Deep learning is quite a complicated subject that requires lots of practice to master. It can be explained as a subfield of machine learning or an artificial intelligence function that imitates the human brain in processing data and creating various patterns that are later used in decision making. Udacity Deep Learning Nanodegree program provides in-depth knowledge and can help you to become an expert in this field.
Udacity Deep Learning is exactly what we’ll be focusing on today, so if you’re interested in the benefits that this nanodegree program can provide you with, stick till the end!
In this article, we’ll be covering all the information that’s needed to understand how the Udacity Deep Learning Nanodegree program works. I will include all the subjects that are covered, the information about the instructors, the skills you need before enrolling, and all the benefits that Udacity Nanodegree programs can bring. Also, at the very end of this article, I’ll introduce additional programs that are also recommended when studying deep learning.
It’s time to move further and find out more about this subject.
Table of Contents
- 1. Why Study Deep Learning?
- 2. Udacity Deep Learning Nanodegree Program (Enroll HERE)
- 2.1. What Should You Know Before Enrolling in Udacity Deep Learning Nanodegree?
- 2.2. What Courses are You Going to Cover?
- 2.3. What are the Perks of Udacity Nanodegree Programs?
- 2.4. Who Will be Your Instructors?
- 2.5. Udacity Deep Learning Pricing & Financial Support
- 3. Alternatives to Udacity Deep Learning Nanodegree Program
- 3.1. Deep Learning Specialization (Enroll HERE)
- 3.2. Professional Certificate in Deep Learning (Enroll HERE)
- 3.3. Deep Learning A-Z™: Hands-On Artificial Neural Networks (Enroll HERE)
- 4. Conclusions
Why Study Deep Learning?
As already explained, deep learning is a part of machine learning methods. To put it simply, it teaches computers to perform tasks that come naturally to humans. Deep learning was first mentioned back in 1980, however, it wasn’t as useful back then as it is now. This has to do with the lack of computer power and data.
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If you’re still a beginner in this field and don’t have any previous experience, it can be difficult to understand how it works. For this reason, I want to shed some light on this topic and explain how machine learning functions and how it can be put into practice.
When searching for information about deep learning, you will also come across machine learning and artificial intelligence. All of them are vital when it comes to technologies that have an impact on our everyday lives.
Deep learning is used in multiple technologies, including:
- Self-driving cars. Deep learning allows them to recognize people crossing the street, road signs, etc. The main goal is to teach the technology to see things like humans do and learn to perform on their own.
- Voice control. The majority of us are used to hand-free speakers, TVs, tablets and phones that are controlled by voice. Of course, only a small percentage of people realize that deep learning is behind all of that.
- Entertainment. Deep learning is used in VEVO, Netflix, Amazon, and other platforms. For example, Netflix is using deep learning to provide customers with a personalized experience by offering various movies and TV shows based on the previously-watched content.
- Visual recognition. Due to deep learning, machines are capable of sorting images into different categories such as a group of people, faces, buildings, etc. They can even offer categorization based on the specific event or date.
- Healthcare. Nowadays, deep learning is widely used in healthcare. It can help to make quicker, more accurate diagnoses, predict future health risks, and so on.
So, due to deep learning, computers can complete various tasks, they can recognize images, sound or text, just the way people do. In fact, some deep learning models can achieve even better results than humans, for example, when it comes to healthcare. This has to do with a complete accuracy that not many people can deliver.
Needless to say, deep learning is used in multiple fields nowadays (keep in mind that I provided only a few examples). For this reason, studying the Udacity Deep Learning Nanodegree program can open new doors for you, especially when it comes to new career opportunities. After all, experts in this field are always needed.
By now it should be clear what deep learning is, where it’s used, and why it’s worth studying. So now let’s move further into the Udacity Deep Learning Nanodegree program review and find out more about it.
- Estimated Time: 4 months (12 hours per week)
- Price: $1356 ($339 per month)
- Certificate: YES
- Level: Intermediate - Advanced
- Apply HERE
When searching for Udacity Deep Learning you will immediately come across the Udacity Nanodegree program. While there are also regular deep learning courses available on this platform, it’s evident that the program is recommended for those who want to gain in-depth knowledge instead of very generic information.
Udacity Deep Learning is recommended for everyone who wants to understand how it’s changing the world around us. This course focuses on teaching you how to build and apply your own deep neural networks to various tasks such as image generation and classification, model deployment, and time-series prediction.
There’s a lot to discuss when it comes to Udacity Deep Learning Nanodegree, so let’s start from the beginning.
What Should You Know Before Enrolling in Udacity Deep Learning Nanodegree?
Before enrolling in the course or program it’s crucial to make sure that you have the needed knowledge and experience. Otherwise, you can find it too overwhelming.
