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[2026] Tensorflow 2: Deep Learning & Artificial Intelligence95% OFF Discount Coupon

Machine Learning & Neural Networks for Computer Vision, Time Series Analysis, NLP, GANs, Reinforcement Learning, +More!

4.5 out of 5
64,224 students
Created by Lazy Programmer Team, Lazy Programmer Inc.
English
Updated January 2026

Quick Facts — Course Summary

Here's a quick overview of everything you need to know about [2026] Tensorflow 2: Deep Learning & Artificial Intelligence before you enroll:

Course Name: [2026] Tensorflow 2: Deep Learning & Artificial Intelligence
Platform: Udemy
Instructor: Lazy Programmer Team, Lazy Programmer Inc.
Coupon Last Verified: January 6, 2026
Level: All Levels
Topic: Development
Subtopic: Deep Learning
Total Time: 26h of video content
Language: English
Access Type: Unlimited lifetime access + updates
Certificate: Included upon completion from Udemy
Main Skills: Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs) · Predict Stock Returns · Time Series Forecasting
Requirements: Know how to code in Python and Numpy · For the theoretical parts (optional), understand derivatives and probability
Current Price: $9.99 (was $199.99). You save $190.00 with 95% discount.
How to Apply: Click the coupon button to activate your discount automatically
💡
Tip:For best results, apply the coupon in a regular browser window rather than incognito/private mode.

Skills You'll Master

By the end of [2026] Tensorflow 2: Deep Learning & Artificial Intelligence, you'll have these practical skills:

Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs) .
Predict Stock Returns .
Time Series Forecasting .
Computer Vision .
How to build a Deep Reinforcement Learning Stock Trading Bot .
GANs (Generative Adversarial Networks) .
Recommender Systems .
Image Recognition .
Convolutional Neural Networks (CNNs) .
Recurrent Neural Networks (RNNs) .
Use Tensorflow Serving to serve your model using a RESTful API .
Use Tensorflow Lite to export your model for mobile (Android, iOS) and embedded devices .
Use Tensorflow's Distribution Strategies to parallelize learning .
Low-level Tensorflow, gradient tape, and how to build your own custom models .
Natural Language Processing (NLP) with Deep Learning .
Demonstrate Moore's Law using Code .
Transfer Learning to create state-of-the-art image classifiers .
Earn the Tensorflow Developer Certificate .
Understand important foundations for OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion.

What You Need Before Starting

Before enrolling in [2026] Tensorflow 2: Deep Learning & Artificial Intelligence, make sure you have:

Know how to code in Python and Numpy
For the theoretical parts (optional), understand derivatives and probability

About This Udemy Course

The following is the full official course description for [2026] Tensorflow 2: Deep Learning & Artificial Intelligence as published on Udemy by instructor Lazy Programmer Team, Lazy Programmer Inc.:

Ever wondered how AI technologies like OpenAI ChatGPT, GPT-4, DALL-E, Midjourney, and Stable Diffusion really work? In this course, you will learn the foundations of these groundbreaking applications.

Welcome to Tensorflow 2.0!

What an exciting time. It's been nearly 4 years since Tensorflow was released, and the library has evolved to its official second version.

Tensorflow is Google's library for deep learning and artificial intelligence.

Deep Learning has been responsible for some amazing achievements recently, such as:

  • Generating beautiful, photo-realistic images of people and things that never existed (GANs)
  • Beating world champions in the strategy game Go, and complex video games like CS:GO and Dota 2 (Deep Reinforcement Learning)
  • Self-driving cars (Computer Vision)
  • Speech recognition (e.g. Siri) and machine translation (Natural Language Processing)
  • Even creating videos of people doing and saying things they never did (DeepFakes - a potentially nefarious application of deep learning)
Tensorflow is the world's most popular library for deep learning, and it's built by Google, whose parent Alphabet recently became the most cash-rich company in the world (just a few days before I wrote this). It is the library of choice for many companies doing AI and machine learning.

