Top Courses to Learn TensorFlow from World-Class Educators β€”2022 Updated

TensorFlow is a machine learning system that operates in heterogeneous environments

Top Courses to Learn TensorFlow from World-Class Educators β€”2022 Updated

TensorFlow is a state-of-the-art, open-source machine learning framework created by Google to design, build, and train Machine Learning and Deep Learning models.

TensorFlow has a comprehensive and flexible ecosystem of tools and community resources that make it easy to develop and train ML and Deep Learning models.

We know the options out there; prerequisites and the skills you need to gain to overcome the learning blocks.

Also, refer to the Notable Mentions section at the tail end of this piece, where you will find helpful resources for bootstrapping your intellectual abilities.

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Best TensorFlow Courses from World-Class Educators

My goal in this piece is to help you find some interactive courses from the Notable Educators that will edify you with a solid understanding of TensorFlow.

So, without further ado, let’s get started.


β€” Introduction to TensorFlow in Python

This course is designed by Isaiah Hull, a senior economist working at Swiss Central Bank, and delivered via DataCamp.

This course covers all the concepts you need to know in the fundamentals of neural networks, making use of high-level API’s and building deep learning models using TensorFlow.

What you will learn?

  • Define constants and variables.
  • Perform Tensor addition and multiplication, and compute derivatives
  • Learn Linear models to solve and make prediction models
  • Making predictions with matrix multiplication
  • Neural Networks
  • Binary Classification problems
  • Training a Network in TensorFlow
  • Use low-level linear algebra and high-level Keras API
  • Train a sign language letter classifier using High-level APIs
  • Build advanced models on TensorFlow 2

Is it right for you?

This course is suitable for learners with experience in Python and high school-level maths.


β€” Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

This course is taught by Laurence Moroney and is part of the TensorFlow in Practice Specialization (sectioned below) by Deeplearning.ai.

Through the guided series of lectures and exercises to learn TensorFlow, you’ll build and train a neural network for computer vision applications and finally learn to use convolutions to improve your models.

What you will learn?

  • Train a neural network
  • Learn Computer Vision from basics to the advanced level
  • Convolutional Neural Networks
  • Handling complex images
  • Key TensorFlow techniques for Ai, ML and Deep Learning
Introduction to TensorFlow, Ai, Machine Learning and Deep Learning
Image by Coursera

Is it right for you?

This course requires intermediate knowledge in Python and high school-level maths.

By the end, you will be highly prepared to learn advanced topics in computer vision, TensorFlow, and Machine Learning.


β€” Introduction to TensorFlow in R

This interactive course in R programming is created by Colleen Bobbie, and delivered via DataCamp.

This course starts from simple linear regressions to more complex deep learning neural networks, and you will also learn the basics of TensorFlow and higher-level APIs such as Keras and TFEstimators.

What you will learn?

  • TensorFlow syntax, TensorFlow constants, placeholders, and variables
  • Data Visualization using TensorBoard, the TensorFlow
  • Deep Learning in TensorFlow
  • Create a Deep Neural Network
  • Increase model accuracy
  • Ridge Regression into a Keras model
  • Multiple hyperparameter tuning
  • Dropout Techniques using TFEstimators
Introduction to TensorFlow in R
Image by DataCamp

Is it right for you?

This course is suitable for learners with intermediate knowledge of R programming and high school-level maths.

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β€” Convolutional Neural Networks in TensorFlow

This high-rated course developed by Deeplearning.ai is part of TensorFlow in practice specialization (added below) and delivered via Coursera.

This course aims to handle ConvNets with real-world image data to help you learn the techniques of improving your ConvNet performance when doing image classification.

You will also learn about plot loss and accuracy, and understand how to prevent over-fitting, including augmentation and dropout.

What you will learn?

  • Inductive transfer
  • Training larger dataset
  • Visualizing the effect of the convolutions
  • Augmentation to avoid overfitting
  • Transfer Learning with Inception
  • Exploring Dropout techniques
  • Multiclass Classifications
  • Training and testing a classifier
  • Tensorflow
Convolution Neural Networks in TensorFlow
Image by Coursera

Is it right for you?

This specialization is suitable for experienced programmers with a solid background in maths.

By the end, you will have gained skills in Inductive Transfer, Augmentation Dropouts, and Machine Learning.


β€” TensorFlow Developer Professional Certificate

This high-quality TensorFlow developer certification specialization is designed by Deeplearning.ai and delivered via Coursera.

In this specialization, you’ll learn the best practices to build and train a neural network for computer vision applications with TensorFlow.

You will also learn to apply RNNs, GRUs, and LSTMs as you train your models using text repositories.

What you will learn?

  • From Basics to advanced - Computer Vision
  • Convolutional Neural Network
  • Machine Learning in TensorFlow
  • Natural Language Processing
  • Inductive Transfer
  • Augmentation
  • Dropouts
  • Tokenization
  • RNNs
  • Forecasting
  • Time Series
TensorFlow Developer Professional Certificate
Image by Coursera

Is it right for you?

This specialization is suitable for intermediate learners with experience in programming and knowledge of high school-level maths.


β€” TensorFlow: Data and Deployment Specialization

This four-course specialization by Deeplearning.ai, complements TensorFlow in Practice specialization (sectioned above) with much-advanced content.

You will learn the deployment scenarios and understand efficient ways to use data when training your models and also run them in your browser using TensorFlow.js

By the end, you will gain lifelong skills in Machine Learning, advanced deployment, Object Detection, and JavaScript.

What you will learn?

  • Machine Learning with Tensorflow
  • Advanced deployment
  • Object Detection in TensorFlow
  • JavaScript to run models in your browser
  • Build and design Convolutional Neural Network
  • TensorFlow.js
  • TensorFlow Lite
  • Mathematical Optimization in TensorFlow
  • Artificial Neural Network
  • Extraction, Transformation And Loading (ETL)
  • Building Data Pipelines
TenforFlow Data and Deployment Specialization
Image by Coursera

Is it right for you?

This specialization is suitable for learners with intermediate programming skills and solid knowledge of maths.


β€” Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization

This highest-rated specialization is designed by Google Cloud Engineers and delivered via Coursera.

In this specialization, you learn TensorFlow with all the key advanced machine learning topics using Google Cloud Platform.

This specialization provides hands-on lab experience in optimizing, deploying, and scaling production ML models.

You will learn to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text.

What you will learn?

  • Machine Learning with Tensorflow on GCP
  • Convolutional Neural Network
  • Building Production Machine Learning Systems
  • Image Understanding with TensorFlow on GCP
  • Natural Language Processing
  • Sequence Models for Time Series
  • Building Recommendation Systems with TensorFlow
  • Learn fault tolerance, replication, and more
  • Advanced Machine Learning
Advanced Machine Learning On Google Cloud Specialization
Image by Coursera

Is it right for you?

This course is suitable for advanced learners with rich experience and knowledge about cloud computing, programming, and maths.

You will be equip you with sound machine learning skills and become highly prepared to build recommendation systems using TensorFlow.


Closing Note

You need to have a fairly good understanding of advanced mathematical concepts to become successful in AI, Machine learning, or Deep Learning.

Thanks for making it to the end ;)

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