Deep Learning Nanodegree

My biggest hesitation with the Nanodegree before enrolling was the price tag. I was worried I wouldnt get anything close to the value of the sticker price, particularly because I wasnt primarily motivated by career advancement.In the end, I think my worry was justified. The Nanodegree is overpriced for what it provides. The instructional videos are high quality, but many of the exercises are lifted directly from Kaggle or from research papers, and there still arent enough of them. The Nanodegree also offers a lot of personalized services that I consider expensive but low-value, like career coaching and 1on1 mentoring. As a self-motivated learner, these kinds of services only draw resources away from the product that I really care about: quality instructional content and challenging exercises.Beyond the steep price, I also felt that the subscription model was detrimental to my learning. The Nanodegree was self-paced, meaning you didnt have to stick to a set schedule, but you had to pay the same amount every month. I felt like I had to rush toward the end of the course to avoid an extra monthly payment, and this made me brush past topics I was interested in instead of pausing to learn more. As someone with a lot of curiosity but very little free time, this was a painful choice to have to make.The pricing model for Udacity courses seems like it changes a lot, so my concerns over pricing may change in the future. Many people also get their bosses to pay for courses like these, so maybe price isnt even a concern for you. But as someone working on the Nanodegree on my own time to satisfy my own curiosity, the price and the subscription model were strong negatives.Conclusion: Who should take the Deep Learning Nanodegree?The Deep Learning Nanodegree might be a good fit for you if youre eager to get some practical experience building neural networks, youre not too concerned about math, and you have a way to pay for an expensive course.If, on the other hand, youre interested primarily in theory, you want to go deep into the details, or you already have a handle on the basics of neural networks and deep learning, the Nanodegree probably wont deliver the value youre looking for. Id instead try Nielsens book for a basic introduction, or Goodfellow, Bengio, and Courvilles book for advanced instruction. In both cases, I would strongly recommend convening a reading group around the book, ideally including mathematicians.In the end, I think the course was a good use of my time. I got unstuck on some personal projects, I got ideas for new ones, and I was introduced to a lot of interesting ideas and good research papers. But I dont expect these conditions to hold for every learner, and I want you to make the best choice you can with the information available to you.

Overall, I would definitely recommend this course as it has number of benefits over other paid courses that are available on internet. To summarize, following are the key benefits.1. Curriculum was designed by some of the best industrial experts2. Concepts were taught in details and they had provided support of forums where people can post and solve each others queries.3. The modules were perfectly designed and consist of mini coding sessions, quizzes and final assignment at the end of each module.4. They provide 100 $ AWS credits for the term exercises.

It was very interesting and stressful last 4 months (I have a full-time job and a family), I enjoyed a lot the learning materials, exercises, projects and community and would definitely do that again.I warmly recommend this Foundations program to beginners and people with small experience who want to understand what problems you can solve with neural networks and how practically create solutions. From the other hand, experienced people could find the program boring or not-demanding enough.Before applying you must be ready not only to read/watch the course materials and make the exercises. Instead you should plan time for additional reading and try-the-things-yourself if you want to take the most from the learning.I want to thank Udacity team for a great experience that I had with the Deep Learning Foundations program.

Good Intro for people with Little or no Deep Learning ExperienceThis ND starts by covering the mathematical foundations of Deep Learning, then moves you through some interesting types of Deep Learning networks and their applications.The ND uses TensorFlow and Python, which are generally accepted in the field.

Best course available out there!With the new added content deep learning nanodegree can be very powerful in terms of learning. Got a job just one week after graduating from it as a fresher.

Good start pointThe course is a good start point in Deep Learning, but I feel that it could have more theory on some topics.

Could use a lot of work: not yet worth the moneyA lot of effort has clearly gone into this course and I believe it may be worthwhile doing at some point, but unfortunately isn't yet worthwhile.The materials are a mix-up of different components merged together and it shows. Some components are extremely lite on detail (they point you at blogs you should read and don't offer much more), while others repeat the same thing over and over (how many times do you need a picture of a mountain to explain SGD?).The projects and assignments are a really unnatural format: you're given half-completed notebooks where you have a very incomplete picture of what's going on (because someone else wrote 80% of the code) and you're expected to just complete a few functions or variable assignments. This is useless for building up pragmatic knowledge that would be useful in the real world.They've made an attempt at having "tutors" via a slack channel, a forum, and a mentor check-in system: these are fundamentally useless for the types of problems students are encountering. The slack is littered with fragments of code of students who can't get things working, and results in students apparently copy and pasting each-others code until something works. The community engagement team are active on the slack, but can't answer technical questions. The experts who drop in once a week for an hour or so generally aren't able to help, and it shows: they rarely get much interaction.The course is very silicon valley in that it's "move fast and be broken": one of the most active channels on slack is for pointing out errors and problems in the code, materials, and videos.That said, the production quality of the videos is generally quite high. The lecturers are all quite clear and well spoken, the videos have good diagrams and visuals most of the time.

Acts as a good introduction to a lot of the deep learning concepts. It is left on the student to explore all the concepts in greater detail, which is mandatory if anyone wants to make a career in this field. The slack channel is an amazing place to communicate with other DL enthusiasts and the office hours with experts gives an insight into how people are actually applying neural nets in research. The projects and mini-projects are the best part of the course as they'll really give your resume a boost if you work hard on them. Overall, highly recommended.

Working on last project now. Learned most of the material by using other resources. It's certainly been a good guide and will be an official certification.

I just submitted the last project. Overall I have enjoyed it, although the bulk of it is pretty much pieces from their "intro to machine learning" and "machine learning".The projects are ok, the first three are the usual iPhython notebook where you fill in your answers. The fourth is a little more complicated and less guides, but also the most fun: teaching a smart cab to drive using reinforcement learning.The forums are active and there will always be a TA or some other student that will answer your question.Overall it took me a little a little over two months, but I admit that I have put time into it. Since you get half your money back if you complete it in less than 10 (12?) months, if you have the time to put into it and finish it more or less quickly I would definitely recommend it.

I enrolled in Deep Learning Nanodegree, Machine Learning Nanodegree, and Data Analyst Nanodegree. I was disappointed at all of them. The course seems to be disorganized. The instructors add many unnecessary information, which made the explanation less clear. When I had puzzles in the projects, it's hard to find someone to help me out. The mentors are previous Nanodegree students and not good enough to help you solve your puzzles.No 1-to-1 appointment, no useful support, disorganized lecturers, overpriced tuition. 1 year ago, the Udacity Nanodegree is 200 dollars/month. When you finish the Nanodegree in 12 months, you will get the half of tuition refund. At that time, the Nanodegree has 1-to-1 appointment. You can choose anytime to schedule an office hour to get help from teaching assistant. They help you through video chat. You can also choose Job guarantee service that if you do not get job in that field after 6 months of graduation then they refund you full tuition.NOW ALL THESE GONE!!!The tuition of Udacity Nanodegree keeps going up. Why do you spend more than 1000 dollars on a 3 or 4 month video course without enough support? The certificate is also without verification.

Currently at my fourth project. The projects have a good and bad part to it. It is very guided and a lot much is already done for you. So, you might feel that you might not be learning too much. At the same time it just lets you focus on optimizing your algorithm's performance which isnt really hard.