Top 9 Deep Learning Courses for Developers and Data Scientists
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Deep learning has been the driving force of advances in artificial intelligence (AI) and has been changing the world and our understanding of the world as we know it.
A thorough understanding of deep learning will enable you to master the building and implementation of neural networks for image recognition, sequence generation, image generation, and so much more!
Artificial intelligence has been transforming multiple industries and by better understanding deep learning, you will be able to find creative ways of applying your work in helpful ways that contribute to the expansion of AI.
The demand for data scientists and developers trained as deep learning professionals is booming. Industries across the world have been embracing AI and the demand for deep learning skills is bound to increase exponentially over time.
Here is a list of some of the 9 top-rated courses we could find to help you gain insights into the world of deep learning:
DEEP LEARNING | UDACITY
If you’re looking to build and apply your knowledge of deep neural networks and deep learning models to challenges such as image classification and generation, time-series prediction, and model deployment, look no further than this comprehensive nanodegree program offered through Udacity by AWS.
This all-inclusive 4-month program includes real-world projects with immersive content designed by industry experts and top tier companies, technical mentor support from knowledgeable mentors who will guide and motivate your learning process, access to personal career coaches and career services to help you expand your career, as well as a custom learning plan that has been tailored to fit your busy schedule and learning style.
Before enrolling, you will be required to have a working knowledge of Python programming, including NumPy and pandas.
Outside of the Python prerequisites, the program is beginner-level friendly and targets individuals who have a keen interest in machine learning, artificial intelligence and deep learning.
What the reviews are saying:
“This is probably the most approachable way to get into deep learning I have found thus far. The course covers a lot of interesting subjects, with (usually) good explanatory videos and walkthroughs. These always feel fresh and get you motivated for the subjects you are about to learn. As a bonus, they have gotten a few known names to present individual subjects. As an example, the introduction to GANs is done by none other than the inventor himself, which is a cool bonus. There is a lot of great material here, and while some of it feels a bit rushed or oversimplified at times, they do reference more material for those that want to dive deeper into the learning B). (That being said, you will definitely have to get your hands dirty at times as well.) The main value here is in the projects and introductory notebooks. Here, you’ll get a lot of hands on experience writing code, and you will definitely feel like you’ve come a long way after finishing them all. Best of all, you’ll have working code that you can tweak and use for your own projects afterwards, and perhaps a ton of ideas as well. All in all, money well spent, at least in my case.” – Peter L.
“This program definitely delivered what it promised. It was a valuable experience to learn from the leading experts in the field and be part of an active student community.” – Arda O.
DEEP LEARNING EXPLAINED | QUICKSTART
Deep Learning Explained is a beginner friendly course that helps introduce to you the basic concepts of deep learning and its various applications.
Deep learning is a key component to AI-powered advancements that are created globally. You will cover the theoretical aspects of machine and deep learning, as well as the practical aspects as you learn to build applications based on cognitive computing, artificial intelligence and deep learning.
On completion of this course, you should have gained proficiency with an intuitive way of dealing with building complex models that assist machines in solving genuine issues with human-like intelligence.
Anyone with some working knowledge of data science and basic programming skills is welcome. You will be able to complete the course at your own pace which runs for 24 hours in total. There are also various community and course experts that you can consult with.
DEEP LEARNING: GANS AND VARIATIONAL AUTOENCODERS | UDEMY
If you have a basic understanding of deep learning and are looking to broaden your knowledge of deep learning, this course is for you!
This best-seller course designed and created by Lazy Programmer Inc. was developed to help you learn the basic principles of generative models, how to build a GAN (Generative Adversarial Network) in Theano and TensorFlow, as well as how to build a variational autoencoder in Theano and TensorFlow.
Variational autoencoders and GANs have become two of the most interesting and important developments in deep learning. A working understanding of these concepts will definitely put you ahead in your field of development.
The course includes 7.5 hours of on-demand video content and can be completed at your own pace with full lifetime access to the content.
Be sure to check out this incredible opportunity to improve on your deep learning knowledge.
What the reviews are saying:
“As always a really great course from lazy programmer. I am someone who wants to understand the underlaying math and all the related topics which can help me to create better understanding of the things I am learning and lazy programmer is great at doing that. The practical examples are really good and gives good kick start to initiate building something new from it.” – Bhargav Upadhyay
“Couldn’t have asked for a better course about unsupervised deep learning and GANs. Great discussion on variational autoencoders and it makes the math really clear. I loved the review section, it helps you understand the big picture between complicated deep learning topics and the basic foundations.” – Matthew Wu
AI MACHINE LEARNING – DEEP LEARNING & COMPUTER VISION: AN INTRODUCTION 2017 | E-COURSES4YOU
Be able to discover core machine learning concepts as well as build an artificial neural network after completing this Deep Learning and Computer Vision course through e-courses4you.
Deep learning and computer vision are two of the hottest topics in machine learning at the moment.
This course was designed to get you started by teaching you how to design and implement a simple computer vision use-case and so much more!
