[2026] Tensorflow 2: Deep Learning & Artificial Intelligence — 95% Off Coupon

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

⭐ 4.5 out of 5 Rating (64,224 students) Created by Lazy Programmer Team, Lazy Programmer Inc. Updated: January 6, 2026 🌐 English

Key Takeaways

A summarized snapshot of the essential course data, author credentials, and live coupon verification statistics from our manual technical audit.

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Course Title: [2026] Tensorflow 2: Deep Learning & Artificial Intelligence

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Provider: Udemy (Listed via CoursesWyn)

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Instructor: Lazy Programmer Team, Lazy Programmer Inc.

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Coupon Verified On: January 6, 2026

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Difficulty Level: All Levels

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Category: Development

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Subcategory: Deep Learning

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Duration: 26h of on-demand video

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Language: English

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Access: Lifetime access to all course lectures and updates

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Certificate: Official certificate of completion issued by Udemy upon finishing all course requirements

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Top Learning Outcomes: Artificial Neural Networks (ANNs) / Deep Neural Networks (DNNs) · Predict Stock Returns · Time Series Forecasting

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

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Price: $9.99 with coupon / Regular Udemy price: $199.99. Applying this coupon saves you $190.00 (95% OFF).

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Coupon: Click REDEEM COUPON below to apply discount

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What You'll Learn

The following technical skills represent the core curriculum targets for learners enrolling in this verified program today.

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

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Requirements

Please review the following prerequisites to ensure you have the necessary tools and foundational knowledge for this training.

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Know how to code in Python and Numpy

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For the theoretical parts (optional), understand derivatives and probability

About This Course

Comprehensive curriculum analysis and educational value proposition from the official provider library hubs.

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

Meet Your Instructor

Academic background and professional track record of the subject matter expert responsible for this curriculum.

Lazy Programmer Team, Lazy Programmer Inc.

Verified Architect

A global leader with specialized excellence in Development. Instructors are vetted for curriculum quality, responsiveness, and consistent student success across the Udemy platform.

4.8 / 5.0

Instructor Rating

94% +

Success Rate

Course Comparison

Market-relative value analysis comparing this verified instructor deal against professional subscription and retail averages.

Feature Benchmarks	This Verified Offer	Global Standard
Cost Verification	FREE (100% Validated)	Fixed Subscription Fee
Enrollment Type	Professional Lifetime Access	Limited Time Ownership
Certification Award	Included with Access Code	Required Add-on Fee

Expert Review

Andrew Derek

Lead Course Analyst, CoursesWyn

"After auditing the curriculum depth and verifying the live access protocol, [2026] Tensorflow 2: Deep Learning & Artificial Intelligence stands as an essential career asset. For a verified cost of $0, the return-on-learning ratio far exceeds commercial alternatives."

✅ Strategic Advantages

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Official Certificate: Credential generated at no cost.
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Mobile Friendly: Full access via smart TV & mobile.
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Expert Pacing: Modular design for professional schedules.

❌ Considerations

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Technical Depth: Requires focused 10+ hours study.
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Tool Prep: Certain labs require proprietary software setups.

Verification Outcome: Exceptional Academic Value

Course Rating

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4.5

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Frequently Asked Questions

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Andrew Derek

Expert Reviewer

Andrew 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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