TensorFlow Developer Certificate Bootcamp

Pass the TensorFlow Developer Certification Exam by Google. Become an AI, Machine Learning, and Deep Learning expert!

4.66 (10150 reviews)
Udemy
platform
English
language
Data Science
category
instructor
TensorFlow Developer Certificate Bootcamp
70,572
students
63.5 hours
content
Mar 2024
last update
$109.99
regular price

What you will learn

Learn to pass Google's official TensorFlow Developer Certificate exam (and add it to your resume)

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 and Deep Learning, to test your abilities with the TensorFlow assessment exam

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 Certified Developer

Be recognized as a top candidate for recruiters seeking TensorFlow developers

Why take this course?

Just launched with all modern best practices for building neural networks with TensorFlow and passing the TensorFlow Developer Certificate exam!

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

TensorFlow experts earn up to $204,000 USD a year, with the average salary hovering around $148,000 USD. By passing this certificate, which is officially recognized by Google, you will be joining the growing Machine Learning industry and becoming a top paid TensorFlow developer! If you pass the exam, you will also be part of Google's TensorFlow Developer Network where recruiters are able to find you.

The goal of this course is to teach you all the skills necessary for you to go and pass this exam and get your TensorFlow Certification from Google so you can display it on your resume, LinkedIn, Github and other social media platforms to truly make you stand out.

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!):

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. Most importantly, we will show you what the TensorFlow exam will look like for you. 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 passing the TensorFlow Developer Certificate to qualify you as a TensorFlow expert. So why wait? Make yourself stand out by becoming a Google Certified Developer and advance your career.


See you inside the course!

Screenshots

TensorFlow Developer Certificate Bootcamp - Screenshot_01TensorFlow Developer Certificate Bootcamp - Screenshot_02TensorFlow Developer Certificate Bootcamp - Screenshot_03TensorFlow Developer Certificate Bootcamp - Screenshot_04

Reviews

Salvatore
August 24, 2023
Finora solo introduttivo però il programma del corso e le risorse fornite sembrano offrire un'ottima ed esaustiva base per i miei studi
Vishal
August 22, 2023
I am very happy feeling Glorius just because naw exploring future coding era deep learning, and neural networks(TF). I'm from India and thankful to sir for easily explaining everything.
Zakir
August 19, 2023
Really an advanced course, It contains valuable and great information at such a low price, recommend only to those who are at the advance level of Programming because as this is an advanced course, beginners and intermediate programmers wont understand it easily, Loved it and great content, thanks to the instructor
Aditya
August 18, 2023
The best course in the Udemy. There is a deep drive in Machine Learning and lots of hands-on coding. Thank you!
Cycle.Win
August 17, 2023
Personally, it has helped further my knowledge in TensorFlow, and I've definitely learnt better than when I attempted to learn it myself. Thanks!
Rakesh
August 16, 2023
Can you take a tensor out of an object ??? .. Then you can do whatever you want with it end of the day.. I just did code along Daniel and I really feel that I know a lot of things about deep learning.. Thank you Daniel for the amazing effort from you. I am really waiting for a course on GANs and Diffusion models from you..!!!!!! :)
John
August 15, 2023
Chatgpt is here now and it shows how much can be done with AI. This doesn't mean all other AI is dead. It's a call more than ever to understand what AI is. And what a better place to learn than with Andre and Daniel. They clearly know their subject and are very good at explaining it for others. Its not Andre and Daniel are doing Tensor flow now. It's Tensor flow now has them. And it needs them because it ca be a very complex subject very fast without such guides. Now back to work.
Scott
August 11, 2023
Fantastic course. Daniel is very passionate about Deep Learning and makes it easy to stay engaged in an otherwise complex topic
UWIRAGIYE
August 8, 2023
I was looking for courses that could boost my little skills in ML and this course matches with what I was wanted so far
Sita
August 2, 2023
Too much of repeated content. This can be trimmed Content and Lecture are very good, except for the repetition
Christopher
August 1, 2023
The laid foundation before starting the actual sty is very detailed. A lot of time and effort has gone into it. My perception is that the instructor has a genuine concern for the students success.
Shailender
July 30, 2023
Just started the course - looks like the support for learning is comprehensive! Nice work on the course, thanks Daniel, Andrew! I'm more of a reader-learner, so I'll double back to Github the moment I'm done with the videos
Emir
July 27, 2023
Wow Daniel, what a journey it was. Thank you for everything. I learned a lot. Although, I try to approach problems in my own way. I learned a lot from your way of building neural networks. A few comments here: * I tried to use efficient data input pipelines by using tf.data.Dataset API almost in every section because preprocessing the data usually the most time-consuming part and I wanted to be experienced about this. *For those complaining about the lecture regarding the duration of the modules. I recommend them to write their own code in a different way and check whether your code works similarly to Daniel's. By doing this you can focus on building skills rather than watching videos. On the other hand, this will mean that you need to spend at least 60 hours on writing the code. *The course could be around 40-45 hours by removing the repetitive sections. Then, the remaining 10-15 hours could be on theoretical Neural Networks lessons. Overall, I am satisfied with this course.
Feisal
July 27, 2023
Got me excited, lots of resources . . .good advice on how to proceed. In continuation, I really like this course, very hands on, exactly right, coding is repetition and most importantly . . . The talking through of the thought process is really useful. So far so good, looking forward to the Time series . .that's really where the rubber meets the road.
Harsh
July 26, 2023
Such a great course, I have already learned deep learning and I really wanted to do the TensorFlow developer exam, and this course is a good revision for me

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3693164
udemy ID
12/9/2020
course created date
4/29/2021
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