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Today we’re looking at the best deep learning courses of this year.

**🧠 Did you know?** According to AI Multiple, deep learning, machine learning and NLP are the most in-demand skills on Monster.com.

**What is deep learning?**

Deep learning is a subset of machine learning where machines have the ability to learn. It uses a series of artificial neural networks to simulate the learning style of the human brain. 🤯

**Is deep learning for beginners?**

Deep learning is typically for beginners experienced with programming languages and math. But for more advanced deep learning concepts, you’ll need to know algorithms and frameworks.

**How long does it take to learn deep learning?**

It all depends.

**Deep learning isn’t easy.**

Students typically learn at different paces. It also depends on how much time you spend on learning deep learning.

That said, with the right learning materials, you can become a master of deep learning ASAP.

So today we’re showing you the best deep learning courses we could find.

*This post contains affiliate links. I may receive compensation if you buy something. Read my disclosure for more details.*

**TLDR: Best Deep Learning Courses****🔥 Best Overall 🔥****A Beginner’s Guide to Deep Learning: Educative.io****💥 Best for Newbies 💥****Introduction to Deep Learning with Python: DataCamp****💸 Best Value 💸****Build Deep Learning Models with TensorFlow Skill Path: Codecademy Pro**

**Best Deep Learning Courses: At A Glance**

Interactive or video-based learning | Community | Duration | Level | Certificate | Cost | |

A Beginner’s Guide to Deep Learning: Educative.io | Interactive | See below | 20 hours | Beginner | ✅ | $59 per month / $199 per year |

Introduction to Deep Learning with Python: DataCamp | Both | ✅ | 4 hours | Beginner | ✅ | $25 per month |

Introduction to Deep Learning with PyTorch: DataCamp | Both | ✅ | 4 hours | Beginner | ✅ | $25 per month |

Introduction to Deep Learning with Keras: DataCamp | Both | ✅ | 4 hours | Beginner | ✅ | $25 per month |

Deep Learning: The Big Picture: Pluralsight | Video | ❌ | 1.5 hours | Beginner | ✅ | $29 per month |

Build Chatbots with Python Skill Path: Codecademy Pro | Both | ✅ | 8 weeks | Beginner | ✅ | $39.99 per month / $239.88 per year |

Build Deep Learning Models with TensorFlow Skill Path: Codecademy Pro | Both | ✅ | 3 months | Beginner | ✅ | $39.99 per month / $239.88 per year |

Deep Learning Specialization: Coursera | Video | ✅ | 4 months | Intermediate | ✅ | $49 per month |

**1. A Beginner’s Guide to Deep Learning: Educative.io**

💰 **Price:** $69 per year for the course // $59 per month or $199 per year for all courses on **Educative.io**

⏲️ **Duration:** 20 hours

📉 **Level:** Beginner

🖥️ **Format:** Interactive learning

🎖️ **Certificate:** Yes

**Prerequisites: Python**

👍 *Check out what we think of Educative in our article Is Educative Worth It?*

You should be familiar with Python before taking this course.

### ➡️ **A Beginner’s Guide to Deep Learning is one of the best deep learning courses this year.**

First you’ll learn about the fundamental concepts and terminologies commonly found in deep learning. Then you’ll explore deep learning techniques.

You’ll look at both simple and complex deep learning models. And with hands-on exercises, you’ll discover how to code them in Python libraries NumPy and Keras.

💡 *A Python library is a set of functions that eliminates the need to write code from scratch. They’re vital for data science, machine learning and yes, deep learning.**There are over 137,000 Python libraries in existence.*

**Course Layout**

**Educative.io** has an interactive learning environment where you’ll do all work in the same browser. In **A Beginner’s Guide to Deep Learning**, you’ll find:

✅ 57 coding playgrounds

✅ 13 challenges

✅ 20 quizzes

And 214 illustrations.

With 9 modules, you’ll learn about:

✅ simple perceptron models in NumPy

✅ towards deep neural networks in NumPy

✅ building machine learning models with Keras

And beyond.

Each module has a series of lessons and exercises. For example, in the module **Fine-Tune Keras Model**, you’ll find:

✅ an introduction to model optimization

✅ 2 challenges with solution reviews

✅ model validations and capacity

Finally at the end of the course, you’ll tackle two exams: Deep Learning in NumPy and Deep Learning in Keras. These assessments contain multiple choice, match and write-the-code questions.

