Do I need to have a good level in maths to understand this course?
Only high school level in mathematics, especially in probability, statistics, and a little bit in algebra. You will get an intuitive understanding of how the models work, without needing all the mathematics behind it. And for those who want to go further, we will give you each time the best reference that accompanies the lectures.
Last updated: March 17, 2017 06:19
Do I need to know how to code?
No! You don’t need any prior experience in coding. We will not type any line of code without explaining what it does and how it works. Besides we will often take a step back to have a global vision at the code, to make sure you see the logic pattern of the code.
Last updated: March 17, 2017 06:19
Do I need prior knowledge or experience in Machine Learning?
No! We will explain every concept that needs to be integrated before exploring the Deep Learning universe.
Last updated: March 17, 2017 06:19
Which bundle should I take if I am a complete beginner in Data Science?
Again, you don’t need an extensive background in mathematics or prior experience in coding to understand and apply Deep Learning. But if you really want to start from scratch, and learn the different branches of Data Science one by one, we recommend the COMPLETE EDITION which contains separate courses in Python, R, Data Science, Machine Learning and Deep Learning.
Last updated: March 17, 2017 06:19
What happens if I am stuck at some point in the course, if I don’t understand something or if my code doesn’t work?
If you are stuck at some point in the course, whether it is a problem with your code or something you don’t understand, feel free to ask a question in the Q&A and someone from the team will reply to you and help you fix the problem usually within 24 hours. In fact, all of our students who asked question in the Machine Learning got assistance in less than 24 hours.
Last updated: March 17, 2017 06:19
How flexible are the code templates if I want to reuse them for my datasets?
The code templates are very flexible, and can work on any datasets, provided they have the same form as the ones given in the lectures. There will be very few changes to make for you to adapt them to your datasets, but we will of course explain clearly how to manage that.
Disclaimer: if you choose to apply the provided code templates to your own projects, you are doing so at your own risk.
Last updated: March 17, 2017 06:19
How will I get the course bundles?
We will send out a survey at the end of the kickstarter. You will need to provide your email address and then within a few days you will get a special coupon code to enroll in the course. Note: this is our very first kickstarter, so please forgive us if there are slight delays in getting these surveys / coupon codes to you. We are still learning this :)
Last updated: March 17, 2017 06:19
How will I get the bonuses?
The bonuses are separate to the course and will be sent to your email via a dropbox link after you have completed the survey.
Last updated: March 17, 2017 06:19
Will this course be hosted on Udemy?
That is correct. This course will be hosted on Udemy. If you are wondering about price, then we’ve specifically set the prices in such a way that even during the initial promotion on Udemy it won’t be possible to get the whole course + all the bonuses at a price lower than the kickstarter special reward level.
Last updated: March 17, 2017 06:19
What are “Intuition Tutorials”?
If practical tutorials are the “How?”, then Intuition Tutorials are the “Why?”. Let us explain this in a bit more detail.
Deep Learning is a complex topic and can be hard to understand on a conceptual level. This is not made easier by the sophisticated calculus that usually accompanies lectures on Deep Learning. That’s why we have developed special Intuition Tutorials which help you understand the concepts on a profound level (without the math) before you dive into the practical applications. This way solving the business challenges in this course will be ten-fold more meaningful and it should be super-clear not only How we are creating the algorithms but also Why we are creating them in a certain way.
Last updated: March 17, 2017 07:24
What kind of computer will I need for this course?
Just a computer that is not from 20 years ago :)
Last updated: March 17, 2017 08:08
What is the recommended order for taking the courses in the Complete Edition?
It will always depend on what you want to master first. These courses are very in-depth and there can be many ways to go through them. Moreover, the courses are absolutely independent, so you can go through them in any order! Really depends on what you want to accomplish first. Very detailed descriptions and curriculums will be available for each course once you enroll. Please review those to understand how to best structure YOUR personal learning journey :)
Last updated: March 17, 2017 23:27
Is this course timed or can I approach it at my own pace?
Course is completely self-paced and with the benefit of lifetime access you can go through it as quickly or as gradually as you like. Feel free to approach the tutorials with the learning style that is most comfortable and convenient for you!
Last updated: March 17, 2017 23:28
Will I have an opportunity to ask questions if I get stuck?
All students of this course have the opportunity to interact with the instructors and our support staff: you can post a question at any time and we will get back to you to help overcome whatever challenge you are facing. We usually respond within 24 hours no matter how complex your query!
Last updated: March 17, 2017 23:43
Interesting things about Deep Learning
What does the future of deep learning hold? How will it change the World? Can we control AI if we create it? Curious?… Check out the list of cool articles here for interesting thoughts, opinions and discussions:
https://hackernoon.com/index-of-best-ai-machine-learning-resources-71ba0c73e34d#.lrmaeew9a
Shout out to Dave from Amsterdam for the share!
Last updated: March 22, 2017 18:58
Do I need to have a good level in maths to understand this course?
