Romeo Kienzler
>>> 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. …
Instructor Details
Courses : 5
Specification: Applied AI with DeepLearning
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56 reviews for Applied AI with DeepLearning
Add a review
| Price | Free |
|---|---|
| Provider | |
| Duration | 17 hours |
| Year | 2018 |
| Level | Expert |
| Language | English |
| Certificate | Yes |
| Quizzes | Yes |
Waleed M S A A A G –
good
Ramachandra R K –
Great course with several hands on assignments. Highly recommend.
Fernando C –
The course is great!
Serdar M –
materials offered are not enough, and it is confusing.
Valerio N –
Very Complete course.
Amin s –
even after getting financial aid i am not able to upload my submissions.
Jose L M G –
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 ensena eso muy bien. En lo demas esta bien, pero al no contar con elementos visuales de ayuda en laclase de LSTM se hace tediosa.
Quang N L –
This is an excellent course in teaching me not only the deep learning principles but also practical usecases and various frameworks.
Nikolas R –
The course covers a broad range of tools to deploy deep learning algorithms.
Jair M –
Some videos are missing, but anyway is a great course
Saumya T –
Very good course for learning Neural Network. Well explained!!!
FREDDY Y –
great course
Evan S –
I learned a lot about neural networks and the infrastructure they run on. I enjoyed the course very much.
David J D T –
Would love to have a deeper lecture on NLP inside Watson
Neeraj k –
best method for understanding
Francisco J G L –
Very bad course
Chiara P M –
poor expalined. Too many things threw there without proper explanation. Poor exercise with the notebooks. Better less things with higher focus
Kylie T –
Very well organized course
Ashish P –
This is really Amazing Course. I learn those micro things which is people rarely understand.
Sourastra N –
The course needs to allow the students to build their own model.
Vinayak B –
Really Helpful course for AI Enthusiasts
Varadharajan R –
Self motivated to learn and do the assignments all the discussions in the forum guided me thoroughly
Bharath S –
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
Egemen I –
This course and the knowledge it provided were incredibly helpful. Thank you IBM and thank you Coursera!
Leonardo I –
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.
Sheen D –
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…
Reynier H –
Curso bem completo e bem explicado!
Felipe M M –
Videos are old. It feels like he had a bunch of material and put them together to create this course. For example: There are assignments that they give you the answer because the questions are not supposed to be there. He doesnt teach, instead, he reads a script. The assignments are not challenging and you dont feel like you learned. Horrible and painful.
SHIVANI Y –
ossum
Julien P –
Very nice and complete.
Csaba P O –
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.
Filip G –
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.
MD S U –
A great course about Deep learning with AI.
Ted H –
I can’t believe how much progress has been made with Neural Networks since I studied them at school!
PV R K –
excellent course
Gustavo H M d C –
Very good!!!
Muyanja S Z –
ThIs is an in depth course which while taxing has immense rewards for those who keep the faith and patience to go all the way!
Francesco d C –
The lessons provided by Skymind were very poor.
Naveen R –
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..!!
Pierre–Matthieu P –
I was pretty disppointed overall. Pros : we see many types of tools and get to use some of them in the programming assignments. I feel like I now have a general knowledge of the field. I particularly liked the aspects of scaling and deploying models in production. Cons : This honestly feels more like a rough draft than a finished and polished course. I would have liked a consolidated overview of all these tools, their pros and cons, etc. Some tools and techniques were explained in literaly 15 min(!) and in some cases simply walked through a tutorial from the tool’s website (!!). A programming assignment was broken through not being updated for more recent spark versions. Some videos mentioned a non existent programming assignment (I assume they were reused from an internal IBM training session), etc. The comparison with say Andrew Ng’s course on ML is cruel.
Pierre Matthieu P –
I was pretty disppointed overall. Pros : we see many types of tools and get to use some of them in the programming assignments. I feel like I now have a general knowledge of the field. I particularly liked the aspects of scaling and deploying models in production. Cons : This honestly feels more like a rough draft than a finished and polished course. I would have liked a consolidated overview of all these tools, their pros and cons, etc. Some tools and techniques were explained in literaly 15 min(!) and in some cases simply walked through a tutorial from the tool’s website (!!). A programming assignment was broken through not being updated for more recent spark versions. Some videos mentioned a non existent programming assignment (I assume they were reused from an internal IBM training session), etc. The comparison with say Andrew Ng’s course on ML is cruel.
Prithvi S –
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.
Madan K –
Excellent Course
Abdelfettah H –
it was really helpful, thank you so much.
Raja s v –
Not for learning only for reference
Carlos F C d S e S –
It is an amazing course!
Amalka W –
Course covers scalerble deep learning concepts
Giovani F M –
I’ve learned a lot from this course. I’ve very much the Time Series Forecasting Section Explanation. The notebook is detailed and the concepts very well discussed.
Ngoc T L –
Wonderful course with hands on tutorials.
SRAVANKUMAR E –
good course
Armen M –
Interesting course with bad explanation. To many topics and to poor explanation
Thomas B –
This is a good course with good introductory material that covers a broad range of topics.
HAMM,CHRISTOPHER A –
No pedagogy. No instruction, mostly copy and paste and guess.
Daniel G S –
Good course. I think practice exercises should be a little bit more challengengin. But they are fine for learning the basics of the topics that are taugh.
Jakob S –
The course covers some very interesting and important concepts, however on a very low level. The reason for this might simply be the lack of time; one cannot properly cover methods for AI image processing, NLP, etc. in such limited space. I also had mixed feelings about the exercises: It is very nice to see applications of the tools discussed in the lectures, but unfortunately the exercises are so simple that they can be easily finished without really understanding the code.
KVD S –
good