Save for later

Applied AI with DeepLearning

This course is part of a Specialization (series of courses) called Advanced Data Science with IBM.

>>> 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.

Get Details and Enroll Now

OpenCourser is an affiliate partner of Coursera.

Get a Reminder

Not ready to enroll yet? We'll send you an email reminder for this course

Send to:

Coursera

&

IBM

Rating 4.0 based on 22 ratings
Length 5 weeks
Effort 4 weeks of study, 4-6 hours/week
Starts Jan 14 (last week)
Cost $79
From IBM via Coursera
Instructors Romeo Kienzler, Max Pumperla, Ilja Rasin, Niketan Pansare, Tom Hanlon
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Programming IT & Networking
Tags Data Science Machine Learning Cloud Computing Information Technology

Get a Reminder

Get an email reminder about this course

Send to:

What people are saying

We analyzed reviews for this course to surface learners' thoughts about it

deep learning in 3 reviews

I thoroughly enjoyed learning the concept and techniques of deep learning.

One of the great course from IBM Watson .Really one should take this one if intrested in Deep Learning.

This course provides deep insights, explanations and examples on how to apply deep learning networks to machine learning problems.

The course level is intermediate - you will need some basic knowledge on deep learning and some programming skills in order to get most out of this course.

Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

Adjunct Professor, Time Series Econometrics $36k

Professor (adjunct series) $37k

Assistant Editor for RFC Series $58k

Traffic Studies Specialist Series $64k

Senior Series Editor $67k

Junior Series Producer, Music Choice Concert Series $71k

Series Editor $84k

Spark series editor $87k

Manager, Series Marketing $88k

Senior Editor for RFC Series $102k

3000 Series Team Leader $111k

Assistant Professor (adjunct series) $162k

Write a review

Your opinion matters. Tell us what you think.

Coursera

&

IBM

Rating 4.0 based on 22 ratings
Length 5 weeks
Effort 4 weeks of study, 4-6 hours/week
Starts Jan 14 (last week)
Cost $79
From IBM via Coursera
Instructors Romeo Kienzler, Max Pumperla, Ilja Rasin, Niketan Pansare, Tom Hanlon
Download Videos On all desktop and mobile devices
Language English
Subjects Data Science Programming IT & Networking
Tags Data Science Machine Learning Cloud Computing Information Technology