23 окт. 2020 г.
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 апр. 2018 г.
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
автор: RUBEN A•
18 окт. 2018 г.
Uninformative, undidactic, very poorly explained. One of the worst courses I've taken.
24 мар. 2018 г.
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.
автор: sada n•
20 авг. 2018 г.
No clarity in lectures. IBM platform set up is too complicated and confusing.
18 апр. 2020 г.
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.
автор: Armen M•
15 февр. 2020 г.
Interesting course with bad explanation. To many topics and to poor explanation
автор: Raja s v•
21 дек. 2019 г.
Not for learning only for reference
автор: Matheus S•
14 янв. 2019 г.
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
автор: Rohan C K•
14 июня 2020 г.
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.
автор: Adam K•
29 июля 2020 г.
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.
автор: edoardo b•
22 авг. 2018 г.
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
автор: Saurabh K•
20 дек. 2018 г.
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.
автор: Merem Y•
10 мая 2018 г.
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.
автор: Bryon B•
3 мая 2018 г.
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.
автор: Nuwan A•
11 мая 2020 г.
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.
автор: FRANCOIS K•
3 июня 2018 г.
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.
автор: Rahul G•
12 июня 2020 г.
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.
25 апр. 2018 г.
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.
автор: SHEILA D D S•
15 мар. 2022 г.
Chamou a atenção o nível de profundidade com que o professor Romeo abordou cada variável, função, e saída de código com o seu porquê, histórico e contextualização. foi muito valioso, principalmente quando se trata de ensino on line.
Apesar da explicação sobre as bibliotecas utilizadas serem explicadas meticulosamente, o nível de conhecimento prévio sobre lógica de programação e álgebra linear é avançado, principalmente para quem tem o perfil autodidata.
автор: Frakc S•
21 мар. 2018 г.
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
автор: Rudolf P•
24 февр. 2018 г.
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.
16 нояб. 2020 г.
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!
автор: Naveen R•
25 нояб. 2019 г.
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..!!
автор: Nigel S•
19 янв. 2021 г.
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.
автор: Youdinghuan C•
12 июня 2020 г.
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.
20 авг. 2019 г.
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!