Deep Learning involves techniques that can’t be understood without an effective teacher.
First off, you need to have a solid understanding of advanced mathematical concepts and understanding of Algorithms for deep learning. So, if you need a refresher, I’ve got you covered in Maths for Machine Learning and Learn Algorithms for Machine Learning
This post is originally published and updated here ➡ Deep Learning Courses
Below, I’ve curated a selection of the best available courses in Deep Learning for beginners and experts who aspire to expand their minds.
1. Deep Learning with Python - DataCamp
If you want to learn Deep Learning in Python, this course will introduce you to the fundamental concepts and terminologies used in deep learning, and understand why deep learning techniques are powerful these days.
This course will provide basics of deep learing and neural networks and also teach you a deep learning framework called Keras using which in just a few lines of code you can train very deep neural networks.
This course is suitable for beginners in Deep Learning with good knowledge of Python programming and some experience in Machine Learning.
By the end of this course you will also build a simple neural network all by yourself and generate predictions using Python’s numpy library.
2. An Introduction to Practical Deep Learning - Intel AI Academy
An Introduction to Practical Deep Learning is taught by AI Principal Engineers at Intel.
This course is very dense and informative that aims to help learners to grasp the basics of Deep Learning.
This course is primarily aimed at learner with some background in programming and understanding of basic calculus, but are new to the field deep learning.
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3. Deep Learning Specialization - Andrew NG
Deep Learning CourseThis is one of the best and highly recommended Deep Learning Specialization, comprised of five courses taught be the AI Pioneer - Andrew Ng, Co-Founder of Coursera, DeepLearning AI and Adjunct Professor at Stanford University.
This specialization will help to learn the foundations of Deep Learning, understand techniques to build effective neural networks, and learn how to manage successful machine learning projects.
This specialization assumes that a learner has intermediate skills in Python and basic knowledge of statistics to understand and work on case studies from healthcare, autonomous driving, music generation, sign language reading, and natural language processing.
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4. Deep Learning with Keras - PluralSight
This course on Deep Learning with Keras is Created by Jerry Kurata, Technology Expert and best selling author of Machine Learning and Deep Learning Courses on Pluralsight and Coursera.
This course will get you up to speed with both the theory and practice of using Keras to create powerful deep neural networks.
And equip you with the various methods of using Keras for interconnecting various layers of neurons quickly and easily to form the structure of your deep neural networks.
This course is suitable for learners with a good knowledge of Python to work with Keras and will help gain the skills required to effectively create deep neural networks through the course’s combination of lecture and hands-on coding.
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Continue reading this article "Deep Learning Courses" from the World-Class Educators.
You may also be interested in finding the Best TensorFlow Courses for Machine Learning and Deep Learning.
If you know of any courses that I may have missed, please let me know in the comments below!
If you found this post helpful enough, I have got two practical reads for you. One about A Beginner's Guide to Machine Learning with Python and one about the Best Courses in Machine Learning Courses on the Internet.