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If you love Andrew Ng's first Coursera course on machine learning as much as I do, you were equally hyped when you heard that deeplearning.ai Since everybody's on a tight schedule, let's try the impossible and finish a course that is laid out to last one month in one week. Let's not rush through though, but actually understand the material. And of course, we'll do it while continuing our 40h/week job. What are the advantages of finishing the course quickly you ask?
Serengil received his MSc in Computer Science from Galatasaray University in 2011. He has been working as a software developer for a fintech company since 2010. Currently, he is a member of AI and Machine Learning team as a Data Scientist. His current research interests are Machine Learning and Cryptography. He has published several research papers about these motivations.
Fast forward to 2017 I have spent 100's of hours working on Deep learning projects and the technology has become more and more accessible due to several advancements in software(ease of usage -- Keras, PyTorch), hardware(GPU becoming commercially viable for someone like me sitting in India -Not still cheap), availability of data, good books and MOOCS. After completing the 3 most popular MOOCS in deep learning from Fast.ai, deeplearning.ai/Coursera In this post I talk about 5 aspects of each course which will help you decide. I came across this course when reading an article in kddnudgets . For the first time I heard about Jeremy Howard, searched about him in Wikipedia and was impressed .
I hope you will take the best advantage of this course with the given url. This is a streamlined course to take you from knowing nothing about CATIA V5 to give you all the knowledge and skills needed to become a certified CATIA Associate. This course should enable you to, with confidence, use CATIA to design your next innovation. After this course, you can proudly list your CATIA skills in your resume. THIS COURSE IS NOT A SHORTCUT TO GET THE CERTIFICATE.
Lots of people will tell you they're nervous about the changes artificial intelligence will bring to the world, but Andrew Ng is confident it's all for the best. And to bring about that future, Ng, now an adjunct professor at Stanford, will share what he knows best by teaching. Today, Ng is launching a new course on deep learning on Coursera, the online education site he co-founded. The syllabus will follow his popular machine learning course, which has attracted some 2 million enrollments since its launch in 2011. "There's a lot of PR and buzz focused on AI transforming large tech companies, but there's a lot of work that still needs to be done for AI to transform the non-tech companies," Ng tells The Verge.
The Deep Learning Specialization consists of five different courses. The courses are free to take, but you need to sign up for a subscription of $49/month if you want access to the graded assignments or earn certificates. There is a seven day free trial. The individual courses are free, but you need to visit the course pages separately (you can't sign up to them from the Specialization page). Though the courses officially start on 15 August, the course materials for the first three courses are already available.
Andrew Ng is a soft-spoken AI researcher whose online postings talk loudly. A March blog post in which the Stanford professor announced he was leaving Chinese search engine Baidu temporarily wiped more than a billion dollars off the company's value. A June tweet about a new Ng website, Deeplearning.ai, Today that speculation is over. Deeplearning.ai is home to a series of online courses Ng says will help spread the benefits of recent advances in machine learning far beyond big tech companies such as Google and Baidu.
Some videos are available only by enrolling in a Coursera or EdX class. It is free to do so, but sometimes the classes are no longer in session so you have to wait a couple of months, so you have no access. I'm going to be adding more videos from public sources and replacing the online course videos over time. I like using university lectures.