The course is only 2 hours long and led by experts in the field.
By the time you have completed this course, you should have a solid understanding of the theory underlying deep learning and computer vision.
DEEP LEARNING SPECIALIZATION | COURSERA
Learn about the fascinating world of artificial intelligence through this Deep Learning Specialization course, which will broaden your understanding about this highly sought-after skill in tech.
This specialization is taught over 5 courses, in which you will learn the fundamentals of deep learning, understand how to build neural networks, and learn how to successfully lead machine learning projects.
By the end of this course, you should also be able to confidently work with Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more.
You will also work on real-life case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing, which will allow you to use your extensive knowledge of the theoretical aspects in a productive manner. You will also be able to apply this knowledge across multiple industries.
Throughout the course, you will be encouraged and assisted by world-class instructors who have extensive knowledge and practical working experience in the field.
The course will take approximately 2 months to complete at a suggested 12 hours per week.
What the reviews are saying:
“My course taught me to pick up new ideas quickly and apply them to real-world problems. Today, my certificates make me stand out from the crowd.” – Praveen K.S.
“Having a like-minded community makes me feel like I’m part of something bigger. Before Coursers, I thought online learning was lonely and unengaging.” – Gabriela G.
DEEP LEARNING: ARTIFICIAL INTELLIGENCE GRADUATE CERTIFICATE | STANFORD SCHOOL OF ENGINEERING
Andrew Ng, a Stanford Adjunct Professor, describes artificial intelligence as “the new electricity” which speaks loudly to the importance and expansion of this highly sought-after skill.
Through this comprehensive course, you will come to better understand and master the theory of deep learning and its significance to artificial intelligence.
You will learn the fundamentals of deep learning and how to apply them across multiple industries in real-life scenarios through carefully structured case studies. You will also be able to practice your ideas through programs such as Python and TensorFlow, which will be taught to you.
By the end of this course, you should be able to find creative ways of applying your knowledge to your work.
The course is taught in a flipped-classroom manner, where you will watch videos and complete in-depth programming assignments and quizzes in the comfort of your own home.
You will then attend classes for more advanced discussions and work on the projects.
At the end of the classes, you will take part in an open-ended final project which will be facilitated by an experienced teaching team.
INTRO TO DEEP LEARNING WITH PYTORCH | UDACITY
This free Intro to Deep Learning with PyTorch is offered though Udacity by Facebook Artificial Intelligence in order for you to learn how to use PyTorch to implement your first deep neural network.
Over the 2-month duration of this course, you will discover the basics of deep learning and how to build your own deep neural networks using PyTorch.
You will gather practical experience using PyTorch through detailed coding exercises and projects implementing state-of-the-art AI applications including style transfer and text generation.
The course leads are super helpful and competent professionals in their field, offering you the greatest assistance on your path to successfully completing this course.
PyTorch is an important aspect of the AI revolution as it has made it easier for almost anyone to build deep learning applications.
This course will adequately equip you with the practical experience building and training deep neural networks with the aid of PyTorch. These skills can then be applied to your own personal projects.
DEEP LEARNING: ADVANCED COMPUTER VISION (GANS, SSD, +MORE!) | UDEMY
Currently the highest rated course, this deep learning program was designed and created by the talented team at Lazy Programmer Inc.
The course was designed to help you understand and apply transfer learning, how to use object detection algorithms like SSD, understanding and using state of the art convolutional neural nets such as VGG, ResNet and Inception, applying neural style transfers, and so much more!
This deep learning program is perfectly suited for students and professional looking to take their knowledge of computer vision and deep learning to the next level, as well as individuals looking to transfer learning or anyone wanting to learn to write code for neural style transfer.
What the reviews are saying:
“Clear explanations at a good pace. Lazy programmer has given me good understanding of the industry and I’m able to apply the skills I learnt in a meaningful way.” – Sarthak Goel
“It was a good learning experience for me. Best thing I learnt is that jupyter notebooks are not a good choice. Also, the way in which the lazy programmer approaches the problems is very good. Doesn’t leave a single line of code unexplained.” – Shubham Kumar
PROFESSIONAL CERTIFICATE IN DEEP LEARNING | EDX
IBM has teamed up with edX to bring you a hands-on artificial intelligence deep learning course that will contribute to the way AI has been revolutionizing how we live, work and communicate.
The course runs over 7-months and will cover the fundamental concepts of deep learning, including neural networks for both supervised and unsupervised learning.
You will make use of popular deep learning libraries such as, Keras, PyTorch, and TensorFlow and apply these to industry problems.
This will also allow you to apply deep learning to real-life scenarios such as, object recognitions and computer vision, image and video processing, text analytics, natural language processing, recommender systems, and other types of classifiers.
Throughout the course, you will be given the opportunity to practice your deep learning skills through a series of hands-on labs, assignments, and projects inspired by real world problems and data sets from existing industries.
This program was designed for and intended to prepare learners and equip them with the necessary skills they need to become successful AI practitioners and to be able to start a career in applied deep learning.
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