Udacity Deep Learning Nanodegree program is created for people who want to gain knowledge in artificial intelligence, machine learning, and deep learning (obviously). The program requires you to have experience with Python, especially NumPy and pandas.
Also, it will be easier for you if you have some knowledge of machine learning. I said easier because this experience is not required, you’ll be covering all the needed basics in this program. Moreover, it’s recommended that you would be familiar with calculus and linear algebra.
All in all, apart from experience with Python, recommended knowledge in machine learning, and familiarity with calculus and linear algebra, the Udacity Deep Learning Nanodegree program would be suitable for beginners.
Now, if you don’t have the required knowledge and skills, it doesn’t mean that you won’t be able to enroll in Udacity Deep Learning Nanodegree program. You’re probably wondering how is that possible? Well, you can easily prepare yourself for learning with AI Programming with Python Nanodegree program.
AI Programming with Python Nanodegree program is all about teaching you AI fundamentals such as Python, NumPy and PyTorch programming tools. What is more, it will provide you with the needed knowledge in calculus and linear algebra, and the key techniques of neural networks. You should be able to complete this program within 3 months, however, once you’re done, you will be fully prepared for the Udacity Deep Learning Nanodegree program.
Now that you know what knowledge and skills are needed to enroll in this program and start studying deep learning, it’s time to move further and find out more about it.
What Courses are You Going to Cover?
Udacity Deep Learning Nanodegree program consists of 5 courses that each include multiple lessons and cover different subjects. Let’s go through each of those courses to find out more about what you’re going to learn.
Course 1: Neural Networks
The first course focuses on the basics of neural networks. You will learn how to implement gradient descent and backpropagation in Python. What is more, you will learn to use NumPy matrix multiplication, techniques that can help to improve neural networks training as well as preventing overfitting of training data and practices that help to minimize the error of a network.
Moreover, you will learn how to define and train neural networks for sentiment analysis, and how to use PyTorch. This course also includes a project on building and training neural networks from the very beginning to predict the number of bike-share users on the provided day.
Course 2: Convolutional Neural Networks
The second course consists of 7 lessons, it’s all about building convolutional networks and using them to classify images based on various objects and patterns that appear in them.
At the beginning of this course, you will learn to train your neural network faster by using Amazon’s GPUs. Moving further, you will learn more about Convolutional Neural Networks (CNN), CNN in PyTorch, weight initialization to arrive at an optimal solution faster, and even more.
In this course, you will also have an interesting project that will allow you to define a Convolutional Neural Network that can identify dog breeds better than an average human being.
Course 3: Recurrent Neural Networks
The third course is all about building recurrent neural networks (the name says it all) and long short-term neural networks with Pytorch. The course consists of 6 lessons:
- Recurrent neural networks.
- Long short-term memory networks.
- RNN & LSTM implementation.
- Embeddings & Word2vec.
- Sentiment prediction RNN.
The third course also includes a project that will require you to create your own recurrent networks as well as long short-term memory networks using PyTorch. Generating new text, performing sentiment analysis as well as using recurrent networks to generate new text is also a part of this project.
Course 4: Generative Adversarial Networks
Course number 4 is all about the implementation of Deep Convolutional generative adversarial networks (GAN) that will help you to generate realistic-looking images.
The class includes 4 lessons. The first one focuses on generative adversarial networks and using them on a simple dataset. The second lesson will teach you how to use GAN to create complex, color images of house numbers. Finally, you will learn about the CycleGan formulation that is capable of learning from unlabeled sets of images.
This course will be very interesting to study as your main project will be to generate realistically-looking faces by applying all the knowledge that you gained in these lessons and using Deep Convolutional GAN made of a pair of multi-level neural networks that compete against each other to achieve the best result.
Course 5: Updating a Model
In the final course, you will learn how to use Amazon SageMaker on AWS to deploy your own PyTorch sentiment analysis model. The main goal is to train this model so that it would be able to perform sentiment analysis on movie reviews - positive or negative ones.
The course includes 5 lessons:
- Introduction to deployment - the usage of cloud deployment and various deployment methods such as websites, apps, and so on.
- Deploy a model - learn to apply built-in algorithms using Amazon SageMaker.
- Custom models & web hosting - training and deploying your own PyTorch model.
- Model monitoring - learn to interpret log messages, and monitor your model behavior.
- Updating a model - evaluate indicators such as data distribution to recognize if the model could be updated.
As you can see, there’s so much to cover when it comes to Udacity Deep Learning, so why not start right now?
What are the Perks of Udacity Nanodegree Programs?
Now that you know what you’re going to learn, I would like to cover the benefits of choosing Udacity Nanodegree Programs, whether it’s deep learning, machine learning, or any other subject.
The perks that could be distinguished are these:
- Hands-on experience.
- Get access to Knowledge - proprietary Udacity wiki.
- Student Hub - communicate with your classmates.
