8 Best Deep Learning Courses to Grow Your Skillset

Deep learning—a branch of machine learning that uses artificial neural networks to learn how to perform tasks—is a powerful tool for solving real-world problems, from image recognition to natural language processing. And as more companies begin using artificial intelligence, demand for workers with deep learning skills will only increase. So if you’re interested in applying for jobs requiring these skills or simply want to increase your marketability as a data scientist, taking a deep learning course will help you stand out from the crowd.

However, with so many courses, how do you know which one to choose? That’s why we’ve compiled this guide. Below, we’ll cover the eight best deep learning courses and give an overview to help you decide which is best. Let’s dive right into it!

How Important Is a Deep Learning Course?

Deep learning courses will help you develop a critical eye for identifying problems and solutions, which is an essential skill for anyone who wants to work in this field. It’s a great way to get your foot in the door of the AI world, and will give you some extra skills to put on your resume.

Best Deep Learning Courses

Maybe you’re a beginner or an advanced practitioner looking to take your skillset to the next level. With so many options, it can be overwhelming to figure out which online courses are worth your time.

That’s why we’ve put together this list of the best deep learning courses for beginners and advanced students alike.

Data Science Career Track – Springboard

Rating

4.7 on SwitchUp

Overview

The Springboard Data Science Bootcamp is the best way to build your data science skills and machine learning skills on your own schedule. With Springboard’s flexible, remote program and one-on-one support at every step, you’ll graduate in six months, land your dream job, or receive a refund.

Springboard’s unique curriculum focuses on practical projects that teach the skills employers are looking for—like how to use Python for machine learning and analysis, how to clean and wrangle messy data, and how to build software from scratch—so you can show off what you’ve learned at career fairs. 

Best For

Before enrolling in the Data Science Bootcamp, you should have at least six months of coding experience with a programming language such as Python or Java.

You can also choose to enroll in this program if:

• You have the desire to work with data but don’t know where to start
• You want to work in the deep learning industry but don’t have a lot of experience
• You want to make a career change and are willing to put in the work

Duration

You’ll complete the course in about six months if you devote around 20 hours a week to studying and practicing.

Price

The Springboard Data Science Bootcamp pricing is pretty straightforward. If you pay upfront, you get a 13% discount and only pay $9,900. You can also choose to pay $1,890 in monthly installments or pay only after you land a job.

Deep Learning Specialization – DeepLearning.AI on Coursera

Rating

4.9 on Coursera

Overview

If you’ve ever wanted to learn the fundamentals of deep learning, this course is for you. The Deep Learning Specialization course from Coursera will teach you how to build and train neural networks—an exciting branch of machine learning that has recently made huge strides in computer vision, natural language processing, image recognition, and speech recognition.

You’ll also learn how to use deep learning algorithms like convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to solve problems in computer vision, natural language processing, speech recognition, and more.

Related Read: RNN vs. CNN: Which Neural Network Is Right for Your Project?

With a basic understanding of theory and practice, you can use what you learn in this course to build real-world solutions for complex problems in many fields.

Best For

The Deep Learning Specialization Course from Coursera is best for anyone who wants to learn more about the latest developments in artificial intelligence, as it gives you a practical introduction to machine learning. It’s also a great choice if you’re interested in applying your knowledge of deep learning in your own work or study.

The course is designed to be accessible to students at all levels, as it focuses on giving you a solid foundation of knowledge so that you can understand and apply deep learning concepts, even if you haven’t taken any related courses before.

However, you should have basic programming skills and basic knowledge of machine learning and programming languages such as Python.

Duration

The course takes approximately five months to complete, with around 9 hours of study per week.

Price

You can enroll for free and pay the $49 per month Coursera subscription fee after the 7-day free trial.

Stanford CS224N: Natural Language Processing with Deep Learning – Stanford Online on Youtube

Rating

N/A

Overview

If you’re looking for a free deep-learning course, look no further than Stanford University’s CS224N. This course is an online video series on YouTube that costs nothing. It covers key topics like convolutional neural networks, recurrent neural networks, and deep learning models—all essential to understanding how artificial intelligence works in today’s world.

