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Complete Tensorflow 2 and Keras Deep Learning Bootcamp (Udemy.com)

Learn to use Python for Deep Learning with Google's latest Tensorflow 2 library and Keras!

4.7
8,938 reviews

Created by: Jose Portilla

Last updated June 2022

Our take

Based on the ratings of 8,938 students, a sample of their written reviews and the syllabus, as the course stood in June 2022. No course pays to be reviewed.

Jose Portilla's TensorFlow 2 bootcamp runs about 19 hours over 116 lectures and 13 sections. It opens with short NumPy, Pandas and plotting refreshers, then moves through basic neural networks, CNNs, RNNs, NLP, autoencoders, GANs and a deployment section. The requirements ask for working Python and some derivatives, and one reviewer calls it very good for people with basic programming knowledge. The course has about 56,000 students and a 4.7 average from roughly 8,900 ratings.

Students like how clearly the instructor explains things. Reviewers call the teaching clear and concise, one loves the CNN section and another praises the practical examples. The complaints cluster in two places. One is age: the course was last updated in 2022, and recent reviewers say deprecated pieces such as predict_classes, ImageDataGenerator and TimeseriesGenerator need real workarounds, and a few lean on ChatGPT to fix errors. The other is the back half. Some say the NLP and GAN sections feel rushed, that details get skipped, and that questions often go unanswered.

Value is decent if you accept the maintenance cost. Expect to spend time matching old code to current library versions. It is a solid way to get through the main deep learning model types with notebooks and exercises, but a thinner pick for GANs and deployment. Pair it with the current TensorFlow docs when things break. Pick it for clear teaching of the basics, and skip it if you want code that runs unchanged on today's releases.

Best forPython coders with basic derivatives who want clear, hands-on Keras models across CNNs, RNNs and GANs.
Skip it ifYou want code that runs unchanged on current TensorFlow, or a deep treatment of NLP and GANs.

Pros

  • Clear, concise explanations of core ideas, with one reviewer singling out the CNN section
  • Covers CNNs, RNNs, autoencoders, GANs and deployment in one 19-hour path
  • Jupyter notebooks and exercises let students code along, and early exercises get praise
  • Short NumPy, Pandas and plotting refreshers open the course before the neural network material

Cons

  • Last updated in 2022; predict_classes, ImageDataGenerator and TimeseriesGenerator are now deprecated
  • NLP, GAN and later sections feel rushed, with skipped details and half-done exercises
  • Reviewers say questions to the course staff often go unanswered
Very good for people with some basic programming knowledge!
Jason, a student

Labeled All Levels, but the requirements list working Python and some math basics such as derivatives.

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What you will learn

  • Learn to use TensorFlow 2.0 for Deep Learning
  • Leverage the Keras API to quickly build models that run on Tensorflow 2
  • Perform Image Classification with Convolutional Neural Networks
  • Use Deep Learning for medical imaging
  • Forecast Time Series data with Recurrent Neural Networks
  • Use Generative Adversarial Networks (GANs) to generate images
  • Use deep learning for style transfer
  • Generate text with RNNs and Natural Language Processing
  • Serve Tensorflow Models through an API
  • Use GPUs for accelerated deep learning

Course content

13 sections · 116 lectures · 19 hours of video 1 quiz, 2 articles

  1. 1Course Overview, Installs, and Setup 1 free preview4 lectures · 30 min
  2. 2COURSE OVERVIEW CONFIRMATION1 quiz
  3. 3NumPy Crash Course 2 free previews6 lectures · 49 min
  4. 4Pandas Crash Course10 lectures · 1.5 hours
  5. 5Visualization Crash Course5 lectures · 38 min
  6. 6Machine Learning Concepts Overview6 lectures · 49 min
  7. 7Basic Artificial Neural Networks - ANNs 1 free preview27 lectures · 5.1 hours
  8. 8Convolutional Neural Networks - CNNs 1 free preview17 lectures · 2.7 hours
  9. 9Recurrent Neural Networks - RNNs 1 free preview14 lectures · 2.6 hours
  10. 10Natural Language Processing7 lectures · 58 min

Who it is for

The instructor says it suits

  • Python developers interested in learning about TensorFlow 2 for deep learning and artificial intelligence

What you need before you start

  • Know how to code in Python
  • Some math basics such as derivatives

How it compares

Against the other 126 rated Udemy courses in Deep Learning on CourseDuck:

  • Rating4.7 out of 5higher than 82% of them
  • Reviews8,938#7 of 127 by number of reviews
  • Length19.2 hourslonger than 80% of them
  • Last updatedJune 2022earlier than 76% of them

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Course Description

This course will guide you through how to use Google's latest TensorFlow 2 framework to create artificial neural networks for deep learning! This course aims to give you an easy to understand guide to the complexities of Google's TensorFlow 2 framework in a way that is easy to understand.

We'll focus on understanding the latest updates to TensorFlow and leveraging the Keras API (TensorFlow 2.0's official API) to quickly and easily build models. In this course we will build models to forecast future price homes, classify medical images, predict future sales data, generate complete new text artificially and much more!