- Automatically-graded quizzes to test your knowledge.
- Create a custom study plan.
- Track your progress.
First of all, Udacity Nanodegree programs will provide you with hands-on experience. You will work with industry-relevant projects that will help you to gain valuable skills that are easily applicable in the real world. Udacity has a network of more than 900 reviewers that will provide you with personalized feedback and will help you to achieve better results. Also, since Udacity has a very clear interface, you’ll be able to upload your projects without much trouble.
Moreover, once you enroll in Udacity Deep Learning Nanodegree, you get access to Knowledge where you can find answers to your questions in no time. What is more, you can also find answers to the questions that other students were looking for as well as connect with mentors to solve the issues that you’re experiencing.
Some say that the easiest way to learn is by teaching others. That’s exactly what you can do by using the Student Hub. It allows you to connect with fellow learners, ask questions as well as provide advice. Let’s just say that it should make your learning experience a lot more enjoyable.
Now, Workspaces allow you to test the quality of your codes as well as the output. It’s a part of your classroom. What is more, Udacity Deep Learning Nanodegree includes quizzes that will allow you to test your knowledge and see if you actually understand what you’re learning. The quizzes are graded automatically, so you will get the results in no time. Keep in mind that if you forgot about a specific concept, you can easily get back to classes where you learned about it and repeat it once again until you have a full understanding.
To motivate yourself better, you can create custom study plans and easily add them to your personal calendar. This way, you will always remember when it’s time to study and will create yourself a routine that will help you to stick to the schedule.
Udacity Deep Learning Nanodegree also includes a progress tracker. Needless to say, when you can see progress it’s easier to motivate yourself to move further. Also, the program includes milestones that work as great reminders.
Thus, once enrolled in the Udacity Deep Learning Nanodegree program, you will have an amazing online classroom experience. Since the majority of traditional institutions have transferred classes online due to COVID-19 pandemic, you will have quite a similar experience as university students, especially since you’ll be able to communicate with your classmates, ask for advice and even help other students understand specific topics.
Since this part of the Udacity Deep Learning Nanodegree review is already clear, let’s move further and find out about experts who will be teaching you.
Who Will be Your Instructors?
People say that if you want to become the best, you need to learn from the very best. After all, who can provide you with better knowledge than people who have been working in that specific field for years?
Getting back to Udacity Nanodegree, you will have 1 curriculum lead and 7 instructors. Let me briefly introduce to you each of them:
- Cezanne Camacho (curriculum lead) - a computer vision expert who received her Masters in Electrical Engineering from Stanford University - one of the most prestigious universities in the world. She’s applied deep learning to medical diagnostics.
- Matt Leonard (instructor) - a former physicist, data scientist, and research neuroscientist who gained his Ph.D. and completed a Postdoctoral Fellowship at the University of California, Berkeley.
- Luis Serrano (instructor) - received his Ph.D. in mathematics from the University of Michigan, Serrano had an opportunity to work at Google as a Machine Learning Engineer.
- Alexis Cook (instructor) - applied mathematician who received her Master’s degree in computer science from Brown University and Master’s degree in applied mathematics from the University of Michigan.
- Jennifer Staab (instructor) - has Ph.D. in Computer Science and Masters in Biostatistics. She has worked as a statistician and computer scientist for years.
- Sean Carrell (instructor) - specializing in Algebraic Combinatorics, Carell is a former research mathematician who completed his Ph.D. and Postdoctoral Fellowship at the University of Waterloo, Canada.
- Ortal Arel (instructor) - previously worked as a computer engineering professor, received her Ph.D. in Computer Engineering from the University of Tennessee.
- Jay Alammar (instructor) - computer scientist.
Based on student reviews, they’re very happy not only about the knowledge they gain but also about instructors that make every class interesting and worth the wait. That being said, this should encourage you to stop hesitating and start learning right now.
Udacity Deep Learning Pricing & Financial Support
Now that we’re moving towards the end of this Udacity Deep Learning Nanodegree review, it’s to discuss the pricing of this program and find out whether or not it’s worth paying.
Currently, the Udacity Deep Learning Nanodegree program costs $1356 for all 4 months. It might seem quite expensive to pay it all at once, however you can simply choose to pay as you go. If you do that, you will need to pay as low as $339 per month. It’s fair to say that the price is very affordable, especially when you take a look at all the skills that you’re going to learn.
Also, there’s one more option that allows you to start learning now but pay later. Affirm financing allows you to make monthly payments over 3, 6, or 12 months. That being said, you can pay as low as $113 per month at 0% APR. That sounds like a good option, however, it’s completely for you to decide.
Alternatives to Udacity Deep Learning Nanodegree Program
Udacity Deep Learning Nanodegree program is definitely one of the best ones you’ll be able to find, however, there are also other alternatives that you might want to take into account. Even though they’re not as extensive, thousands of students have already enrolled in them.
