Are you looking for the best TensorFlow courses online?
With skills in TensorFlow, you’ll be able to build accurate and reliable neural networks. However, developing reliable neural networks can be challenging because the process often involves putting far too many factors into consideration.
It is for this reason that the best TensorFlow courses are key to building reliable AI models. With the right learning resources, you’ll quickly master the ins and outs of using TensorFlow, including shortcuts to speed up your design.
TensorFlow is a popular choice for learning artificial intelligence. The framework is backed by Google, so it receives regular updates and new features to ensure seamless performance. Moreover, TensorFlow offers robust debugging capabilities.
In this guide, I’ll take you through the best TensorFlow courses online to complete in 2023 if you’d like to build powerful neural networks that scale.
Let’s get started.
1. Complete Guide to TensorFlow for Deep Learning with Python [Udemy]
Would you like to learn how to build an image classifier?
Then this may be the course to get you started.
By taking this course you’ll be able to:
- Create, train, and evaluate a neural network model using TensorFlow. This neural network will be able to classify images, and can be used for document sorting, among other applications.
- Learn how to use OpenAI Gym to implement reinforcement learning, making this the best TensorFlow course online for solving complex challenges.
- Know how to work around the common challenges of unsupervised machine learning by using autoencoders.
Unfortunately, this TensorFlow training targets learners already familiar with Python programming. Even so, it’s still one of the best TensorFlow courses on Udemy because it contains crash courses on common Python libraries like Panda, Sci-kit learn, and Numpy.
2. Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning [Coursera]
Packed with TensorFlow best practices, this TensorFlow training takes your knowledge of artificial intelligence to the next level with deep learning.
Taking this course will teach you:
- Cross-platform coding knowledge that you can use for TensorFlow 1.x as well as TensorFlow 2.0 alpha. So this is the best TensorFlow course on Coursera for mastering both versions.
- You’ll get to learn about the top artificial intelligence trends to tap into for modern AI-based applications, such as building a computer vision model for image classification.
- Tips on enhancing the performance of the neural networks you’ll build through convolutions.
Being a basic level introduction with a focus on Keras, this TensorFlow course may seem superficial if you’re an intermediate learner. However, you also get to build a couple of complex convolution neural networks, so it does have its appeal to intermediate learners as well.
3. Building and Deploying Deep Learning Applications with TensorFlow [LinkedIn Learning]
Would you like to deploy your ML models to the cloud?
Then this is the TensorFlow training to take as it covers:
- Using TensorBoard to visually track accuracy and loss, making this one of the best TensorFlow courses online for visual machine learning experimentation.
- Calling the machine learning model you’ll build from any program after you’ve deployed it to the cloud. Moreover, you’ll also learn about local deployment.
- Creating and training deep learning models, complete with shortcut tips. If you want to build ML models fast, then this is the best TensorFlow course on LinkedIn Learning.
Given that the course is a little outdated, you may have trouble configuring your new Google Cloud account. However, this is not a point of focus for the course, but rather an important sidestep. What’s more, you can fix this with a simple internet search.
4. TensorFlow: Getting Started [PluralSight]
From simple linear regression models to advanced deep learning neural networks, this is the TensorFlow course to take you from beginner to expert.
The tutorial discusses:
- The gradient descent technique of optimization for building machine learning models when it’s hard to calculate parameters analytically. Consequently, you’ll deal with the underlying problems behind some of the biggest artificial intelligence failures.
- Simple and deep MNIST datasets so you can learn to build a range of simple and complex machine learning models.
- Transfer learning with TensorFlow, making it the best TensorFlow course on PluralSight for shortcuts on building sophisticated deep learning models.
Given that the course was released a while ago, it focuses on the older version of TensorFlow (1.0). That said, it is still the best TensorFlow course online because migrating to TensorFlow 2.0 is easily manageable once you’re familiar with coding in TensorFlow.
5. A Complete Guide on TensorFlow 2.0 Using Keras API [Udemy]
With this TensorFlow tutorial, you’ll get to use real-world data to build a stock market trading bot through reinforcement learning.
The course also covers:
- The transition from TensorFlow 1.0 to 2.0. As a result, this is the best TensorFlow course on Udemy if you have some experience with TensorFlow 1.0.
- Carrying out data preprocessing using TensorFlow data validation. This way, you can ensure your models feed on quality data.
