PyTorch for Deep Learning with Python Bootcamp (Udemy.com)
Learn how to create state of the art neural networks for deep learning with Facebook's PyTorch Deep Learning library!
Created by: Jose Portilla
Last updated September 2023
Our take
Based on the ratings of 5,633 students, a sample of their written reviews and the syllabus, as the course stood in September 2023. No course pays to be reviewed.
This is a 17-hour, 97-lecture PyTorch course from Jose Portilla, last updated in September 2023. It opens with short crash courses in NumPy and pandas, then covers PyTorch basics and machine learning concepts before the bulk of the time goes to ANNs, CNNs and RNNs. A GPU section and a short NLP section close it out. The audience line says intermediate to advanced Python developers, but reviewers call it a solid introduction. Basic Python and some derivative calculus are expected.
Most of the praise is about the teaching. Reviewers describe Jose as clear and to the point, with well-organized notes, and several mention fast answers on the Q&A board. About 5,200 of 5,633 ratings are four or five stars. The complaints are consistent, though. Theory gets hand-waved, the RNN and LSTM sections are light, and the embeddings lectures lose some students. One reviewer found the exercises were mostly lecture code copied over. Another says the NumPy, pandas and machine learning sections could have been more PyTorch.
The bigger issue is age. Several recent reviewers say the material feels dated, with library versions that no longer match, and one wants Transformers added. The Q&A board helped some of them sort out version problems. It is a low-cost, reasonable way to get a first working sense of PyTorch if you are comfortable with Python. Plan to practice on your own datasets and check current docs as you go. Anyone after modern PyTorch practice should look elsewhere.
Pros
- Jose's explanations are described as clear and to the point, with well-organized notes
- Q&A board gets quick answers from the helpers, per several reviewers
- Covers ANN, CNN, RNN and NLP in one 17-hour path, with about 5,200 four and five star ratings
- Short NumPy and pandas crash courses (about two hours combined) come before the PyTorch work
Cons
- Material is dated: library versions drift from the lectures, per 2025 and 2026 reviewers
- Theory is hand-waved, and the RNN, LSTM and embeddings parts feel thin
- Exercises mostly repeat the lecture code, and Udemy lists zero coding exercises
Great course!! Clear explanations of the theory and code, super fast feedback on the Q&A board. Love it!
Listed as All Levels, but it assumes basic Python and derivatives, and the audience line says intermediate.
What you will learn
- Learn how to use NumPy to format data into arrays
- Use pandas for data manipulation and cleaning
- Learn classic machine learning theory principals
- Use PyTorch Deep Learning Library for image classification
- Use PyTorch with Recurrent Neural Networks for Sequence Time Series Data
- Create state of the art Deep Learning models to work with tabular data
Course content
12 sections · 97 lectures · 17 hours of video 1 quiz, 2 articles
- 1Course Overview, Installs, and Setup 1 free preview2 lectures · 25 min
- 2COURSE OVERVIEW CONFIRMATION CHECK1 quiz
- 3Crash Course: NumPy7 lectures · 46 min
- 4Crash Course: Pandas9 lectures · 1.2 hours
- 5PyTorch Basics 1 free preview7 lectures · 55 min
- 6Machine Learning Concepts Overview 1 free preview6 lectures · 47 min
- 7ANN - Artificial Neural Networks 1 free preview22 lectures · 4.7 hours
- 8CNN - Convolutional Neural Networks 1 free preview22 lectures · 4.4 hours
- 9Recurrent Neural Networks12 lectures · 2.2 hours
- 10Using a GPU with PyTorch and CUDA2 lectures · 31 min
- 11NLP with PyTorch7 lectures · 1.1 hours
- 12BONUS SECTION: THANK YOU!1 lecture
Who it is for
The instructor says it suits
- Intermediate to Advanced Python Developers wanting to learn about Deep Learning with PyTorch
What you need before you start
- Understanding of Python Basic Topics (data types,loops,functions) also Python OOP recommended
- Be able to work through basic derivative calculations
- Admin Permissions on your computer (ability to download our files)
How it compares
Against the other 126 rated Udemy courses in Deep Learning on CourseDuck:
- Rating4.5 out of 5higher than 46% of them
- Reviews5,633#18 of 127 by number of reviews
- Length17 hourslonger than 74% of them
- Last updatedSeptember 2023earlier than 66% of them
Course Description
Welcome to the best online course for learning about Deep Learning with Python and PyTorch!
