Deep Learning: Convolutional Neural Networks in Python — 90% OFF Discount Coupon
Tensorflow 2 CNNs for Computer Vision, Natural Language Processing (NLP) +More! For Data Science & Machine Learning
Quick Facts — Course Summary
Here's a quick overview of everything you need to know about Deep Learning: Convolutional Neural Networks in Python before you enroll:
Skills You'll Master
By the end of Deep Learning: Convolutional Neural Networks in Python, you'll have these practical skills:
What You Need Before Starting
Before enrolling in Deep Learning: Convolutional Neural Networks in Python, make sure you have:
About This Udemy Course
The following is the full official course description for Deep Learning: Convolutional Neural Networks in Python as published on Udemy by instructor Lazy Programmer Team, Lazy Programmer Inc.:
Ever wondered how AI technologies like OpenAI ChatGPT, GPT-5, DALL-E, Midjourney, and Stable Diffusion really work? In this course, you will learn the foundations of these groundbreaking applications.
Learn about one of the most powerful Deep Learning architectures yet!
The Convolutional Neural Network (CNN) has been used to obtain state-of-the-art results in computer vision tasks such as object detection, image segmentation, and generating photo-realistic images of people and things that don't exist in the real world!
This course will teach you the fundamentals of convolution and why it's useful for deep learning and even NLP (natural language processing).
You will learn about modern techniques such as data augmentation and batch normalization, and build modern architectures such as VGG yourself.
This course will teach you:
- The basics of machine learning and neurons (just a review to get you warmed up!)
- Neural networks for classification and regression (just a review to get you warmed up!)
- How to model image data in code
- How to model text data for NLP (including preprocessing steps for text)
- How to build an CNN using Tensorflow 2
- How to use batch normalization and dropout regularization in Tensorflow 2
- How to do image classification in Tensorflow 2
- How to do data preprocessing for your own custom image dataset
- How to use Embeddings in Tensorflow 2 for NLP
- How to build a Text Classification CNN for NLP (examples: spam detection, sentiment analysis, parts-of-speech tagging, named entity recognition)
All of the materials required for this course can be downloaded and installed for FREE. We will do most of our work in Numpy, Matplotlib, and Tensorflow. I am always available to answer your questions and help you along your data science journey.
This course focuses on "how to build and understand", not just "how to use". Anyone can learn to use an API in 15 minutes after reading some documentation. It's not about "remembering facts", it's about "seeing for yourself" via experimentation. It will teach you how to visualize what's happening in the model internally. If you want more than just a superficial look at machine learning models, this course is for you.
Suggested Prerequisites:
- matrix addition and multiplication
- basic probability (conditional and joint distributions)
- Python coding: if/else, loops, lists, dicts, sets
- Numpy coding: matrix and vector operations, loading a CSV file
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
Is the Deep Learning: Convolutional Neural Networks in Python Coupon Worth It?
Based on analysis of the curriculum structure, student engagement metrics, and verified rating data, Deep Learning: Convolutional Neural Networks in Python is a high-value resource for learners seeking to build skills inDevelopment. Taught by Lazy Programmer Team, Lazy Programmer Inc. on Udemy, the 14h 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 90%, from $109.99 to $10.99, removing the primary financial barrier to enrollment.
✓What We Like (Pros)
- Verified 90% 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 47,075 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 Deep Learning: Convolutional Neural Networks in Python:
- 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.
Course Rating Summary
Deep Learning: Convolutional Neural Networks in Python Course holds an aggregate rating of 4.6 out of 5 based on 47,075 student reviews on Udemy.
* 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 Deep Learning: Convolutional Neural Networks in Python on Udemy.
Deep Learning: Convolutional Neural Networks in Python 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.
Frequently Asked Questions
The following questions and answers cover the most common queries about Deep Learning: Convolutional Neural Networks in Python, its coupon code, pricing, and enrollment process.
About the Author
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.
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