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Looking for ways to improve your TensorFlow machine learning skills?

As TensorFlow gains popularity, it has become imperative for aspiring data scientists and machine learning engineers to learn this open-source software library for dataflow and differentiable programming. However, finding the rightTensorFlow course that suits your needs and budget can be tricky.

In this article, we have rounded up the top 10 online free and paid TensorFlow courses that will help you master this powerful machine learning framework.

Lets dive into TensorFlow and see which of our top 10 picks will help you take your machine-learning skills to the next level.

This course from Udacity is available free of cost. The course has 4 modules, each teaching you how to use models from TF Lite in different applications. This course will teach you everything you need to know to use TF Lite for Internet of Things devices, Raspberry Pi, and more.

The course starts with an overview of TensorFlow Lite, then moves on to:

This course is ideal for people proficient in Python, iOS, Swift, or Linux.

Duration: 2 months

Price: Free

Certificate of Completion: No

With over 91.534 enrolled students and thousands of positive reviews, this Udemy course is one of the best-selling TensorFlow courses. This course was created by Jos Portilla. She is famous for her record-breaking Udemy course, The Complete Python 3 Bootcamp, with over 1.5 million students enrolled in it.

As you progress through this course, you will learn to use TensorFlow for various tasks, including image classification with Convolutional Neural Networks (CNN). Youll also learn how to design your own neural network from scratch and analyze time series.

Overall, this course is excellent for learning TensorFlow fundamentals using Python. The course covers the basics of TensorFlow and more and does not require any prior knowledge of Machine Learning.

Duration: 14 hrs

Price: Paid

Certificate of Completion: Yes

TensorFlow: Intro to TensorFlow for Deep Learning is third in our list of free TensorFlow courses one should definitely check out. This course includes a total of 10 modules. In the first part of the course, Dr. Sebastian Thrun, co-founder of Udacity, gives an interview about machine learning and Udacity.

Initially, youll learn about the MNIST fashion dataset. Then, as you progress through the course, youll learn how to employ a DNN model that categorizes pictures using the MNIST fashion dataset.

The course covers other vital subjects, including transfer learning and forecasting time series.

This course is ideal for students who are fluent in Python and have some knowledge of linear algebra.

Duration: 2 months

Price: Free

Certificate of Completion: No

This course from Coursera is an excellent way to learn about the basics of TensorFlow. In this program, youll learn how to design and train neural networks and explore fascinating new AI and machine learning areas.

As you train a network to recognize real-world images, youll also learn how convolutions could be used to boost a networks speed. Additionally, youll train a neural network to recognize human speech with NLP systems.

Even though auditing the courses is free, certification will cost you. However, if you complete the course within 7 days of enrolling, you can claim a full refund and get a certificate.

This course is for those who already have some prior experience.

Duration: 2 months

Price: free

Certificate of Completion: Yes

This is a free Coursera course on TensorFlow introduction for AI. To get started, you must first click on Enroll for Free and sign up. Then, youll be prompted to select your preferred subscription period in a new window.

There will be a button that says Audit the Course.. By clicking on the button, it will allow you to access the course for free.

As part of the first week of this course, Andrew Ng, the instructor, will provide a brief overview. Later, there will be a discussion about what the course is all about.

The Fashion MNIST Dataset is introduced in the second Week as a context for the fundamentals of computer vision. The purpose of this section is for you to put your knowledge into practice by writing your own computer vision neural network (CVNN) code.

Those with some Python experience will benefit the most from this course.

Duration: 4 months

Price: Free

Certificate of Completion: Yes

For those seeking TensorFlow Developer Certification in 2023, TensorFlow Developer Certificate in 2023: Zero to Mastery is an excellent choice since it is comprehensive, in-depth, and top-quality.

In this online course, youll learn everything you need to know to advance from knowing zero about TensorFlow to being a fully certified member of Googles TensorFlow Certification Network, all under the guidance of Daniel Bourke, a TensorFlow Accredited Professional.

The course will involve completing exercises, carrying out experiments, and designing models for machine learning and applications under the guidance of TensorFlow Certified Expert Daniel Bourke.

By enrolling in this 64-hour course, you will learn everything you need to know about designing cutting-edge deep learning solutions and passing the TensorFlow Developer certification exam.

This course is a right fit for anyone wanting to advance from TensorFlow novice to Google Certified Professional.

Duration: 64 hrs

Price: Paid

Certificate of Completion: Yes

This is yet another high-quality course that is free to audit. This course features a five-week study schedule.