The course covers a lot of ground—from the basics to more advanced topics like adversarial networks and word embeddings. You’ll also learn about loss function and optimization methods like backpropagation and stochastic gradient descent.

Best For

If you’re interested in how computers learn to recognize patterns in data—and how you can use them to solve problems that have traditionally been the domain of humans—this is the course for you.

Duration

The course consists of 23 video lectures between 1 and 2 hours each.

Price

The course is available for free on YouTube.

Deep Learning A-Z™: Hands-On Artificial Neural Networks (Udemy)

Rating

4.6 on Udemy

Overview

With the Deep Learning A-Z™ course from Udemy, you’ll learn to create deep learning algorithms using Python. You’ll be taught by machine learning and data science professionals with experience in machine learning and building real-world applications of artificial intelligence.

The course is practical, meaning that you’ll learn by doing. You’ll work through real-world examples and projects, each building on the last so that you can see how everything fits together.

Best For

This course is perfect for anyone looking to enter the field of data science or learn about new machine learning technologies that are changing the way we live and work. You should have basic Python knowledge and a deep understanding of mathematics.

Duration

You can go through this course at your own pace. It includes less than 23 hours of video content and downloadable resources and articles.

Price

Udemy offers this course at an 80% discount, meaning you only need to pay $16.99.

Intro to Deep Learning with PyTorch – Facebook Artificial Intelligence on Udacity

Rating

4.5 on Class Central

Overview

This course is designed to teach you how to implement your first deep neural network using PyTorch. You’ll learn the basics of deep learning frameworks and get practical experience by implementing various neural networks.

Throughout this course, you’ll learn how to use the PyTorch library to build neural networks: from basic feed-forward networks to convolutional networks, recurrent neural networks (RNNs), and more.

You’ll also learn how to set up your environment for deep learning using Jupyter Notebooks, an excellent tool for performing data science tasks on your computer. And you’ll spend some time looking at how you can use TensorBoard—a data visualization tool built into PyTorch—to understand what’s happening inside your network during training.

Best For

The Introduction to PyTorch course is best for students familiar with Python libraries and data processing.

Duration

It takes around two months to go through the course materials and graduate.

Price

The Introduction to PyTorch course is free to access.

Practical Deep Learning for Coders 2022 – fast.ai

Rating

3.8 on Class Central

Overview

The fast.ai Practical Deep Learning course is a hands-on introduction to applying deep learning to real-world problems. You’ll learn to deploy machine learning models and use PyTorch, the state-of-the-art open-source library for deep learning research and applications.

The course focuses on practical skills you can use on your own projects and share with the community on the forum at fast.ai. The fast.ai community is made up of practitioners from all over the world who support one another in their projects, so you’ll get feedback from expert practitioners and other learners.

Best For

This course is best for people with coding experience and deep learning practitioners alike.

Duration

The fast.ai course is broken down into nine lessons. Each lesson is approximately 90 minutes long, and the course takes around 10 hours to complete.

Price

The Practical Deep Learning course is free to access.

Deep Learning Prerequisites: Logistic Regression in Python (Lazy Programmer Inc. on Udemy)

Rating

4.7 on Udemy

Overview

The Deep Learning Prerequisites: Logistic Regression in Python on Udemy course is designed to help you learn how to use Python for data science. 

In this course, you will go through hands-on projects in real-time, so you can quickly gain the skills needed for your next job or project. You will also understand the basics of logistic regression algorithms, a prerequisite for many fundamental machine learning courses.

Best For

Before you take the Deep Learning Prerequisites: Logistic Regression in Python course, you should know some basic Python coding with the Numpy Stack. This includes derivatives, matrix arithmetic, and probability.

Duration

The course includes almost 7 hours of video content, so you can complete it at your own pace.

Price

The course costs $19.99.

