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The Pytorch basics you need to start your ML projects

Gaspard Baye

In this 1-hour long project-based course, you will learn how to use simple commands to create and manipulate files and folders, perform multiple complex tasks using one simple command, use the superuser to perform high privilege operations.

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What's inside

Syllabus

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Explores simple and complex Linux commands to automate systems operations

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Reviews summary

Beginner's fast track to pytorch ml

According to learners, this course offers a clear and concise introduction to PyTorch basics, making it ideal for those new to the framework. Students particularly appreciate the hands-on, project-based approach, which helps solidify understanding of core concepts like tensors, neural network modules, and optimizers. While it provides a solid foundation for starting ML projects, some note its brevity and focus purely on basics, meaning it serves as an excellent starting point rather than a comprehensive deep dive. The pace is generally well-received, though absolute programming beginners might find it moves quickly.

A quick, focused overview; ideal for a rapid start.

"It's a one-hour project, so it's very concise, which is great for a quick introduction."

"The course moves at a good pace, covering a lot in a short amount of time."

"While it's fast, I found the pace appropriate for someone with a basic Python background."

"I was able to get up and running with PyTorch basics in just an hour, very efficient."

Effectively introduces essential PyTorch components.

"It gave me a good understanding of tensors, optimizers, and the basic neural network module in PyTorch."

"I now understand how to initialize and use tensors, and the basic ML training loop is much clearer."

"The coverage of fundamental PyTorch modules was spot on for a beginner's course."

"Learned about the core components needed to start any basic machine learning project in PyTorch."

The project-based learning effectively applies concepts.

"The hands-on project made learning PyTorch so much more practical and engaging."

"I really benefited from the practical examples and the basic ML training loop demonstration."

"Learning by doing through the project was key to grasping how to use PyTorch effectively."

"The course is very practical; I could immediately apply what I learned to my own small projects."

A perfect entry point for those new to PyTorch and ML.

"This course is absolutely perfect for an absolute beginner in PyTorch. It explains concepts very clearly."

"I found this project extremely helpful as a quick introduction to PyTorch and its fundamental concepts for ML."

"As a beginner, I needed something to get me started with PyTorch, and this course delivered exactly that."

"This is an ideal course for beginners to understand the PyTorch fundamentals, especially the basic ML training loop."

Focuses on basics, not for advanced or detailed study.

"This is strictly a basic introduction; don't expect deep dives into complex topics."

"While excellent for beginners, more experienced users won't find much new content."

"It lays a strong foundation, but I will definitely need to supplement this with more advanced courses."

"Due to its 1-hour length, it can't cover everything, so it's only for the absolute essentials."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in The Pytorch basics you need to start your ML projects with these activities:

Read "Deep Learning with PyTorch" by Eli Stevens, Luca Antiga, and Thomas Viehmann

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Gain a comprehensive understanding of PyTorch by reading a book that covers the core concepts and advanced techniques.

View Deep Learning with PyTorch: Build, train, and... on Amazon

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Purchase or borrow the book
Read the book thoroughly, taking notes and highlighting important concepts
Complete the exercises and examples provided in the book
Discuss the book with others or join online forums for further insights

Follow PyTorch video tutorials

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Expand your knowledge by following online video tutorials that cover advanced PyTorch concepts or techniques.

Browse courses on Deep Learning

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Find reputable video tutorials on PyTorch
Watch the videos and take notes
Practice the concepts and techniques demonstrated in the videos
Ask questions or seek clarification if needed

Solve PyTorch coding challenges

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Reinforce your understanding by practicing PyTorch coding skills through online challenges or exercises.

Browse courses on Deep Learning

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Find coding challenges or exercises online
Attempt to solve the challenges or exercises
Review your solutions and identify areas for improvement
Seek help or guidance if needed

Five other activities

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Show all eight activities

Mentor other PyTorch learners

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Consolidate your understanding by mentoring other learners and helping them overcome challenges.

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Identify opportunities to mentor others, such as online forums or study groups
Provide guidance, support, and encouragement to other learners
Review your own understanding of PyTorch through the process of teaching others
Seek feedback from your mentees to improve your mentoring skills

Attend a PyTorch workshop

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Enhance your learning through hands-on experience and networking at a PyTorch workshop or conference.

Browse courses on Deep Learning

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Find and register for a reputable PyTorch workshop or conference
Attend the workshop or conference and actively participate in sessions
Network with other attendees and industry experts
Follow up on any connections or opportunities that arise

Create a PyTorch project

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Demonstrate your understanding of PyTorch by creating a small project that uses the concepts covered in the course.

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Define the project scope and goals
Gather the necessary data and resources
Design and implement the PyTorch model
Train and evaluate the model

Develop a PyTorch tutorial

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Enhance your understanding by creating a tutorial that explains a specific PyTorch concept or technique.

Browse courses on Deep Learning

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Choose a topic and gather the necessary information
Write the tutorial content, including code examples and explanations
Review and edit the tutorial for clarity and accuracy
Publish the tutorial online or share it with others

Create a PyTorch resources compilation

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Enhance your learning and contribute to the PyTorch community by compiling a collection of valuable resources.

