TensorFlow for Deep Learning Bootcamp
Learn TensorFlow by Google. Become an AI, Machine Learning, and Deep Learning expert!
What you'll learn in this Udemy Course
- ✓ Build TensorFlow models using Computer Vision, Convolutional Neural Networks and Natural Language Processing
- ✓ Complete access to ALL interactive notebooks and ALL course slides as downloadable guides
- ✓ Increase your skills in Machine Learning, Artificial Intelligence, and Deep Learning
- ✓ Understand how to integrate Machine Learning into tools and applications
- ✓ Learn to build all types of Machine Learning Models using the latest TensorFlow 2
- ✓ Build image recognition, text recognition algorithms with deep neural networks and convolutional neural networks
- ✓ Using real world images to visualize the journey of an image through convolutions to understand how a computer “sees” information, plot loss and accuracy
- ✓ Applying Deep Learning for Time Series Forecasting
- ✓ Gain the skills you need to become a TensorFlow Developer
- ✓ Be recognized as a top candidate for recruiters seeking TensorFlow developers
Udemy Coupon Requirements
- Mac / Windows / Linux - all operating systems work with this course!
- No previous TensorFlow knowledge required. Basic understanding of Machine Learning is helpful
About This Udemy Coupon
- Introduction to tensors (creating tensors)
- Getting information from tensors (tensor attributes)
- Manipulating tensors (tensor operations)
- Tensors and NumPy
- Using @tf.function (a way to speed up your regular Python functions)
- Using GPUs with TensorFlow
- Build TensorFlow sequential models with multiple layers
- Prepare data for use with a machine learning model
- Learn the different components which make up a deep learning model (loss function, architecture, optimization function)
- Learn how to diagnose a regression problem (predicting a number) and build a neural network for it
- Learn how to diagnose a classification problem (predicting whether something is one thing or another)
- Build, compile & train machine learning classification models using TensorFlow
- Build and train models for binary and multi-class classification
- Plot modelling performance metrics against each other
- Match input (training data shape) and output shapes (prediction data target)
- Build convolutional neural networks with Conv2D and pooling layers
- Learn how to diagnose different kinds of computer vision problems
- Learn to how to build computer vision neural networks
- Learn how to use real-world images with your computer vision models
- Learn how to use pre-trained models to extract features from your own data
- Learn how to use TensorFlow Hub for pre-trained models
- Learn how to use TensorBoard to compare the performance of several different models
- Learn how to setup and run several machine learning experiments
- Learn how to use data augmentation to increase the diversity of your training data
- Learn how to fine-tune a pre-trained model to your own custom problem
- Learn how to use Callbacks to add functionality to your model during training
- Learn how to scale up an existing model
- Learn to how evaluate your machine learning models by finding the most wrong predictions
- Beat the original Food101 paper using only 10% of the data
- Combine everything you've learned in the previous 6 notebooks to build Food Vision: a computer vision model able to classify 101 different kinds of foods. Our model well and truly beats the original Food101 paper.
- Preprocess natural language text to be used with a neural network
- Create word embeddings (numerical representations of text) with TensorFlow
- Build neural networks capable of binary and multi-class classification using:
- RNNs (recurrent neural networks)
- LSTMs (long short-term memory cells)
- GRUs (gated recurrent units)
- CNNs
- Learn how to evaluate your NLP models
- Replicate a the model which powers the PubMed 200k paper to classify different sequences in PubMed medical abstracts (which can help researchers read through medical abstracts faster)
- Learn how to diagnose a time series problem (building a model to make predictions based on data across time, e.g. predicting the stock price of AAPL tomorrow)
- Prepare data for time series neural networks (features and labels)
- Understanding and using different time series evaluation methods
- MAE — mean absolute error
- Build time series forecasting models with TensorFlow
- RNNs (recurrent neural networks)
- CNNs (convolutional neural networks)
- If you've read this far, you are probably interested in the course. This last project will be good... we promise you, so see you inside the course ;)
⚡ Limited Time Offer
Coupon valid until end of April 2026
Don't miss out — grab this Development course before the coupon expires.
You save
$187.00
94% OFF original price
What is TensorFlow for Deep Learning Bootcamp?
TensorFlow for Deep Learning Bootcamp is a 62h 30m online course on Udemy taught by Andrei Neagoie, Daniel Bourke. It covers TensorFlow and is designed for learners who want to build tensorflow models using computer vision, convolutional neural networks and natural language processing . With 87,032 students enrolled and a 4.6 star rating, it is one of the top-rated courses in TensorFlow on Udemy. Use the coupon above to access it at 94% OFF ($12.99).
About the Instructor
Andrei Neagoie, Daniel Bourke
Udemy Instructor · Development Expert
Andrei Neagoie, Daniel Bourke is an expert instructor on Udemy specializing in Development. Their course "TensorFlow for Deep Learning Bootcamp" has helped 87,032 students master TensorFlow with a 4.6 star rating.
Course Information
Platform
Udemy
Instructor
Andrei Neagoie, Daniel Bourke
Duration
62h 30m
Language
English
Category
Development · TensorFlow
Rating
Price
Last Updated
February 2026
Related Topics
Andrew Derek
Expert ReviewerAndrew Derek is a lead editor and course analyst at CoursesWyn with over 8 years of experience in online education and digital marketing. He meticulously audits every Udemy coupon and course syllabus to ensure students get the highest quality learning materials at the best possible price.
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Frequently Asked Questions
Is there a discount for TensorFlow for Deep Learning Bootcamp?
Yes! Instead of paying $199.99, you can get TensorFlow for Deep Learning Bootcamp for just $12.99 with our verified coupon — saving you $187.00 (94% OFF) today.
How do I apply the coupon code?
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How long is TensorFlow for Deep Learning Bootcamp?
TensorFlow for Deep Learning Bootcamp is approximately 62h 30m long. Udemy gives you lifetime access so you can learn at your own pace and revisit content anytime.
What will I learn in TensorFlow for Deep Learning Bootcamp?
In TensorFlow for Deep Learning Bootcamp by Andrei Neagoie, Daniel Bourke, you will learn: Build TensorFlow models using Computer Vision, Convolutional Neural Networks and Natural Language Processing ; Complete access to ALL interactive notebooks and ALL course slides as downloadable guides ; Increase your skills in Machine Learning, Artificial Intelligence, and Deep Learning . The course covers TensorFlow with 62h 30m of hands-on content.
What is TensorFlow for Deep Learning Bootcamp?
TensorFlow for Deep Learning Bootcamp is a 62h 30m online course on Udemy taught by Andrei Neagoie, Daniel Bourke. It covers Development with a 4.6 star rating from 87,032 enrolled students. Use our verified coupon to access it at $12.99 (94% OFF).