Best Online Courses to Learn TensorFlow from Scratch

Best Online Courses to Learn TensorFlow from Scratch

Do you want to learn TensorFlow? Here we listed TensorFlow tutorials which will help you learn TensorFlow from scratch, and are suitable for beginners, intermediate learners as well as experts

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. 9 hours
Rating: 4.5 (2,047 ratings) out of 5
Trainer: Google Cloud Training
URL: https://www.coursera.org/learn/intro-tensorflow

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
URL: https://www.coursera.org/specializations/advanced-machine-learning-tensorflow-gcp

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
URL: https://www.coursera.org/specializations/machine-learning-tensorflow-gcp

TensorFlow in Practice Specialization

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 (13,340 ratings) out of 5
Trainer: Laurence Moroney
URL: https://www.coursera.org/specializations/tensorflow-in-practice

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
URL: https://www.coursera.org/specializations/tensorflow-data-and-deployment

Deep Learning with Tensorflow

What you’ll learn

  • Explain foundational TensorFlow concepts such as the main functions, operations and the execution pipelines.
  • Describe how TensorFlow can be used in curve fitting, regression, classification and minimization of error functions.
  • Understand different types of Deep Architectures, such as Convolutional Networks, Recurrent Networks and Autoencoders.
  • Apply TensorFlow for backpropagation to tune the weights and biases while the Neural Networks are being trained.
Duration: Approx. 15 hours
Rating: 4.4 (480 ratings) out of 5
Trainer: Saeed Aghabozorgi
URL: https://www.edx.org/course/deep-learning-with-tensorflow

Intro to TensorFlow for Deep Learning

What you’ll learn

  • How to build deep learning applications with TensorFlow
  • You’ll get hands-on experience building your own state-of-the-art image classifiers and other deep learning models
  • You’ll also use your TensorFlow models in the real world on mobile devices, in the cloud, and in browsers
Duration: Approx. 2 Months 
URL: https://www.udacity.com/course/intro-to-tensorflow-for-deep-learning--ud187

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
URL: https://www.udemy.com/course/tensorflow-20-recurrent-neural-networks-lstms-grus/

TensorFlow Developer Certificate in 2022: 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
URL: https://www.udemy.com/course/tensorflow-developer-certificate-machine-learning-zero-to-mastery/

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
URL: https://www.udemy.com/course/complete-tensorflow-2-and-keras-deep-learning-bootcamp/

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.
URL: https://www.udemy.com/course/deep-learning-tensorflow-2/

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
URL: https://www.udemy.com/course/tensorflow-2-practical/

Deep Learning with TensorFlow 2.0 [2022]

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
URL: https://www.udemy.com/course/machine-learning-with-tensorflow-for-business-intelligence/

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
URL: https://www.udemy.com/course/complete-guide-to-tensorflow-for-deep-learning-with-python/

A Complete Guide on TensorFlow 2.0 using Keras API

What you’ll learn

  • How to use Tensorflow 2.0 in Data Science
  • Important differences between Tensorflow 1.x and Tensorflow 2.0
  • How to implement Artificial Neural Networks in Tensorflow 2.0
  • How to implement Convolutional Neural Networks in Tensorflow 2.0
  • How to implement Recurrent Neural Networks in Tensorflow 2.0
  • How to build your own Transfer Learning application in Tensorflow 2.0
  • How to build a stock market trading bot using Reinforcement Learning (Deep-Q Network)
  • How to build Machine Learning Pipeline in Tensorflow 2.0
  • How to conduct Data Validation and Dataset Preprocessing using TensorFlow Data Validation and TensorFlow Transform.
  • Putting a TensorFlow 2.0 model into production
  • How to create a Fashion API with Flask and TensorFlow 2.0
  • How to serve a TensorFlow model with RESTful API

Duration: 13 hrs
Rating: 4.4 (1754 ratings) out of 5
Trainer: Hadelin de Ponteves
URL: https://www.udemy.com/course/tensorflow-2/

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