Without further ado, let’s take a look at those alternatives.
- Platform: Coursera
- Estimated Time: 4 months (about 5 hours per week)
- Price: FREE for 7 days, then $49 per month
- Certificate: YES
- Level: Intermediate
- Apply HERE
Deep Learning Specialization is one of the better alternatives to the Udacity Deep Learning Nanodegree program. It focuses on deep learning capabilities, challenges and consequences. You will learn how to build neural network architectures and make them better using different techniques and strategies such as BatchNorm, Dropout, and others.
You should be able to complete this specialization within 4 months when learning about 5 hours per week. What’s amazing about it is that you can start learning completely free and see whether or not it’s suitable for your needs.
The Deep Learning Specialization offered by Coursera is recommended for intermediate-level students as you need to have previous knowledge in Python, including basic programming skills, understanding of data structures, if/else statements and loops. You also need to have a basic understanding of linear algebra and ML.
Once you complete this specialization, you will have both theoretical and practical knowledge.
- Platform: edX
- Estimated Time: 8 months (2-4 hours per week)
- Certificate: YES
- Level: Intermediate
- Apply HERE
The Professional Certificate in Deep Learning offered by edX is another alternative for those who are looking for “deep learning Udacity”. The program is self-paced, so you’ll be able to learn whenever you find the time.
The Certificate covers multiple courses, including deep learning fundamentals with Keras, PyTorch basics for machine learning, deep learning with Python and PyTorch, deep learning with Tensorflow, and others.
In this program, you will learn more about practical applications and various concepts of deep learning. What is more, you will learn how to build models and algorithms by applying deep learning. To do that, you’ll be using various libraries such as PyTorch, Tensorflow and Keras.
This course is not only about theoretical material, you will also gain practical experience through various assignments, hands-on lab works, and projects that will help to solve actual problems.
To complete the Professional Certificate in Deep Learning, you will need to prepare a deep learning capstone project. Using this project you’ll be able to show off your skills to future employers and get better job opportunities.
- Platform: Udemy
- Estimated Time: 22.5 hours
- Price: $11.99
- Certificate: YES
- Level: Intermediate
- Apply HERE
Deep Learning A-Z™: Hands-On Artificial Neural Networks is an extensive course that will teach you how to create deep learning algorithms in Python. In this course, you’ll be learning from the experts in their field, so they will definitely teach you valuable knowledge.
As I mentioned, this course is definitely very extensive, it consists of 26 sections, 173 lectures and about 22 hours of content. While it’s self-paced, everyone will be able to complete it within a different time frame.
In this course, you will gain knowledge in Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Self-Organizing Maps, Boltzmann Machines and Autoencoders. What is more, you will get hands-on experience and learn how to apply Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, and all the other previously-discussed networks in real-life situations.
The instructors of your course are Kirill Eremenko and Hadelin de Ponteves. Kirill Eremenko is a data scientist who has experience in finance, retail, transport and other industries. Hadelin de Ponteves is an AI entrepreneur who’s also a co-founder and CEO at BlueLife AI. He’s already created more than 70 high-rated online courses.
Since this course is a path of learning series, it’s recommended to continue learning other provided courses for in-depth knowledge.
After completing the Udacity Deep Learning Nanodegree review, it’s clear that this program is one of the best options for those who want to become experts in deep learning. The program consists of 5 courses:
- Neural Networks
- Convolutional Neural Networks
- Recurrent Neural Networks
- Generative Adversarial Networks
- Updating a Model
Almost every course includes not only theoretical knowledge but also hands-on experience that will help you to easier understand every subject. Once enrolled in this program, you’ll gain access to various career services, technical mentor support, the ability to learn at flexible hours and participate in various real-world projects.
In the Udacity Deep Learning Nanodegree program, you’ll be learning from the experts in their field, including data scientists, neuroscientists, mathematicians, computer vision experts, computer engineers, and other specialists that will transfer their knowledge to you.
This program costs $1356 which is $339 per month. While it can be slightly expensive, you can get financial support from Udacity. Also, you can take advantage of Affirm financing and start learning now but pay later.
Before enrolling in this program, make sure that you have the needed knowledge. You need to have experience with Python, basic knowledge in machine learning would be also great, and you should be familiar with calculus and linear algebra. If you lack this experience, there’s no need to worry, you can enroll in AI Programming with Python Nanodegree program that will provide you with the needed skills.
Finally, if you want to check out some other great alternatives, including programs and courses on deep learning, you should definitely take a look at these options:
- Deep Learning Specialization
- Professional Certificate in Deep Learning
- Deep Learning A-Z™: Hands-On Artificial Neural Networks
I hope that this Udacity Deep Learning Nanodegree review provided you with all the information that you were looking for. So wait no more and start studying to become an expert in deep learning!