Only high school level in mathematics, especially in probability, statistics, and a little bit in algebra. You will get an intuitive understanding of how the models work, without needing all the mathematics behind it. And for those who want to go further, we will give you each time the best reference that accompanies the lectures. Last updated: Fri, Mar 17 2017 9:19 am EDT
Do I need to know how to code?
No! You don’t need any prior experience in coding. We will not type any line of code without explaining what it does and how it works. Besides we will often take a step back to have a global vision at the code, to make sure you see the logic pattern of the code. Last updated: Fri, Mar 17 2017 9:19 am EDT
Do I need prior knowledge or experience in Machine Learning?
No! We will explain every concept that needs to be integrated before exploring the Deep Learning universe. Last updated: Fri, Mar 17 2017 9:19 am EDT
Which bundle should I take if I am a complete beginner in Data Science?
Again, you don’t need an extensive background in mathematics or prior experience in coding to understand and apply Deep Learning. But if you really want to start from scratch, and learn the different branches of Data Science one by one, we recommend the COMPLETE EDITION which contains separate courses in Python, R, Data Science, Machine Learning and Deep Learning. Last updated: Fri, Mar 17 2017 9:19 am EDT
What happens if I am stuck at some point in the course, if I don’t understand something or if my code doesn’t work?
If you are stuck at some point in the course, whether it is a problem with your code or something you don’t understand, feel free to ask a question in the Q&A and someone from the team will reply to you and help you fix the problem usually within 24 hours. In fact, all of our students who asked question in the Machine Learning got assistance in less than 24 hours. Last updated: Fri, Mar 17 2017 9:19 am EDT
How flexible are the code templates if I want to reuse them for my datasets?
The code templates are very flexible, and can work on any datasets, provided they have the same form as the ones given in the lectures. There will be very few changes to make for you to adapt them to your datasets, but we will of course explain clearly how to manage that. Disclaimer: if you choose to apply the provided code templates to your own projects, you are doing so at your own risk. Last updated: Fri, Mar 17 2017 9:19 am EDT
How will I get the course bundles?
We will send out a survey at the end of the kickstarter. You will need to provide your email address and then within a few days you will get a special coupon code to enroll in the course. Note: this is our very first kickstarter, so please forgive us if there are slight delays in getting these surveys / coupon codes to you. We are still learning this :) Last updated: Fri, Mar 17 2017 9:19 am EDT
How will I get the bonuses?
The bonuses are separate to the course and will be sent to your email via a dropbox link after you have completed the survey. Last updated: Fri, Mar 17 2017 9:19 am EDT
Will this course be hosted on Udemy?
That is correct. This course will be hosted on Udemy. If you are wondering about price, then we’ve specifically set the prices in such a way that even during the initial promotion on Udemy it won’t be possible to get the whole course + all the bonuses at a price lower than the kickstarter special reward level. Last updated: Fri, Mar 17 2017 9:19 am EDT
What are “Intuition Tutorials”?
If practical tutorials are the “How?”, then Intuition Tutorials are the “Why?”. Let us explain this in a bit more detail. Deep Learning is a complex topic and can be hard to understand on a conceptual level. This is not made easier by the sophisticated calculus that usually accompanies lectures on Deep Learning. That’s why we have developed special Intuition Tutorials which help you understand the concepts on a profound level (without the math) before you dive into the practical applications. This way solving the business challenges in this course will be ten-fold more meaningful and it should be super-clear not only How we are creating the algorithms but also Why we are creating them in a certain way. Last updated: Fri, Mar 17 2017 10:24 am EDT
What kind of computer will I need for this course?
Just a computer that is not from 20 years ago :) Last updated: Fri, Mar 17 2017 11:08 am EDT
What is the recommended order for taking the courses in the Complete Edition?
It will always depend on what you want to master first. These courses are very in-depth and there can be many ways to go through them. Moreover, the courses are absolutely independent, so you can go through them in any order! Really depends on what you want to accomplish first. Very detailed descriptions and curriculums will be available for each course once you enroll. Please review those to understand how to best structure YOUR personal learning journey :) Last updated: Sat, Mar 18 2017 2:27 am EDT
Is this course timed or can I approach it at my own pace?
Course is completely self-paced and with the benefit of lifetime access you can go through it as quickly or as gradually as you like. Feel free to approach the tutorials with the learning style that is most comfortable and convenient for you! Last updated: Sat, Mar 18 2017 2:28 am EDT
Will I have an opportunity to ask questions if I get stuck?
All students of this course have the opportunity to interact with the instructors and our support staff: you can post a question at any time and we will get back to you to help overcome whatever challenge you are facing. We usually respond within 24 hours no matter how complex your query! Last updated: Sat, Mar 18 2017 2:43 am EDT
Interesting things about Deep Learning
What does the future of deep learning hold? How will it change the World? Can we control AI if we create it? Curious?… Check out the list of cool articles here for interesting thoughts, opinions and discussions: https://hackernoon.com/index-of-best-ai-machine-learning-resources-71ba0c73e34d#.lrmaeew9a Shout out to Dave from Amsterdam for the share! Last updated: Wed, Mar 22 2017 9:58 pm EDT
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