PyTorch is an open source deep learning platform that provides a seamless path from research prototyping to production deployment. It is rapidly becoming one of the most popular deep learning frameworks for Python. Deep integration into Python allows popular libraries and packages to be used for easily writing neural network layers in Python. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more.
This course focuses on balancing important theory concepts with practical hands-on exercises and projects that let you learn how to apply the concepts in the course to your own data sets! When you enroll in this course you will get access to carefully laid out notebooks that explain concepts in an easy to understand manner, including both code and explanations side by side. You will also get access to our slides that explain theory through easy to understand visualizations.
In this course we will teach you everything you need to know to get started with Deep Learning with Pytorch, including:
NumPy
Pandas
Machine Learning Theory
Test/Train/Validation Data Splits
Model Evaluation - Regression and Classification Tasks
Unsupervised Learning Tasks
Tensors with PyTorch
Neural Network Theory
Perceptrons
Networks
Activation Functions
Cost/Loss Functions
Backpropagation
Gradients
Artificial Neural Networks
Convolutional Neural Networks
Recurrent Neural Networks
and much more!
By the end of this course you will be able to create a wide variety of deep learning models to solve your own problems with your own data sets.
So what are you waiting for? Enroll today and experience the true capabilities of Deep Learning with PyTorch! I'll see you inside the course!
-Jose
Instructor Details
- 4.5 Rating
5,633 Reviews
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
By Bruno Ranschaert on 3/14/2026
The course starts pretty good, everything clear, but from the moment where Jose starts talking about embeddings (48, 15:40) it seems to me that a part is missing in the course. The jump from pytorch to actual use for machine learning is so big, one cannot understand it from this course alone. Many concepts are introduced with some hand waving that you have to research yourself.
By Frederik Vanaverbeke on 4/2/2024
This was a great course. It is very much to the point with relevant examples and great lecturing. I've done a course at MIT on data science and AI, but I felt they were force-feeding me with all sorts of examples, involving Python packages I had never heard of, without allowing the time to internalize the material. This is much more streamlined and I feel more confident about what I learned.
By Eduard A. Stefanescu on 8/24/2023
Simple, concise and straight to the point. Nothing to complain about. I'm sure there must be other useful PyTorch-related notions not covered here, but for the paid price this was a real bargain. Jose really knows how to craft material in an interesting manner and keep the viewer awake. I will also note that his helpers are also doing a pretty good job addressing any questions in pretty much real time. Udemy qualifies a 5-star review as material above expectations, but this level of quality is what I've come to expect from Jose.
By Jan Purchase on 2/1/2021
This is a typically great course form this capable instructor. The content spans a good range of subjects both theoretical and practical. Joes establishes a firm foundation of theory and practice before heading to the more advanced material. He covers lots of ground; I particularly liked the content on tabular neural networks, RNNs and CUDA. The exercises are well thought out. I only have to minor criticisms: the last section on NLP is rather rushed compared to the rest of the material (no exercises and not everything is explained). Also, occasionally (especially in the last section) Jose just types complex code and speaks it - without explaining or justifying his approach. This can be confusing. Nevertheless a great course which I strongly recommend.
By Luiz Gustavo da Rocha Charamba on 1/26/2021
The content course is good and the exercises are good for fixation and well explained, but the theoretical part such as backpropagation, CNN is poor, I felt missed good diagrams and/or graphs for explaining better these concepts. And the subtitles are automatically generated, several words are translated wrongs, which is bad for students that use the captions
By Dian Wei on 11/7/2020
Excellent course, a lot of details were provided which helps a lot.
Beyond expectation.
By Franck Edery on 11/7/2020
Explanations are very clear and projects are very well explained!
By Aanu Pelumi Olakunle on 10/24/2020
I am lucky to have this course. I love the course and I will gladly recommend beginner or anyone looking to learn Pytorch or Artificial Intelligence to first check out the course
By Osagie NOZE-OTOTE on 10/23/2020
This course is beautiful so far. I like that it starts with an overview. Reminding even more seasoned python programmers of some concepts we may have forgotten.
It then goes into more complex topics however the confidence gained from the earlier sections helps to overcome any fear . wonderful stuff
By Subrota Mondal on 10/21/2020
In my view, the best PyTorch course.
By Gaurav Kumar Yadav on 10/20/2020
Actually the way he guiding us, really good and appreciable. The one who not belong to computer science background can also understand. So it is really good explanation so for.
By Thomas Erian on 10/14/2020
Perfect
Quality Score
No CourseDuck member has rated this course yet. Taken it? Give each part a thumbs up or down.
Overall Score : 90 / 100












