Best Deep Learning Courses from World-Class Educators

Deep Learning involves techniques that can’t be understood without an effective teacher. I’ve taken many data science and Machine Learning related courses and audited portions of many more.

I know the options out there, and what skills are needed for learners preparing for a Data Scientist, Machine Learning Engineer or Deep Learning Scientist role.

So I started creating a review-driven guide that recommends the best courses for each subject within Deep Learning and for this guide, I put a tremendous amount of efforts trying to identify every best deep learning course.

I extracted key bits of information from their syllabus and compiling their ratings because techniques like Deep Learning, which underpin many of today’s AI tools, aren’t easy to grasp.

First off, you need to have a solid understanding of advanced mathematical concepts for deep learning. So, if you to want learn the basics or need a refresher, I’ve got you covered in this article about Maths for Machine Learning.

Deep learning offers enormous potential for creative applications and in this guide, for best Deep Learning Courses we interrogate what’s possible. So, without further ado, let’s get started !


The 5+ Best Deep Learning Courses from the World-Class Educators. 

These courses will prepare you for the Deep Learning role and help you learn more about artificial neural networks and how they’re being used for machine learning, as applied to speech and object recognition, image segmentation, modelling language, and human motion, and more.

Below, I’ve curated a selection of the best available courses in Deep Learning for beginners and experts who aspire to expand their minds.


Deep Learning in Python 

DataCamp Logo

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.

The topics in this course will mostly cover the basics of deep learning and neural networks. This course will 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.

Is it right for you?

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.

Deep Learning in Python

What you will learn?
  • Basics of deep learning and neural networks
  • Optimizing a neural network with backward propagation
  • Building deep learning models with keras
  • Fine-tuning keras models


— An Introduction to Practical Deep Learning

Intel AI DeveloperAn 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.

You will also learn to speed up your deep learning and accelerated computing applications for the development of self-driving cars, speech interfaces, genomic sequence analysis, and algorithmic trading.

Is it right for you?

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.

Introduction to Practical Deep Learning by Intel

What you will learn?
  • Introduction to Deep Learning and Deep Learning Basics
  • Convolutional Neural Networks (CNN), Fine-Tuning and Detection
  • Recurrent Neural Networks (RNN)
  • Training Tips and Multinode Distributed Training
  • Hot Research and Intel’s Roadmap
  • Final Quiz


Introduction to Deep Learning 

National Research University Higher School of Economics LOGOIntroduction to Deep Learning is an advanced 6-week course created by the National Research University Higher School of Economics. This course introduces learners to the basic understanding of modern neural networks and their applications in computer vision and natural language understanding.

The course starts with a recap of linear models and discussion of stochastic optimization methods that are crucial for training deep neural networks.

You will also learn to use popular building blocks to define complex modern architectures in TensorFlow and Keras frameworks.

Is it right for you?

This course is suitable for Developers, analysts, and researchers with the basic knowledge of Python, linear algebra and probability.

The topics covered in this course will help learners who are faced with tasks involving complex structure understanding such as image, sound and text analysis.

Introduction to Deep Learning

What you will learn?
  • Introduction to optimization
  • Introduction to neural networks
  • Deep Learning for images
  • Unsupervised representation learning
  • Deep learning for sequences
  • Final Project


— Deep Learning Specialization –  Highly Recommended 

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 you learn the foundations of Deep Learning, understand techniques to build effective neural networks, and learn how to manage successful machine learning projects.

You will master not only the theory but also see how it is applied in businesses with hand-on-practice in Python and TensorFlow.

Is it right for you?

If you are seeking an opportunity to build a deep learning project with cutting-edge, industry-relevant techniques, this specialization will help you do so.

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, sign language reading, music generation, and natural language processing.

Deep Learning Specialization

What you will learn?
  • Neural Networks and Deep Learning
  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization, and Optimization
  • Structuring Machine Learning Projects
  • Convolutional Neural Networks
  • Sequence Models


Deep Learning with Keras

Pluralsight LogoThis 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.

You will be equipped 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.

Is it right for you?

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.

Deep Learning with Keras

What you will learn?
  • Introduction to Deep Learning
  • Introduction to Keras, TensorFlow and Neural Networks
  • Introduction to Installation – TensorFlow and Keras
  • Creating your First Keras Neural Network
  • Conducting Models in Keras
  • Employing Layers in Keras Models
  • Building Convolutional NN with Keras
  • Implementing Recurrent Neural Nets with Keras
  • Using Specialty Layers and Functions


— Applied AI with Deep Learning 

IBM Logo

This course, Applied Artificial Intelligence with DeepLearning gives you easy access to the invaluable insights into Deep Learning models used by experts in Natural Language Processing, Computer Vision, Time Series Analysis, and many other disciplines.

You will learn about the fundamentals of Linear Algebra and Neural Networks and also we understand Anomaly Detection, Time Series Forecasting, Image Recognition and NLP by building up models using Keras one real-life examples from IoT, Financial Marked Data, Literature or Image Databases.

Is it right for you?

This course requires some background in programming, preferably Python and the basic understanding of math (linear algebra) is a plus.

This course is suitable for learners who want to master Deep Learning and learn to use the most popular Frameworks like Keras, TensorFlow, PyTorch, DeepLearning4J and Apache SystemML.

Deep Learning Course

What you will learn?
  • Introduction to deep learning
  • Deep learning frameworks
  • DeepLearning Applications
  • Scaling and Deployment


Thanks for making it to the end 🙂 

If you liked this article, I’ve got a few very practical reads for you. One about Best AI Courses from the World-Class Educators and one about The Best Machine Learning Courses on the Internet.

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