**Projects**

There are two projects in **A Beginner’s Guide to Deep Learning**:

1️⃣ Build a letter classification model

2️⃣ Build a digit recognition model

**Community**

**Educative.io** has a community board where you can get help from teachers and other students.

**2. Introduction to Deep Learning with Python: DataCamp**

💰 **Price:** $25 per month for all courses and Learning Paths / $33.25 per month for all courses, Learning Paths and projects

⏲️ **Duration:** 4 hours

📉 **Level:** Beginner

🖥️ **Format:** Video and Interactive Learning

🎖️ **Certificate:** Yes

**Prerequisites: Python**

*Want to know why we think DataCamp is so awesome? Read our DataCamp Full Review.*

Introduction to **Deep Learning with Python** is similar to **A Beginner’s Guide to Deep Learning**. But you’ll also find some videos in this course.

### ➡️ **DataCamp has some of the best deep learning courses you’ll find. **

We could go on and on about its interactive learning environment, data science-centered curriculum and abundance of exercises. But we just don’t have enough space here.

**Introduction to Deep Learning with Python** offers hands-on teaching where you’ll learn how to use Keras 2.0, a Python library.

**Course Layout**

**DataCamp** has an interactive learning environment where you’ll do all work inside the same browser. One of the nice things about **DataCamp’s** code editor is that it comes in dark mode.

You’ll also find some videos that introduce or clarify concepts.

**Introduction to Deep Learning with Python** has four modules:

✅ Basics of deep learning and neural networks

✅ Optimizing a neural network with backward propagation

✅ Building deep learning models with keras

✅ Fine-tuning keras models

Each module has a series of lessons, videos, exercises and quizzes. For example, in **Fine-Tuning Keras Models**, you’ll watch videos about model optimization, model validation and model capacity.

Then you’ll work on exercises related to changing optimization patterns and adding layers to a network, to name a few.

**Projects**

There are no projects in **Introduction to Deep Learning with Python**. Rather, you’ll work on a series of exercises throughout the course.

In addition, you’ll find plenty of projects with a Premium **DataCamp** subscription.

**Community**

**DataCamp** has a community where you’ll find a community forum, news and more.

💡*There’s also a Trello board where you can see upcoming courses.*

**3. Introduction to Deep Learning with PyTorch: DataCamp**

💰 **Price:** $25 per month for all courses and Learning Paths / $33.25 per month for all courses, Learning Paths and projects

⏲️ **Duration:** 4 hours

📉 **Level:** Beginner

🖥️ **Format:** Video and interactive learning

🎖️ **Certificate:** Yes

**Prerequisites: Python**

Unlike **Introduction to Deep Learning with Python**, **Introduction to Deep Learning** will take you on a journey through PyTorch instead of Python.

💡 **PyTorch** is a leading Python deep learning framework. It’s considered powerful and easy to use.

We recommend this course for students interested in learning deep learning through the lens of a Python library.

In **Introduction to Deep Learning with PyTorch**, you’ll learn about the fundamentals of neural networks. You’ll even build your own neural network that predicts digits from a dataset.

**Course Layout**

**DataCamp** has an interactive learning environment that is sprinkled with videos to clarify concepts. You’ll do all work within the browser.

**Introduction to Deep Learning with PyTorch** has 4 modules:

✅ Introduction to PyTorch

✅ Artificial Neural Networks

✅ Convolutional Neural Networks (CNNs)

✅ Using Convolutional Neural Networks

Each module has a series of lessons, videos, exercises and quizzes. For example, in **Artificial Neural Networks**, you’ll learn about activation and loss functions, preparing a dataset in PyTorch and training neural networks.

Then you’ll work on exercises such as calculating loss function in PyTorch and preparing MNIST datasets.

**Projects**

There aren’t any projects in Introduction to **Deep Learning with PyTorch**. However, you’ll find plenty of stimulating challenges throughout the course.

**Community**

**DataCamp** has a robust community with news, a community board and more. They also have a Trello board.

**4. Introduction to Deep Learning with Keras: DataCamp**

💰 **Price:** $25 per month for all courses and Learning Paths / $33.25 per month for all courses, Learning Paths and projects

⏲️ **Duration:** 4 hours

📉 **Level:** Beginner

🖥️ **Format:** Video and interactive learning

🎖️ **Certificate:** Yes

**Prerequisites: Python**

💡 **Keras** is a deep learning Python API that makes it easier to develop deep learning models.

