache Spark and GPUs. IMPORTANT: THIS COURSE ALONE IS NOT SUFFICIENT TO OBTAIN THE "IBM Watson IoT Certified Data Scientist certificate". You need to take three other courses where two of them are currently built. The Specialization will be ready late spring, early summer 2018 Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life. If you’re already an expert, this peep under the mental hood will give your ideas for turbocharging successful creation and deployment of DeepLearning models. If you’re struggling, you’ll see a structured treasure trove of practical techniques that walk you through what you need to do to get on track. If you’ve ever wanted to become better at anything, this course will help serve as your guide. Prerequisites: Some coding skills are necessary. Preferably python, but any other programming language will do fine. Also some basic understanding of math (linear algebra) is a plus, but we will cover that part in the first week as well. 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....

Top reviews

By RC

Apr 26, 2018

It was really great learning with coursera and I loved the course. The way faculty teaches here is just awesome as they are very much clear and helped a lot while learning this coursea

By MA

May 20, 2018

This is best course in order to know how machine learning application is scaled on different machines.

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44 Reviews

By Riku Sarlin

Feb 07, 2019

A nice intro to TensorFlow, Keras, SystemML, DL4J and Apache Spark!

By Jorge Abreu Vicente

Feb 05, 2019

Explanations are a bit rush. Would not be easy to follow if I would not have deep previous understanding on the Deeep learning topics.

By Khawar Ashfaq Ahmed

Jan 27, 2019

Great course and superb professor Romeo. !!

By Ray Hermann ANGOSSIO LIWA

Jan 15, 2019

No easy...But was supprise to have got enrolle for the course: Applied AI with DeepLearning

By Matheus Sarafyan

Jan 14, 2019

mais propaganda dos serviços da ibm do que conteúdo... honestamente, eu fiquei mais tempo brigando com a interface do watson pra conseguir executar os notebooks na versão que os caras usam do que programando

By Dmitry Berezhnoy

Jan 11, 2019

This course is packed with info on different deep learning techniques and libraries. Not all of them can be found in exercises though.

By Victor de Oliveira

Jan 09, 2019

I think we need in this module more pratical assignments.

By Saurabh Kumar

Dec 20, 2018

This course is good for people who want to learn ML as a black box, also the scaling part was really rush. I'd advice the constructors to take full sessions for apache spark and DL4J separatly. Overall i enjoyed.

By Azeezur Rahman

Oct 19, 2018

Excellent way of teaching concepts

By RUBEN ADAD

Oct 18, 2018

Uninformative, undidactic, very poorly explained. One of the worst courses I've taken.