- A concise course structure with excellent visualization in terms of slides and other graphic details. It is, therefore, one of the best TensorFlow courses online if you’re a visual learner.
This TensorFlow training assumes basic Python scripting skills, so you may want to check out the best Python courses online if you need to quickly brush up.
However, if you’re familiar with Python, you can quickly get into advanced neural network techniques without spending any time on syntax and theory.
6. DeepLearning AI TensorFlow Developer Professional Certificate [Coursera]
For aspiring professional developers, this 4-part TensorFlow specialization will set you on the right career path.
Some course highlights include:
- Using real-world data to develop a sunspot prediction model. This reinforces the theory of solving forecasting problems using time series.
- Exploring important techniques like data augmentation to prevent models from overfitting on training data sets. Consequently, this is one of the best TensorFlow courses on Coursera for building reliable models.
- Transfer learning concepts and how you can transfer features between your ML models to give your new projects a head start.
Being an intermediate-level TensorFlow course, a foundation in machine learning is essential. So you may want to tap into the best resources for learning machine learning first.
If you fit the prerequisite, you’ll find that the specialization develops a highly practical approach to deep learning and offers many projects.
7. Deep Learning Foundations: Natural Language Processing with TensorFlow [LinkedIn Learning]
If you want an ultra-modern TensorFlow course on natural language processing, this may just be the perfect fit.
Benefits of this TensorFlow tutorial include:
- 3 video previews on important topics, including tokenization on TensorFlow, to make it one of the best TensorFlow courses on LinkedIn Learning if you’d like to test-drive the training.
- A recently updated course outline to tap into the latest features of TensorFlow 2.0, to save time on coding, and other shortcomings arising from TensorFlow 1.0.
- Tons of practical work on building models. You’ll get to build a text classifier and a movie classification system using TensorFlow.
While course support could be better for the tutorial, it is still the best TensorFlow course online for natural language processing. That’s because it covers advanced text generation techniques with RNNs, and the student-fueled forum offers abundant help.
8. Understanding the Foundations of TensorFlow [PluralSight]
This TensorFlow tutorial uncovers machine learning models from a mathematical perspective to better understand what makes ML algorithms tick.
The course covers:
- Computational graphs in deep learning, and how you can easily derive the variables you need for backpropagation. It is for this reason that this is one of the best TensorFlow courses online to learn neural network finetuning.
- K-nearest neighbors algorithms, which prove useful because they can do both classification and regression, and work well with noisy data.
- A crash course on TensorFlow and Numpy, making it one of the best TensorFlow courses on PluralSight for bonus content on Python.
With a comprehensive section on solving math functions, this TensorFlow requires a background in statistics, which you can get via the best statistics courses online.
The great thing about this mathematical approach is that you get to understand how advanced ML modeling techniques work under the hood.
9. Modern Deep Learning in Python [Udemy]
With up to 5 modern deep learning libraries for you to learn from, this course is packed full of value.
Course highlights include:
- Using libraries such as Theano, CNTIK, Keras, and others. This is therefore the best TensorFlow course on Udemy to learn about today’s many important deep learning libraries.
- Learning how to set up a GPU instance on AWS so you can take advantage of your computer’s advanced hardware to speed up training.
- A concise and systematic approach to choosing hyperparameters and techniques you can use to reduce the risk of overfitting.
A little familiarity with Matplotlib and Python is an important prerequisite for this course. Armed with knowledge on gradient descent and backpropagation, this is the best TensorFlow course online to learn how to improve various aspects of data science.
10. TensorFlow 2 for Deep Learning Specialization [Coursera]
This 3-part specialization will introduce you to the deep learning framework of TensorFlow 2 before taking it up a notch with probabilistic deep learning.
It is one of the best TensorFlow courses online because of:
- An excellent teaching style by a top instructor. You’ll master TensorFlow 2 with plenty of hands-on projects for self-assessment, which is the best way to learn machine learning in 2021.
- An updated course outline using the latest version of TensorFlow, making this an excellent modern course where you won’t have to deal with deprecated features.
- Due to its approach to building complex model architectures using lower-level APIs, it’s the best TensorFlow course on Coursera for beginners.
The only downside is that the peer-graded assignment may take a while to reflect. Other than that, this specialization is perfect for learning TensorFlow 2 and a little bit of Python 3.