Professional Certificate in Deep Learning – IBM on edX

Rating 

4.1 on Class Central

Overview

If you’re looking to get started with deep learning or just want to gain a basic understanding of machine learning, then the Professional Certificate in Deep Learning is for you. This deep learning program is designed to give professionals the skills they need to use deep learning algorithms in real-world scenarios. You will learn about the fundamentals of machine learning and its applications, as well as how to use popular deep learning libraries.

Best For

The course is designed for candidates familiar with Python and basic programming languages.

Duration

The course lasts for seven months, with 2 to 4 hours of study per week.

Price

The full program costs $525.60.

How Do You Choose a Deep Learning Course?

Here are some factors to consider when picking a deep learning course. 

Curriculum

The first thing to consider is the curriculum of the course. A good course will balance theory and practice and cover both supervised and unsupervised learning methods. It should also include practical examples to see how these methods work in real-life situations. Does the curriculum include courses that will help you reach your specific career goals? Do they cover all of the relevant topics? If not, you can always supplement with other classes or tutorials on YouTube or elsewhere online.

Career Goals

If you want to get into academia, look for courses emphasizing research. But if you wish to build a career in machine learning and become a data scientist, look for courses emphasizing practical applications of deep learning. And if you want to make some extra cash with freelancing gigs, look for courses that teach how to build self-sufficient projects using deep learning algorithms.

Expertise of Instructors

You want instructors who are deeply knowledgeable and passionate about their subject matter—and able to convey that passion in their teaching style. The best teachers know how to make learning fun but also challenge students with complex concepts so they can grow as learners and professionals.

Pricing and Payment Options

Some courses charge a flat fee for access to all lectures, while others charge per lecture. Paid courses almost always include a certificate that shows you’ve completed the course—this can be useful if you’re looking for a job in the field and need some kind of proof of your skillset.

Some courses also offer a free trial period so that you can try them before you buy. Just be sure that what they offer during this period matches what they promise in the full course (i.e., don’t expect to get all lectures for free if their website says otherwise).

Schedule

Online courses may be for you if you want a more hands-off learning experience! Many online courses allow students to work at their own pace, so even if your busy schedule doesn’t allow for much time spent in front of a computer screen every day, there are still options available for you.

Reputation

One important thing to remember is that not all courses are created equal. It’s essential to look at the reputation of the course provider before signing up for one of their courses, especially if it’s a paid course. 

Reputable providers will have positive reviews from previous students and be able to answer questions about their program thoroughly and honestly.

Projects and Practical Assignments

One thing distinguishing good machine learning courses from bad ones is the number of practical programming assignments and machine learning projects in each lesson. 

When choosing a course, make sure each lesson has at least one project or assignment to test what you’ve learned and see how it applies to real-world scenarios.

Making the Most Out of Your Deep Learning Course

There are many ways to make the most of your deep learning course. Here is what you should keep in mind.

Are There Any Prerequisites for a Deep Learning Course?

If you are taking a course focused on the foundations of deep learning, it’s not necessary to have any prior programming knowledge in this area. If you’re taking a course focused on applying deep learning techniques to solve specific problems, background knowledge will likely help you get the most out of your class.

Remember that some advanced courses may require you to have previous programming experience with Python or R—while others may not. So if you’re unsure whether or not a particular course requires such knowledge, check with your professor before enrolling.

What Should You Expect To Learn in a Deep Learning Course?

If you’re trying to decide whether or not to take a deep learning course, you should first check out what the course covers. It’s important to know what you’re signing up for. Here are some of the things you can expect to learn in a deep learning course:

• The basic concepts of machine learning and neural networks;
• How to build your own neural network using Python and TensorFlow;
• How to train your neural network using data and machine learning techniques like gradient descent and backpropagation.

What Will Your Schedule Look Like?

Depending on the course you are taking, your schedule will look different. For example, if you’re taking a short course that involves only 1-2 hours of study per week, your schedule would allow you to pursue a part-time job or full-time study.

However, if you are enrolled in a longer course that requires more time and effort, it may take more time to complete. Before registering, ensure you have enough time to fit your studies around other commitments such as work or family life.

FAQs About Deep Learning Courses

We’ve got the answers to your most frequently asked questions.

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