In other words, if you want to do deep learning, you gotta know Tensorflow.

This course is for beginner-level students all the way up to expert-level students. How can this be?

If you've just taken my free Numpy prerequisite, then you know everything you need to jump right in. We will start with some very basic machine learning models and advance to state of the art concepts.

Along the way, you will learn about all of the major deep learning architectures, such as Deep Neural Networks, Convolutional Neural Networks (image processing), and Recurrent Neural Networks (sequence data).

Current projects include:

  • Natural Language Processing (NLP)
  • Recommender Systems
  • Transfer Learning for Computer Vision
  • Generative Adversarial Networks (GANs)
  • Deep Reinforcement Learning Stock Trading Bot

Even if you've taken all of my previous courses already, you will still learn about how to convert your previous code so that it uses Tensorflow 2.0, and there are all-new and never-before-seen projects in this course such as time series forecasting and how to do stock predictions.

This course is designed for students who want to learn fast, but there are also "in-depth" sections in case you want to dig a little deeper into the theory (like what is a loss function, and what are the different types of gradient descent approaches).

Advanced Tensorflow topics include:

  • Deploying a model with Tensorflow Serving (Tensorflow in the cloud)
  • Deploying a model with Tensorflow Lite (mobile and embedded applications)
  • Distributed Tensorflow training with Distribution Strategies
  • Writing your own custom Tensorflow model
  • Converting Tensorflow 1.x code to Tensorflow 2.0
  • Constants, Variables, and Tensors
  • Eager execution
  • Gradient tape

Instructor's Note: This course focuses on breadth rather than depth, with less theory in favor of building more cool stuff. If you are looking for a more theory-dense course, this is not it. Generally, for each of these topics (recommender systems, natural language processing, reinforcement learning, computer vision, GANs, etc.) I already have courses singularly focused on those topics.

Thanks for reading, and I’ll see you in class!

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)

UNIQUE FEATURES

  • Every line of code explained in detail - email me any time if you disagree
  • No wasted time "typing" on the keyboard like other courses - let's be honest, nobody can really write code worth learning about in just 20 minutes from scratch
  • Not afraid of university-level math - get important details about algorithms that other courses leave out

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Is the [2026] Tensorflow 2: Deep Learning & Artificial Intelligence Coupon Worth It?

Expert review by Andrew Derek, Lead Course Analyst at CoursesWyn.Last updated: January 6, 2026.

Based on analysis of the curriculum structure, student engagement metrics, and verified rating data, [2026] Tensorflow 2: Deep Learning & Artificial Intelligence is a high-value resource for learners seeking to build skills inDevelopment. Taught by Lazy Programmer Team, Lazy Programmer Inc. on Udemy, the 26h 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 95%, from $199.99 to $9.99, removing the primary financial barrier to enrollment.

What We Like (Pros)

  • Verified 95% price reduction makes this course accessible to learners on any budget.
  • Aggregate student rating of 4.5 out of 5 indicates high learner satisfaction.
  • Strong enrollment base with over 64,224 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 [2026] Tensorflow 2: Deep Learning & Artificial Intelligence:

  • 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

[2026] Tensorflow 2: Deep Learning & Artificial Intelligence Course holds an aggregate rating of 4.5 out of 5 based on 64,224 student reviews on Udemy.

4.5
★★★★★
64,224 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 Lazy Programmer Team, Lazy Programmer Inc., the instructor responsible for creating and maintaining [2026] Tensorflow 2: Deep Learning & Artificial Intelligence on Udemy.

[2026] Tensorflow 2: Deep Learning & Artificial Intelligence is taught by Lazy Programmer Team, Lazy Programmer Inc., 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: Lazy Programmer Team, Lazy Programmer Inc.
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 [2026] Tensorflow 2: Deep Learning & Artificial Intelligence, 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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