Browse courses on Deep Learning

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Gather and organize relevant PyTorch resources, such as tutorials, articles, and code examples
Annotate the resources with brief descriptions and tags
Share the compilation with other learners through a blog post, GitHub repository, or other platform
Update and maintain the compilation over time to ensure its relevance

Career center

Learners who complete The Pytorch basics you need to start your ML projects will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use machine learning to extract insights from data. This course provides the foundation for understanding and using PyTorch, an open source machine learning library. With the knowledge and skills gained in this course, you will be able to build and train your own machine learning models, a key skill for Data Scientists.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models. This course can help you gain the necessary skills to become a Machine Learning Engineer. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Machine Learning Engineer

Software Engineer

Software Engineers design, develop, and maintain software systems. This course can help you gain the skills needed to become a Software Engineer. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Software Engineer

Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. This course can help you gain the skills needed to become a Data Analyst. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Data Analyst

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. This course can help you gain the skills needed to become a Quantitative Analyst. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Quantitative Analyst

Business Analyst

Business Analysts use data to analyze business processes and identify areas for improvement. This course can help you gain the skills needed to become a Business Analyst. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Business Analyst

Product Manager

Product Managers oversee the development and launch of new products. This course can help you gain the skills needed to become a Product Manager. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Product Manager

Project Manager

Project Managers plan and execute projects. This course can help you gain the skills needed to become a Project Manager. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Project Manager

Technical Writer

Technical Writers create documentation for software and hardware products. This course can help you gain the skills needed to become a Technical Writer. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Technical Writer

Systems Analyst

Systems Analysts analyze and design computer systems. This course can help you gain the skills needed to become a Systems Analyst. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Systems Analyst

Database Administrator

Database Administrators manage and maintain databases. This course can help you gain the skills needed to become a Database Administrator. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Database Administrator

Computer Programmer

Computer Programmers write and maintain computer programs. This course can help you gain the skills needed to become a Computer Programmer. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Computer Programmer

Network Administrator

Network Administrators manage and maintain computer networks. This course can help you gain the skills needed to become a Network Administrator. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Network Administrator

Computer Support Specialist

Computer Support Specialists provide technical support to computer users. This course can help you gain the skills needed to become a Computer Support Specialist. You will learn how to use PyTorch to create and manipulate files and folders, perform multiple complex tasks using one simple command, and use the superuser to perform high privilege operations.

See salaries and explore the career path for Computer Support Specialist

Information Security Analyst

Information Security Analysts protect computer systems from unauthorized access, use, disclosure, disruption, modification, or destruction. This course may help you gain the skills needed to become an Information Security Analyst.

See salaries and explore the career path for Information Security Analyst

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in The Pytorch basics you need to start your ML projects .

Pattern Recognition and Machine Learning

Save

A classic textbook on pattern recognition and machine learning, covering a wide range of topics and techniques. A valuable reference for those interested in a deeper understanding of machine learning.

Pattern Recognition and Machine Learning...

Pattern Recognition and Machine Learning...

Pattern Recognition and Machine Learning (text...

Unknown Binding

Cover image

Cover image

Save

An advanced textbook on deep learning, covering a wide range of topics and techniques. A valuable reference for those interested in a deeper understanding of deep learning.

Deep Learning (Adaptive Computation and Machine...

Deep Learning (Adaptive Computation and Machine...

Cover image

Cover image

Artificial Intelligence

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A comprehensive and widely-used textbook on AI, covering a range of topics including machine learning. A valuable reference and offers a broader perspective on AI.

Artificial Intelligence: A Modern Approach, Global...

Artificial Intelligence: A Modern Approach (Pearson...

Human Compatible: Artificial Intelligence and the...

Pearson Artificial Intelligence: A Modern Approach,...

Artificial Intelligence: A Modern Approach

Artificial Intelligence: A Modern Approach

Artificial Intelligence: A Modern Approach

Do the Right Thing: Studies in Limited Rationality...

(中文) Artificial Intelligence: A Modern Approach (4th...

Artificial Intelligence: A Modern Approach (Pearson...

Human Compatible: Artificial Intelligence and the...

Cover image

Cover image

Deep Learning with PyTorch

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Teaches you how to design and implement machine learning models using PyTorch, while emphasizing practical aspects of training, evaluating, and deploying your models.

Deep Learning with PyTorch: Build, train, and tune...

Deep Learning with PyTorch: Build, train, and tune...

Cover image

Cover image

Machine Learning Engineering

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Provides a concise and accessible introduction to machine learning concepts. A useful refresher or as background material for this course.

Machine Learning Engineering

Machine Learning Engineering

Cover image

Cover image

Natural Language Processing with PyTorch

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Covers a range of NLP tasks using PyTorch and provides hands-on tutorials. A valuable supplemental resource for applying your PyTorch skills to NLP.

Natural Language Processing with PyTorch: Build...

(Deutsch) Natural Language Processing mit PyTorch:...

(中文) Based on natural language processing...

Cover image

Cover image

Deep Learning with Python

Save

Covers a range of TensorFlow-based projects, including a helpful introduction to PyTorch. Useful if you wish to work with TensorFlow, but the PyTorch-specific parts of this book would be helpful for this course.

Deep Learning with Python: Learn Best Practices of...

Deep Learning with Python: A Hands-on Introduction

Deep Learning with Python: Learn Best Practices of...

Deep Learning with Python: A Hands-on Introduction

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Effort

1hour

Level

Intermediate

Via

Coursera

Institution

Coursera Project Network

Instructor

Gaspard Baye

Language

English

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Explores simple and complex Linux commands to automate systems operations

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