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Voltar para Applied AI with DeepLearning

Comentários e feedback de alunos de Applied AI with DeepLearning da instituição IBM

4.4
530 classificações
80 avaliações

Sobre o curso

>>> 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 on 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....

Melhores avaliações

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

BS

Aug 08, 2019

Gave a good hands-on with IBM Watson studio notebooks. Also a good overview of LSTM's, Keras, Predictive maintenance. Good stuff, keep it going

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51 — 75 de {totalReviews} Avaliações para o Applied AI with DeepLearning

por Ted H

Oct 14, 2019

I can't believe how much progress has been made with Neural Networks since I studied them at school!

por MD S U

Oct 14, 2019

A great course about Deep learning with AI.

por PV R K

Oct 18, 2019

excellent course

por Victor d O

Jan 09, 2019

I think we need in this module more pratical assignments.

por Dmitry B

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.

por Dmitry G

Jul 19, 2018

Concise intro to much needed big data machine learning solutions

por Tobias H

Aug 26, 2018

n/a

por Andrey O

Sep 07, 2018

Part with DeepLearning4J is not very good...

por Saurabh W

Mar 12, 2018

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

por Naveen M N S

Feb 18, 2018

Very hands-on course. Enjoyed the width of problems that were solved. IBM cloud seems irresistible. Certain sections of the course are too fast. For such sections it will be better if the notebook links are provided in the video/description itself.

por PRASHANT K R

Jun 07, 2018

very nice course it gives more insight to deep learning.

por Arati Y

Apr 09, 2018

It was nice

por Valerio N

Mar 27, 2019

Very Complete course.

por Sourastra N

Jul 26, 2019

The course needs to allow the students to build their own model.

por Vinayak B

Jul 30, 2019

Really Helpful course for AI Enthusiasts

por Jair M

May 22, 2019

Some videos are missing, but anyway is a great course

por Filip G

Oct 09, 2019

Nice course with lots of practical examples. Course is delivered by multiple tutors with different styles and level of detail. Overall good introductory course into neural networks, scaling and deployment.

por Daniel P

Jul 10, 2018

Too much focus on IBM platform, good overview on Keras/SystemML/DL4J though, some presentations could have been better prepared and implemented. Overall an average Coursera course and not a particularly great experience to work through the material.

por Jeet D

May 12, 2018

The course is very resource heavy, i.e. it has great intuitive resources, but the learning experience was very poor. Some of the instructors were very sparse with the material contents, some just brushed over the contents without much explanation and.

The quality of the course has to be improved.

por Jose L M G

Apr 01, 2019

Lo hago, el curso es muy bueno en cuanto al uso de la plataforma watson, pero falla en explicar los fundamentos principales con animaciones, ejemplo, el curso de pytorch de udacity enseña eso muy bien. En lo demas esta bien, pero al no contar con elementos visuales de ayuda en laclase de LSTM se hace tediosa.

por Jorge A V

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.

por Leonardo I

Aug 28, 2019

The course is delivered at a very high level of abstraction. If you are a beginner, I wouldn't recommend this course as the explanations provided are quite vague and not so good in many instances. Justifications for the use of quite a couple of algorithms/values are not provided thus leaving the learner with a lot of "Why's"

One of the nice things about the course is that the instructor responds promptly to students' queries.

por Sheen D

Sep 01, 2019

Again, the instructor speaks way too fast to explain anything. Even the subtitle cannot follow the instructor line by line. Frequent occurrence of inaudible words or sentence or wrong translations. When it comes to the code, never really understood what each line of codes is for...

por Csaba P O

Oct 01, 2019

I liked the general idea of this course, but the actual material is not as good as it could be. There are lots of inaccuracies in the material (like annoying typos and not working code examples) which should be corrected before you sell this course on Coursera.

I strongly suggest that you go through your material with someone who has pedagogy knowledge and who can assist you to improve the didactic aspects of your material.

I did this course (and the whole specialization) for the practical examples as I feel rather confident with the theoretical aspects of machine learning, but I wanted to learn how to do these things in Spark environment. At the end of the day I have got what I wanted (more or less, as the NLP part was really lousy), but if I would not have strong experience with the field, I would have been surely lost. Honestly, I would have a hard time to recommend these courses for someone who wants to learn about machine learning and not about how to do machine learning with Keras, etc. And I am sorry to say that, because, again, I liked the team, the attitude, and the technical aspects of this course.

por Serdar M

Mar 22, 2019

materials offered are not enough, and it is confusing.