For a quick crash course on using TensorFlow with Java, this course will show you the way in under one hour.
You’ll get to learn about:
- Leveraging Java knowledge to see through a full project from importing data sets to training your model. As a result, it is the best TensorFlow course on LinkedIn Learning if you have experience with Java development.
- Although the instructor uses Visual Studio Code, he also demonstrates how you can also use other code editors across Windows and Mac.
- Advanced TensorFlow topics such as how to use Python-based models in JS, so you also get exposure to another excellent programming language for web development.
12. Build, Train, and Deploy Your First Neural Network with TensorFlow [PluralSight]
This TensorFlow 2.0 training teaches how to harness the power of machine learning and build better client applications.
The course covers:
- A breakdown of how neural networks are powering some of the top digital transformation trends today, so you can understand the math and concept behind some of these powerful models.
- The use of Google Colab to create machine learning models despite limited computational power on a PC. This makes it one of the best TensorFlow courses on PluralSight if your hardware struggles with huge data sets.
- TensorBoard best practices for visually tracking the performance of the models you’ll build and identifying areas you can improve.
This is a beginner-friendly course so intermediate learners may feel a little underwhelmed by some of the exercises. However, even for advanced learners, it is still the best TensorFlow course online because there are a few advanced topics covered such as calling models via the web.
13. Tensorflow 2.0: Deep Learning and Artificial Intelligence [Udemy]
If you’re keen to create powerful deep learning systems, such as a stock prediction platform, without too much coding work, this may be the course for you.
Some course highlights include:
- Learning to use TensorFlow Serving to create optimized machine learning models that thrive in a production environment.
- If you have some experience with TensorFlow 1.x, this is one of the best TensorFlow courses on Udemy that will show you how you can convert code to TensorFlow 2.0.
- Additionally, you get a free NumPy course, which you can redeem in the FAQ section of this course.
If you’re new to Python and NumPy, you may find this course may not offer a theory-dense course if that’s an important requirement. It instead focuses a lot more on building projects like recommender systems, so it’s one of the best TensorFlow courses online for applied learning.
14. TensorFlow: Advanced Techniques Specialization [Coursera]
This specialization will give you the skills to build machine learning models through four hands-on courses.
By the end of it, you’ll be able to:
- Work in different training environments with varying CPU resources, making this one of the best TensorFlow courses on Coursera for creating models that can perform reliably everywhere.
- Gauge how your model is performing by building and using custom loss functions, so you can help your neural network to learn better.
- Create simple autoencoders for MSINT datasets. Due to unsupervised machine learning, this will enable you to avoid the work of labeling data.
In the first course, there are a few audio issues to watch out for in terms of background noise. However, it’s nothing too major as the audio is fairly audible in this part, and there are also transcripts to help out if need be.
15. Building Deep Learning Applications with Keras 2.0 [LinkedIn Learning]
If you’d like to get acquainted with deep learning applications fast, this quick TensorFlow crash course is an excellent choice.
Course highlights include:
- Learning how to use Keras and libraries such as Theano to build deep learning models via a simple programming interface. It is therefore the best TensorFlow course online to learn about neural networks without coding experience.
- Uploading Keras models to Google cloud so you can be able to call your model from within any program.
- Data transference tips to efficiently combine TensorFlow and Keras features, making it one of the best TensorFlow courses on LinkedIn Learning for value.
You may run into installation problems when installing Keras on Windows due to changed web domain names. The great thing is that you can easily get past this process with the official TensorFlow website guide.
Best Ruby Courses
Would you like to build neural networks on TensorFlow 1.0?
Then you’ll find that the Complete Guide to TensorFlow for Deep Learning with Python is a great option.
Even though we’re in version 2 now, it remains one of the best TensorFlow courses online to complete in 2021 for mastering important foundational concepts.
If you’re already familiar with the first version, or would simply like to straight away get into TensorFlow 2.0, then you may want to try out the Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning course.
It builds cross-version coding skills to accommodate those new to TensorFlow 2.0 and also TensorFlow 1.0 intermediate learners.
Lerma is our expert in online education with over a decade of experience. Specializing in e-learning and e-courses. She has reviewed several online training courses and enjoys reviewing e-learning platforms for individuals and organizations.