Best Online Courses to Learn TensorFlow from Scratch

TensorFlow is an open-source machine learning framework developed by Google Brain, designed to facilitate the creation and deployment of machine learning models. With its computational graph abstraction, TensorFlow allows users to define complex mathematical operations as nodes in a graph, enabling efficient execution across CPUs, GPUs, or even specialized hardware like TPUs. Its extensive ecosystem provides tools for various tasks, including data preprocessing, model training, and deployment. TensorFlow’s flexibility and scalability make it popular among researchers and developers for a wide range of applications, from image recognition and natural language processing to reinforcement learning and beyond.

Are you interested in mastering TensorFlow? We’ve compiled a collection of TensorFlow tutorials tailored to cater to learners at all levels, whether you’re just starting out, have some experience, or consider yourself an expert. These tutorials are designed to guide you through the fundamentals of TensorFlow, equipping you with the knowledge and skills needed to build and deploy machine learning models effectively. Whether you’re a beginner, intermediate learner, or seasoned professional, these resources will help you navigate the intricacies of TensorFlow and unlock its full potential.

Intro to TensorFlow

What you’ll learn

• Create machine learning models in TensorFlow
• Use the TensorFlow libraries to solve numerical problems
• Troubleshoot and debug common TensorFlow code pitfalls
• Use tf.estimator to create, train, and evaluate an ML model
• Train, deploy, and productionalize ML models at scale with Cloud ML Engine

Duration: Approx. 13 hours
Rating: 4.5 (2,047 ratings) out of 5
Trainer: Google Cloud Training
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Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization

What you’ll learn

• hands-on experience optimizing, deploying, and scaling production ML models of various types in hands-on labs
• how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text

Duration: Approx. 50 hours
Rating: 4.5 (2,626 ratings) out of 5
Trainer: Google Cloud Training
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Machine Learning with TensorFlow on Google Cloud Platform Specialization

What you’ll learn

• Learn how to write distributed machine learning models that scale in Tensorflow, scale out the training of those models
• Convert raw data to features in a way that allows ML to learn important characteristics from the data and bring human insight to bear on the problem
• Learn how to incorporate the right mix of parameters that yields accurate, generalized models and knowledge of the theory to solve specific types of ML problems

Duration: Approx. 40 hours
Rating: 4.5 (12,782 ratings) out of 5
Trainer: Google Cloud Training
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DeepLearning.AI TensorFlow Developer Professional Certificate

What you’ll learn

• Best practices for TensorFlow, a popular open-source machine learning framework to train a neural network for a computer vision applications.
• Handle real-world image data and explore strategies to prevent overfitting, including augmentation and dropout.
• Build natural language processing systems using TensorFlow.
• Apply RNNs, GRUs, and LSTMs as you train them using text repositories.

Duration: Approx. 50 hours
Rating: 4.7 (22,340 ratings) out of 5
Trainer: Laurence Moroney
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TensorFlow: Data and Deployment Specialization

What you’ll learn

• Run models in your browser using TensorFlow.js
• Prepare and deploy models on mobile devices using TensorFlow Lite
• Access, organize, and process training data more easily using TensorFlow Data Services
• Explore four advanced deployment scenarios using TensorFlow Serving, TensorFlow Hub, and TensorBoard

Duration: Approx. 40 hours
Rating: 4.4 (480 ratings) out of 5
Trainer: Laurence Moroney
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FREE: Tensorflow 2.0 | Recurrent Neural Networks, LSTMs, GRUs

What you’ll learn

• RNN
• LSTM
• GRU
• NLP
• Seq2Seq
• Attention
• Time series

Duration: 1hr 1min
Rating: 4.1 (65 ratings) out of 5 
Trainer: Jad Slim
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TensorFlow Developer Certificate in 2024: Zero to Mastery

What you’ll learn

• TensorFlow Fundamentals
• Neural Network Regression with TensorFlow
• Neural Network Classification with TensorFlow
• Computer Vision and Convolutional Neural Networks with TensorFlow
• Transfer Learning with TensorFlow Part 1: Feature Extraction, Fine-tuning & Scaling Up
• NLP Fundamentals in TensorFlow
• Time Series fundamentals in TensorFlow

Duration: 63 hrs
Rating: 4.7 (2531 ratings) out of 5 
Trainer: Andrei Neagoie
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Complete Tensorflow 2 and Keras Deep Learning Bootcamp

This course covers a variety of topics, including

• NumPy Crash Course
• Pandas Data Analysis Crash Course
• Data Visualization Crash Course
• Neural Network Basics
• TensorFlow Basics
• Keras Syntax Basics
• Artificial Neural Networks
• Densely Connected Networks
• Convolutional Neural Networks
• Recurrent Neural Networks
• AutoEncoders
• GANs – Generative Adversarial Networks
• Deploying TensorFlow into Production
• and much more!

Duration: 19 hrs
Rating: 4.6 (2531 ratings) out of 5
Trainer: Jose Portilla
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Tensorflow 2.0: Deep Learning and Artificial Intelligence

This course covers a variety of topics, including

• Deploying a model with Tensorflow Serving (Tensorflow in the cloud)
• Deploying a model with Tensorflow Lite (mobile and embedded applications)
• Distributed Tensorflow training with Distribution Strategies
• Writing your own custom Tensorflow model
• Converting Tensorflow 1.x code to Tensorflow 2.0
• Constants, Variables, and Tensors
• Eager execution
• Gradient tape

Duration: 22 hrs
Rating: 4.6 (6366 ratings) out of 5
Trainer: Lazy Programmer Inc.
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TensorFlow 2.0 Practical

The course provides students with practical hands-on experience in training Artificial Neural Networks and Convolutional Neural Networks using real-world dataset using TensorFlow 2.0 and Google Colab.

Duration: 11.5 hrs
Rating: 4.3 (6366 ratings) out of 5
Trainer: Dr. Ryan Ahmed, Ph.D., MBA
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Deep Learning with TensorFlow 2.0 [2024]

after this course you’ll be able to fill your resume with skills and have plenty left over to show off at the interview.

• Of course, you’ll get fully acquainted with Google’ TensorFlow and NumPy, two tools essential for creating and understanding Deep Learning algorithms.
• Explore layers, their building blocks and activations – sigmoid, tanh, ReLu, softmax, etc.
• Understand the backpropagation process, intuitively and mathematically.
• You’ll be able to spot and prevent overfitting – one of the biggest issues in machine and deep learning
• Get to know the state-of-the-art initialization methods. Don’t know what initialization is? We explain that, too
• Learn how to build deep neural networks using real data, implemented by real companies in the real world. TEMPLATES included!
• Also, I don’t know if we’ve mentioned this, but you will have created your very own Deep Learning Algorithm after only 1 hour of the course.
• It’s this hands-on experience that will really make your resume stand out

Duration: 6 hrs
Rating: 4.5 (2154 ratings) out of 5
Trainer: 365 Careers
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Complete Guide to TensorFlow for Deep Learning with Python

This course covers a variety of topics, including

• Neural Network Basics
• TensorFlow Basics
• Artificial Neural Networks
• Densely Connected Networks
• Convolutional Neural Networks
• Recurrent Neural Networks
• AutoEncoders
• Reinforcement Learning
• OpenAI Gym

Duration: 14 hrs
Rating: 4.3 (16306 ratings) out of 5
Trainer: Jose Portilla
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A Complete Guide on TensorFlow 2.0 using Keras API

What you’ll learn

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