So like **Introduction to Deep Learning with PyTorch**, you’ll learn a specific library for deep learning instead of general Python.

In **Introduction to** **Deep Learning with Keras**, you’ll work on stimulating exercises.

For example, you’ll use regression to predict asteroid trajectories.

Then, you’ll use binary classification to differentiate real and fake money.

You’ll also use multiclass classification to choose who threw a dart 🎯, and use neural networks to reconstruct busy images.

**Course Layout**

**DataCamp** has an interactive learning environment where you’ll do all work within the same browser. In addition, you’ll find occasional videos to introduce new concepts.

**Introduction to Deep Learning with Keras** has 4 modules:

✅ Introducing Keras

✅ Going Deeper

✅ Improving Your Model Performance

✅ Advanced Model Architectures

Each module contains lessons, exercises, videos and quizzes. For example, in the module **Introducing Keras**, you’ll learn about neural networks.

Then you’ll work on exercises like counting parameters and specifying a model.

**Projects**

There aren’t any projects in Introduction to **Deep Learning with Keras**. But you’ll work on plenty of exercises throughout the course.

**Community**

**DataCamp** has a strong community that contains a community board, news, and more.

They also have a Trello board for upcoming courses.

**5. Deep Learning: The Big Picture: Pluralsight**

💰 **Price:** $29 per month for standard courses and Learning Paths // $45 per month for advanced courses

⏲️ **Duration:** 1.5 hours

📉 **Level:** Beginner

🖥️ **Format:** Video

🎖️ **Certificate:** Yes

**Prerequisites: Python**

**Pluralsight** is unique because it’s the only platform on our list of best deep learning courses that is exclusively video-based.

In **Deep Learning: The Big Picture**, you’ll learn how to get started in the intimidating world of deep learning. You’ll learn the *basics* of what deep learning is, how it works, and where to get started.

This course is only an hour and a half. So if you have a short attention span, this course could be for you.

*But because this course is so basic, we recommend pairing it with another more in-depth course like A Beginner’s Guide to Deep Learning on Educative.io.*

You’ll also learn about using TensorFlow and the Microsoft Cognitive Toolkit to create deep neural networks.

Next you’ll learn how deep neural networks are trained. Finally, you’ll learn deep learning concepts and technologies.

**Course Layout**

**Pluralsight** is a video-based platform, so you’ll do all work outside of the browser. But not to worry; they’ll show you how to set everything up.

There are 6 modules in **Deep Learning: The Big Picture**:

✅ Deep Learning

✅ Techniques

✅ Applications

✅ Impact

And beyond.

Each module contains a series of lessons that dig deeper into concepts. For example, in **Techniques**, you’ll learn about different types of neural networks:

✅ fully connected

✅ convolutional

✅ recurrent

✅ generative adversarial

Then you’ll touch on deep reinforcement learning.

**Projects**

There aren’t any projects in **Deep Learning: The Big Picture**. For that reason, we recommend pairing it with another course.

**Community**

**Pluralsight** doesn’t have a community, though they do recommend students form guilds. ⚔️

**6. Build Chatbots with Python Skill Path: Codecademy Pro**

💰 **Price:** $39.99 per month or $239.88 ($19.99/mo) for all courses and Learning Paths

⏲️ **Duration:** 8 weeks

📉 **Level:** Beginner

🖥️ **Format:** Interactive learning and video

🎖️ **Certificate:** Yes

**Prerequisites: Python**

**Build Chatbots with Python **is a bit different than the rest of our best deep learning courses.

Instead of one course, it’s a combination of multiple courses called a Skill Path. As a result, it usually takes a few months to complete.

In **Build Chatbots with Python**, you don’t need linear algebra to create chatbots. Instead, you’ll learn Python from scratch to create chatbots that *teach themselves*. 😲

**Course Layout**

Similar to **Educative.io** and **DataCamp**, **Codecademy** has an interactive learning environment where you’ll do all work within the browser. But you’ll also find occasional videos to introduce or clarify concepts.

There are 6 modules in **Build Chatbots with Python** that function as complete courses:

✅ Introduction to Python and Chatbots

✅ Python Data Structures and Loops

✅ Rule-Based Chatbots

✅ Retrieval-Based Chatbots

✅ Deep Learning and Generative Chatbots

✅ Capstone Project

Each module is filled with lessons, quizzes and exercises. For example, in **Module 5**, you can expect to build an open-domain chatbot.