This online course will teach you how to use Tensorflow to create models for deep learning from start to finish. Youll learn via engaging in hands-on programming sessions led by an experienced instructor, where you can immediately put what youve learned into practice.

The third and fourth weeks focus on model validation, normalization, The Hub Modules for Tensorflow, etc. And the final Week is dedicated to a Project for Capstone. Students in this course will be exposed to a great deal of hands-on learning and work.

This course is ideal for those who are already familiar with Python and understand the Machine learning fundamentals.

Duration: 26 hrs

Price: Free

Certificate of Completion: No

This hands-on course introduces you to Googles cutting-edge Deep Learning framework, TensorFlow, and shows you how to use it.

This program is geared toward learners who are in a bit of a rush to get to full speed. However, it also provides in-depth segments for those interested in learning more about the theory behind things like loss functions and gradient descent methods, etc.

This course will teach you how to build Python recommendation systems with TensorFlow. As far as the course goes, it was created by Lazy Programmer, one of the best instructors on Udemy for machine learning.

Furthermore, you will create an app that predicts the stock market using Python. If you prefer hands-on learning through projects, this TensorFlow course is ideal for you.

This is a fantastic resource for those new to programming and just getting their feet wet in the fields of Data Science and Machine Learning.

Duration: 23.5 hrs

Price: Paid

Certificate of Completion: Yes

This resource is excellent for learning TensorFlow and machine learning on Google Cloud. The course offers an advanced TensorFlow environment for building robust and complex deep models using deep learning.

People who are just getting started will find this course one of the most promising. It has five modules that will teach you a lot about TensorFlow and machine learning.

A course like this is perfect for those who are just starting.

Duration: 4 months

Price: Free

Certificate of Completion: Paid Certificate

This course, developed by Hadelin de Ponteves, the Ligency I Team, and Luka Anicin, will introduce you to neural networks and TensorFlow in less than 13 hours. The course provides a more basic introduction to TensorFlow and Keras than its counterparts.

In this course, youll begin with Python syntax fundamentals, then proceed to program neural networks using TensorFlow and Googles Machine Learning framework.

A major advantage of this course is using Colab for labs and assignments. The advantage of Colab is that students have less chance to make mistakes, plus you get an excellent, shareable online portfolio of your work.

This course is intended for programmers who are already comfortable working with Python.

Duration: 13 hrs

Price: Paid

Certificate of Completion: Yes

In conclusion, weve discussed 10 online free and paid TensorFlow courses that can help you learn and improve your skills in this powerful machine-learning framework. Weve seen that there are options available for beginners and more advanced users and that some courses offer hands-on projects and real-world applications.

If youre interested in taking your TensorFlow skills to the next level, we encourage you to explore some of the courses weve covered in this post. Whether youre looking for a free introduction or a more in-depth paid course, theres something for everyone.

So dont wait enroll in one of these incredibly helpful courses today and start learning TensorFlow!

And as always, wed love to hear your thoughts and experiences in the comments below. What other TensorFlow courseshave you tried? Let us know!

Online TensorFlow courses can be suitable for beginners, but some prior knowledge of machine learning concepts can be helpful. Choosing a course that aligns with your skill level and offers clear explanations of the foundational concepts is important. Some courses may assume prior knowledge of Python programming or linear algebra, so its important to research the course requirements before enrolling.

The duration of a typical TensorFlow course can vary widely, ranging from a few weeks to several months, depending on the level of depth and complexity. The amount of time you should dedicate to learning each Week will depend on the TensorFlow course and your schedule, but most courses recommend several hours of study time per Week to make meaningful progress.

Some best practices for learning TensorFlow online include setting clear learning objectives, taking comprehensive notes, practicing coding exercises regularly, seeking help from online forums or community groups, and working on real-world projects to apply your knowledge. To ensure youre progressing and mastering the concepts, track your progress, regularly test your understanding of the material, and seek feedback from peers or instructors.

Prerequisites for online TensorFlow courses may vary, but basic programming skills and familiarity with Python are often required. A solid understanding of linear algebra and calculus can help understand the underlying mathematical concepts. Some courses may also require hardware, such as a powerful graphics processing unit (GPU), for training large-scale deep learning models. Its important to carefully review the course requirements before enrolling.

Some online TensorFlow courses offer certifications upon completion, but there are no official degrees in TensorFlow. Earning a certification can demonstrate your knowledge and proficiency in the framework, which can help advance your career in machine learning or data science. However, its important to supplement your knowledge with real-world projects and practical experience to be successful in the field.

Link:
10 TensorFlow Courses to Get Started with AI & Machine Learning - Fordham Ram