TensorFlow for Deep Learning Bootcamp — 94% OFF Discount Coupon

Learn TensorFlow by Google. Become an AI, Machine Learning, and Deep Learning expert!

★4.6 out of 5
87,032 students
Created by Andrei Neagoie, Daniel Bourke
English
Updated February 2026

Quick Facts — Course Summary

Here's a quick overview of everything you need to know about TensorFlow for Deep Learning Bootcamp before you enroll:

•Course Name: TensorFlow for Deep Learning Bootcamp
•Platform: Udemy
•Instructor: Andrei Neagoie, Daniel Bourke
•Coupon Last Verified: February 16, 2026
•Level: Advanced
•Topic: Development
•Subtopic: TensorFlow
•Total Time: 62h 30m of video content
•Language: English
•Access Type: Unlimited lifetime access + updates
•Certificate: Included upon completion from Udemy
•Main Skills: 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
•Requirements: Mac / Windows / Linux - all operating systems work with this course! · No previous TensorFlow knowledge required. Basic understanding of Machine Learning is helpful
•Current Price: $12.99 (was $199.99). You save $187.00 with 94% discount.
•How to Apply: Click the coupon button to activate your discount automatically
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Skills You'll Master

By the end of TensorFlow for Deep Learning Bootcamp, you'll have these practical skills:

✓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.

What You Need Before Starting

Before enrolling in TensorFlow for Deep Learning Bootcamp, make sure you have:

•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 Course

The following is the full official course description for TensorFlow for Deep Learning Bootcamp as published on Udemy by instructor Andrei Neagoie, Daniel Bourke:

Just launched with all modern best practices for building neural networks with TensorFlow and becoming a TensorFlow & Deep Learning Expert!

Join a live online community of over 900,000+ students and a course taught by a TensorFlow expert. This course will take you from absolute beginner with TensorFlow, to creating state-of-the-art deep learning neural networks.

TensorFlow experts earn up to $204,000 USD a year, with the average salary hovering around $148,000 USD. By taking this course you will be joining the growing Machine Learning industry and becoming a top paid TensorFlow Developer!

Here is a full course breakdown of everything we will teach (yes, it's very comprehensive, but don't be intimidated, as we will teach you everything from scratch!):

The goal of this course is to teach you all the skills necessary for you to become a top 10% TensorFlow Developer.

This course will be very hands on and project based. You won't just be staring at us teach, but you will actually get to experiment, do exercises, and build machine learning models and projects to mimic real life scenarios. By the end of it all, you will develop skillsets needed to develop modern deep learning solutions that big tech companies encounter.

0 — TensorFlow Fundamentals
  • 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
1 — Neural Network Regression 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
2 — Neural Network Classification with TensorFlow
  • 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)
3 — Computer Vision and Convolutional Neural Networks with TensorFlow
  • 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
4 — Transfer Learning with TensorFlow Part 1: Feature Extraction
  • 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
5 — Transfer Learning with TensorFlow Part 2: Fine-tuning
  • 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
6 — Transfer Learning with TensorFlow Part 3: Scaling Up (Food Vision mini)
  • 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
7 — Milestone Project 1: Food Vision
  • 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.
8 — NLP Fundamentals in TensorFlow
Learn to:
  • 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
9 — Milestone Project 2: SkimLit
  • 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)
10 — Time Series fundamentals in TensorFlow
  • 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)
11 — Milestone Project 3: (Surprise)
  • 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 ;)

TensorFlow is growing in popularity and more and more job openings are appearing for this specialized knowledge. As a matter of fact, TensorFlow is outgrowing other popular ML tools like PyTorch in job market. Google, Airbnb, Uber, DeepMind, Intel, IBM, Twitter, and many others are currently powered by TensorFlow. There is a reason these big tech companies are using this technology and you will find out all about the power that TensorFlow gives developers.

We guarantee you this is the most comprehensive online course on TensorFlow. So why wait? Make yourself stand out by becoming a TensorFlow Expert and advance your career.

See you inside the course!

Is the TensorFlow for Deep Learning Bootcamp Coupon Worth It?

Expert review by Andrew Derek, Lead Course Analyst at CoursesWyn.•Last updated: February 16, 2026.

Based on analysis of the curriculum structure, student engagement metrics, and verified rating data, TensorFlow for Deep Learning Bootcamp is a high-value resource for learners seeking to build skills inDevelopment. Taught by Andrei Neagoie, Daniel Bourke on Udemy, the 62h 30m course provides a structured progression from foundational concepts to advanced techniques— making it suitable for learners at all levels. The current coupon reduces the price by 94%, from $199.99 to $12.99, removing the primary financial barrier to enrollment.

✓What We Like (Pros)

  • Verified 94% price reduction makes this course accessible to learners on any budget.
  • Aggregate student rating of 4.6 out of 5 indicates high learner satisfaction.
  • Strong enrollment base with over 87,032 students demonstrates course popularity and trust.
  • Includes an official Udemy completion certificate and lifetime access to all future content updates.

!Keep in Mind (Cons)

The following limitations should be considered before enrolling in TensorFlow for Deep Learning Bootcamp:

  • The depth of Development coverage may be challenging for absolute beginners without the listed prerequisites.
  • Lifetime access is contingent on the continued operation of the Udemy platform.
  • Hands-on projects and quizzes require additional time investment beyond video watch time.
Final Verdict: Worth It
This course offers exceptional value with current pricing
✓

Course Rating Summary

TensorFlow for Deep Learning Bootcamp Course holds an aggregate rating of 4.6 out of 5 based on 87,032 student reviews on Udemy.

4.6
★★★★★
87,032 Verified Ratings
5 stars
75%
4 stars
15%
3 stars
6%
2 stars
2%
1 star
2%

* Rating distribution is approximated from the aggregate score. Sourced from Udemy.

Instructor Profile

The following section provides background information on Andrei Neagoie, Daniel Bourke, the instructor responsible for creating and maintaining TensorFlow for Deep Learning Bootcamp on Udemy.

TensorFlow for Deep Learning Bootcamp is taught by Andrei Neagoie, Daniel Bourke, a Udemy instructor specializing in Development. For the full instructor biography, professional credentials, and a complete list of their courses, visit the official instructor profile on Udemy.

•Instructor Name: Andrei Neagoie, Daniel Bourke
•Subject Area: Development
•Teaching Approach: Practical, project-based instruction focused on real-world application of Development skills.

Frequently Asked Questions

The following questions and answers cover the most common queries about TensorFlow for Deep Learning Bootcamp, its coupon code, pricing, and enrollment process.

About the Author

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Andrew Derek

Lead Course Analyst at CoursesWyn with 8+ years of experience evaluating online learning platforms. I've analyzed 500+ Udemy courses and helped thousands of learners choose the right courses for their career goals.

⭐4.8/5 Rating
✓Trusted by 10K+ Students

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