This course is designed to balance theory and practical implementation, with complete jupyter notebook guides of code and easy to reference slides and notes. We also have plenty of exercises to test your new skills along the way!

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!

Keras, a user-friendly API standard for machine learning, will be the central high-level API used to build and train models. The Keras API makes it easy to get started with TensorFlow 2. Importantly, Keras provides several model-building APIs (Sequential, Functional, and Subclassing), so you can choose the right level of abstraction for your project. TensorFlow’s implementation contains enhancements including eager execution, for immediate iteration and intuitive debugging, and tf.data, for building scalable input pipelines.

TensorFlow 2 makes it easy to take new ideas from concept to code, and from model to publication. TensorFlow 2.0 incorporates a number of features that enables the definition and training of state of the art models without sacrificing speed or performance

It is used by major companies all over the world, including Airbnb, Ebay, Dropbox, Snapchat, Twitter, Uber, SAP, Qualcomm, IBM, Intel, and of course, Google!

Become a deep learning guru today! We'll see you inside the course!
Read More All Levels All Levels product length iconTime: 19.2h

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Instructor Details

Jose Portilla

Jose Marcial Portilla has a BS and MS in Mechanical Engineering from Santa Clara University and years of experience as a professional instructor and trainer for Data Science, Machine Learning and Python Programming. He has publications and patents in various fields such as microfluidics, materials science, and data science. Over the course of his career he has developed a skill set in analyzing data and he hopes to use his experience in teaching and data science to help other people learn the power of programming, the ability to analyze data, and the skills needed to present the data in clear and beautiful visualizations. Currently he works as the Head of Data Science for Pierian Training and provides in-person data science and python programming training courses to employees working at top companies, including General Electric, Cigna, SalesForce, Starbucks, McKinsey and many more. Feel free to check out the website link to find out more information about training offerings.

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Reviews

4.7

8,938 ratings on Udemy

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By Alexander Verner on 6/29/2026

In general, it's a good course that covers many DL topics. But there's a caveat: Up to Chapter 10, the material is covered clearly and in sufficient detail, but in further chapters (11-13), the teaching becomes slipshod. Important details are omitted, and the exercises, which were very good at first, become half-done. In addition, the course staff often ignores questions/comments left.

By Oludolapo Soboyede on 11/6/2021

Complete Tensorflow 2 and Keras Deep Learning Bootcamp is an amazing course that has given me much greater intuition about how machine learning can be used to solve real problems. I really the appreciate the hands-on approach used to teach the course. Thanks to this course I have been able to create my first Artificial Neural Network and deployed it as a web application. I highly recommend this course to anyone who wants a deeper understanding of Tensorflow and machine learning.

By Hans Palacios on 5/25/2021

Great course, as always with Jose's courses! Easy to follow lectures and code-alongs. Detailed guidance on a variety of topics and everything is explained very well. For me, all of the exercises worked exactly as intended and without issue. Thanks, and I look forward to learning more advanced topics in Jose's other courses!

By CHETHAN S H on 2/1/2021

Thank You Jose, for this amazing course!, Instructor Jose Portilla has designed the course in such a way that you get to learn python, numpy, pandas, matplotlib, seaborn in Phase-1, then you get to learn machine learning in Phase-2, then you switch gears to learn deep learning using tensorflow in Phase-3. All in all this course covers all the fundamental's to create deep learning model's. Thank You.

By Johan Schreurs on 1/19/2021

It was a good match. Tensorflow, Keras and ML are a broad and deep subject so it is not easy to give a good foundation, even in a longer course like this one. There are pointers to extra resources about how to choose types of layers, number of neurons etc. I think it could help to add a bit even more pointers like that, but overall a pretty good course. And the exercises really help to make the knowledge stick.

By Alireza Zarghamnezhad on 11/14/2020

This course is one of the most completed course which I see in my journey because here you can find all the information which you should gain for being familiar with AI and ML.

By Balaji Sundararaman on 11/14/2020

Superb. Very High quality of content and explanations.

By Jaro . on 11/14/2020

I highly recommend the course. It is consciously prepared and contains clear explanations. There is necessary theoretical information that allows understanding the whole theory not only the coding/programming issue. The materials are clear and faultless. 5/5

By Shawn Taylor on 11/14/2020

Amazing Class. 2nd class I have taken with this instructor - easy to follow/comprehend. Thanks!

By Siddhesh Shelke on 11/7/2020

Jose Portilla is my favourite instructor.

By Malik Muaz zden on 11/7/2020

there should be more exercises

By Michal Jirk on 11/7/2020

The course is very well structured and the description of the topics is brilliant. I also love the exercises!

Showing 12 of 319 reviews

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Overall Score : 94 / 100

Complete Tensorflow 2 and Keras Deep Learning Bootcamp
Visit course on Udemy Write a review
  • Video Duration: icon 19.2h
  • Price: $16.99
  • Provider: icon Udemy
  • Updated: icon June 2022
  • Level: All Levels All Levels
  • Language: icon English
  • Certificate: icon Yes
  • Lectures:116 in 13 sections
  • Practice:1 quiz
  • Students:56,500
  • Subtitles:10 languages
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