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Avis et commentaires pour d'étudiants pour Applied AI with DeepLearning par IBM

994 évaluations
170 avis

À propos du cours

>>> 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

Meilleurs avis

23 oct. 2020

I learned many things from this course. However, I think in some points it could have been instructed much better. But all in all, it is a very worthy course for the price offered. Thanks a lot!

25 avr. 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

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1 - 25 sur 171 Avis pour Applied AI with DeepLearning


18 oct. 2018

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

par Muhammad

24 mars 2018

I am sorry to say, but this by far the most unimpressive course I have taken at coursera. If I just wanted someone to go through a jupyter notebook, without caring to explain much, why do I need to take a course. Compared to other excellent courses I have taken/audited at coursera, I would rate this as sub par. Worst part about this was, it sounded very incoherent. Seems like no body actually verified the content and assignments to actually make sure they are consistent.

par sada n

20 août 2018

No clarity in lectures. IBM platform set up is too complicated and confusing.

par Bayram

18 avr. 2020

I respect the knowledge the Instructors have. But knowing something doesn't necessarily mean that you're good at teaching it. There are some instructors in this course who fits into this category. And honestly, I care more about the way I'm being thought. Therefore I gave only 2 stars.

par Armen M

15 févr. 2020

Interesting course with bad explanation. To many topics and to poor explanation

par Raja s v

21 déc. 2019

Not for learning only for reference

par Matheus S

14 janv. 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

par Rohan C K

14 juin 2020

The course was amazing however I'm yet to receive my badge from IBM even after completing the course. Would really appreciate if Coursera support could assist me with this.

par Edoardo B

22 août 2018

I like very much the architecture-based approach of these courses/ specialization.

At the end, the goal of an Enterprise, in a general sense, is to satisfy the local or global community necessity in an effective and efficient way. Surreally with the choose of the correct technology, frameworks, languages, instructions, details.... but , at the end, what is really important is the value offered.

That said, I think, that this specialization, provides the mindset, the knowledge, the skills and tools applicable in a corporate environment. Technology is important, yes, but, from my point of view, it is most important to consider the value that is emerging from the holistic approach of all the topics in the different modules of the courses, including also the final capstone project.

Thank you very much Romeo and all instructors for this continuous learning professional opportunity

par Saurabh K

20 déc. 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.

par Merem Y

10 mai 2018

Could not do assignments because the IBM Cloud was terribly shlow or crashed. Eventually it did load but i had to find out that my old IBM Cloud account had expired and could not be moved to the new free and unlimed offer. I need to open a new account with a different e-mail account ... Are you kidding? I'm not sure if the crashes were related to this problem but all in all this was an experience that convinced me to stay clear of the IBM cloud.

Content-wise i only did a quick scan over the material and it look like they try to do to much in to little time without any real explanations. Focus is on IBM products. If you want to learn AI, ML or DL, stay with the courses from Andrew Ng, Geoffrey Hinton, Stanford or Berley lectures on YouTube, etc. There are many free high class resources out there. This course is only useful for people that have to use IBM products.

par Adam K

29 juil. 2020

Pretty disappointed.

A lot of the course is in python 2, assignments are not engaging and very easy. I would like to learn the latest technologies and get much more practice.

par Bryon B

3 mai 2018

Module sequence could have been better sequenced...

Also, when trying to troubleshoot a system error, the support of the forum was significantly lacking... I was unable to finish all but one assignments because my program just kept running... no errors.... I received no help on this...

There were several assessments that did not pertain to what the preceding content covered .

Poor andragogical approach. Some of the lectures were actually not made for this course... The course should be revised!

The certification requires additional modules that have not yet been deployed as well. This course is simply not ready.

par Nuwan A

11 mai 2020

I gained much knowledge about developing, and applying machine learning techniques to real world applications and also now I have a deep knowledge about the tools and techniques which I use when it comes to develop real world machine learning models, specially which platforms to use for a pain free development and testing, deploying models and what are the future work need to do in order to increase the knowledge. I was a newbie to machine learning when I was starting the course, but now I have a much better understand about developing real world applications. Thankyou very much coursera and all the instructors for this amazing course.


3 juin 2018

Overall very good course with experienced instructors and a main instructor whose enthusiasm is communicative. I have two modest improvement proposals. The oil price prediction assignment could be converted in an anomaly analysis - possibly in a Pytorch setting to deepen the initial presentation of Pytorch -, perhaps a more meaningful use of deep-learning to this time series data. Week 4 is a touch light compared to weeks 2 and 3 and could be improved by an assigment illustrating feedback between the anomaly signals in the IOT framework of week 3 and the IOT setup itself. Both anomaly and feedback would be deep-learning based.

par Rahul G

12 juin 2020

Received insights into Deep Learning models in Natural Language Processing, Computer Vision, Time Series Analysis, Neural Networks and LSTM. Learned popular DeepLearning Frameworks like Keras, TensorFlow, PyTorch, DeepLearning4J and Apache SystemML and TensorFlow. Learned 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, learned how to scale those artificial brains using Kubernetes, Apache Spark and GPUs.

par Reetu

25 avr. 2018

Very intuitive course, helped me learn at my own pace, given that I was not having time at a stretch. I thoroughly enjoyed learning the concept and techniques of deep learning. Some of the exams were easy but the objective was that you continue learning, whille some were tough (where I learned the most). It was overwhelming to see real IoT data flowing through and reaching to my code :). Nice!!

It looks easy but simple things are "very" hard to produce so Thanks to the whole Team.

par Frakc S

21 mars 2018

Good rich examples, but videos are hard to understand. Some instructors talk to fast even on 0.75 video speed, other talk to slow and due to accent subtitles full of *INAUDIBLE* parts. Also it will be good if instructors will pay more attention when replying on forums. When i receive exactly same solution which i tried and it did not work, i left pretty confused

par Rudolf P

24 févr. 2018

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.

par N.Srinivas

16 nov. 2020

I found this course to be an excellent introduction to Deep Learning Frameworks. The fact that we cover images, NLP, digital signal processing gives us immense exposure to wide applications of Tensorflow. Many thanks to the Content Creators to putting together this great coursework!

par Naveen R

25 nov. 2019

The course content was very informative and very well structured. Instructors have shown their expertise while explaining the concepts and were able to connect with the learner. This helped me to complete my assignments with hands-on. Good course to sharpen your knowledge..!!

par Nigel S

19 janv. 2021

This course is definitely designed for those who already have a background in machine learning, so it's great for fine-tuning techniques and learning more about how the models work, but it's not so great if you are wanting to learn the models for the first time.

par Youdinghuan C

12 juin 2020

Following the Advanced ML (course 2), this course does an excellent job in introducing key deep learning concepts, especially LSTM. The programming assignments are rather easy & approachable. The quiz questions are pretty challenging but interesting to solve.

par 吴怡

20 août 2019

Wow, What a great course! This course really helps me understand the machine learning basis as well as the practical deployment in multiple environments and programming languages. Thanks for the lecturers and also Coursera!

par Prithvi S

7 déc. 2019

Great Course. Just a point I would like to get in your notice, the course shows completion immediately after the submission of Apache SystemML assignment. There are still few lectures and one quiz after that.