**Projects**

**Codecademy** courses and Learning Paths are always plum-full of mini-projects. So you’ll be working on tons of them throughout the **Build Chatbots with Python**.

In addition, you’ll work on a capstone project on your local machine (this is very rare for **Codecademy**… usually all work is done in the browser) where you can choose between retrieval-based or generative chatbot models.

**Community**

**Codecademy** has a community where you can get help, share your projects, and chat with other students.

**7. Build Deep Learning Models with TensorFlow Skill Path: Codecademy Pro**

💰 **Price:** $39.99 per month or $239.88 ($19.99/mo) for all courses and Learning Paths

⏲️ **Duration:** 3 months

📉 **Level:** Beginner w/experience in Python, NumPy and machine learning

🖥️ **Format:** Interactive learning and video

🎖️ **Certificate:** Yes

**Prerequisites: Python**

💡 **TensorFlow** is a Python library used for fast numerical computing. It was created by Google.

**Build Deep Learning Models with TensorFlow** is another Skill Path that is expected to take several months to complete.

Using TensorFlow, Keras and Python, you’ll learn how to train, test and tune deep learning models… All without having to know advanced math.

**Course Layout**

**Build Deep Learning Models with TensorFlow** has 7 modules that function as individual courses:

✅ Welcome

✅ Foundations of Deep Learning and Perceptrons

✅ Getting Started with TensorFlow

✅ Classification

✅ Deep Learning in the Real World

✅ Deep Learning Portfolio Project

✅ Next Steps

Each module contains a series of lessons, mini-projects and quizzes. For example, in **Module 3**, you’ll learn how to build your own neural networks using TensorFlow.

**Projects**

You’ll work on tons of mini-projects throughout **Build Deep Learning Models with TensorFlow**.

**In addition, you’ll work on a large portfolio-ready deep learning project.**

**Community**

**Codecademy’s** community allows you to get help, share your projects, and chat with other students.

**8. Deep Learning Specialization: Coursera**

💰 **Price:** $49 per month

⏲️ **Duration:** 4 months

📉 **Level:** Intermediate

🖥️ **Format:** Video

🎖️ **Certificate:** Yes

**Prerequisites: Python**

**Coursera** is similar to **Pluralsight** because of all the videos you’ll find. However, you’ll also find readings and quizzes on the **Coursera** platform.

**Deep Learning** is a Specialization, which is **Coursera’s** version of a Learning Path. Instead of one course, there are multiple.

In this Specialization, you’ll use Python and TensorFlow to build neural network architectures such as CNNs and recurrent neural networks. In addition, you’ll work on real-world case studies related to:

✅ autonomous driving

✅ reading sign language

✅ generating music

✅ computer vision

✅ speech recognition

✅ natural language processing

You’ll also get advice from deep learning experts in the industry.

**Course Layout**

**Coursera** is a video-based learning platform. But you’ll also find plenty of readings and quizzes.

The **Deep Learning** Specialization contains 5 modules:

✅ Neural Networks and Deep Learning

✅ Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

✅ Structuring Machine Learning Projects

✅ Convolutional Neural Networks

✅ Sequence Models

Each module has a cluster of lessons broken down by week. For example, in the course **Convolutional Neural Networks** you’ll find 14 videos, 2 readings and 3 quizzes in **Week 3: Object Detection**.

**Projects**

You’ll find one major project in the **Deep Learning** Specialization. In the third course, you’ll build a machine learning project.

It’s here where you’ll build and train deep neural networks, train and develop test sets to analyze bias for deep learning applications, build a CNN and more.

**Community**

There are forums within courses and Specializations on **Coursera** where you can get help from instructors (for a fee), mentors and other students.

**Best Deep Learning Courses: Conclusion**

Now let’s recap.

**Today we looked at the best deep learning courses available, but three came out on top:**

**Best Overall****A Beginner’s Guide to Deep Learning: Educative**

**Best for Newbies****Introduction to Deep Learning with Python: DataCamp**

**Best Value****Build Deep Learning Models with TensorFlow Skill Path: Codecademy Pro**

So whether you’re looking for the best overall, are just getting started, or need a good value, we think these are the best deep learning courses around.

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