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Getting Started with PyTorch

In this 1.5-hour long project-based course, you will learn how to use one of the most popular deep learning frameworks, PyTorch. You will discover PyTorch data structure and perform various tasks with it. PyTorch is more customizable than other deep learning frameworks like Keras. In your journey to become a Data Scientist or implement deep learning projects PyTorch will surly become useful. By the end of this project you will have good understanding of loading and manipulating data in PyTorch, using GPU in PyTorch for reaching much higher performance and also implement linear regression and start understanding building neural...

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Provides foundation in essential PyTorch fundamentals and concepts

Emphasizes the use of GPUs to optimize performance, aligning with industry standards

Introduces the PyTorch data structure, widening understanding of deep learning frameworks

Builds a foundation for neural network construction in PyTorch

Applicable to both aspiring data scientists and deep learning implementors, catering to a range of learners

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Reviews summary

Pytorch basic introduction

Students found the course as a very brief introduction to PyTorch, only covering the basic concepts and not going into detail. Many students mentioned that the course was not worth the money and that they could have learned the same material from the PyTorch documentation or a 10-minute video.

Difficult to understand explanations.

"...difficult to understand the English of the instructor..."

Instructor was difficult to understand and not engaging.

"The instructor sounded utterly bored out of his brain..."

"...nor a clear speaking manner..."

Not worth the cost.

"...definitely not worth the money..."

"...Could have been better edited. Way too expensive for what I got..."

Only covers basic concepts.

"This course is very preliminary..."

"The material covered the bare-bones basics of PyTorch..."

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 Getting Started with PyTorch with these activities:

Review Linear Algebra

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By reviewing basic concepts in Linear Algebra, you will strengthen your grasp on a necessary mathematical foundation for this course.

Browse courses on Linear Algebra

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Review matrix operations, such as addition, subtraction, multiplication, and determinants.
Practice solving systems of linear equations using methods like Gaussian elimination.
Study the concepts of vector spaces, subspaces, and linear independence.

Identify PyTorch Mentors

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Connecting with mentors can provide you with guidance and support throughout your PyTorch learning journey, accelerating your progress.

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Reach out to individuals in your professional network or online communities who have experience with PyTorch.
Request mentorship or guidance on specific PyTorch-related topics.

PyTorch Tensors Exercises

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Working through these exercises will provide you with hands-on experience manipulating and working with PyTorch tensors, a fundamental building block in PyTorch.

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Create PyTorch tensors of different shapes and data types.
Perform basic operations on tensors, such as slicing, indexing, and broadcasting.
Practice tensor reshaping and concatenation.
Implement simple mathematical operations on tensors, like addition, subtraction, and multiplication.

Two other activities

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PyTorch Neural Network Tutorial

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Following a guided tutorial on building neural networks with PyTorch will provide you with a practical understanding of how to construct and train deep learning models using PyTorch.

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Learn about different neural network architectures, such as feedforward networks and convolutional neural networks.
Implement a simple neural network model in PyTorch, including defining the network architecture, forward pass, and loss function.
Train the neural network model on a toy dataset, using techniques like gradient descent and backpropagation.
Evaluate the performance of the trained neural network model.

Personal PyTorch Project

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Embarking on a personal project will challenge you to apply your PyTorch skills to a topic of your interest, fostering your creativity and deepening your understanding.

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Identify a problem or task that you are interested in solving using PyTorch.
Research and gather the necessary resources, such as datasets and libraries.
Design and implement a PyTorch-based solution to the problem.
Evaluate the results of your project and make improvements as needed.
Document your project, including your approach, results, and any challenges encountered.

Career center

Learners who complete Getting Started with PyTorch will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists gather, analyze, and interpret large amounts of data to help organizations understand trends and make informed decisions. This course introduces PyTorch, a powerful deep learning framework, which is an essential tool for data scientists. By completing this course, you will gain a solid foundation in PyTorch, enabling you to build and deploy deep learning models effectively.

See salaries and explore the career path for Data Scientist

Deep Learning Engineer

Deep Learning Engineers specialize in developing and deploying deep learning models. PyTorch is a widely adopted framework in the field of deep learning. This course offers a practical introduction to PyTorch, equipping you with the knowledge and skills to excel as a Deep Learning Engineer. You will gain hands-on experience in building and training deep learning models, enabling you to pursue a successful career in this rapidly growing field.

See salaries and explore the career path for Deep Learning Engineer

Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning models. PyTorch is a popular deep learning framework used by Machine Learning Engineers to build complex and accurate models. This course provides a comprehensive introduction to PyTorch, helping you develop the skills necessary to succeed in this role. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

See salaries and explore the career path for Machine Learning Engineer

Artificial Intelligence Engineer

Artificial Intelligence Engineers design, develop, and deploy AI systems. PyTorch is a popular framework for deep learning, which is a fundamental component of AI. This course will provide you with a solid foundation in PyTorch, enabling you to build and deploy deep learning models for AI applications. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

See salaries and explore the career path for Artificial Intelligence Engineer

Data Analyst

Data Analysts collect, clean, and analyze data to help organizations make informed decisions. PyTorch, a powerful deep learning framework, can enhance data analysis capabilities. This course introduces the basics of PyTorch, providing you with the skills to build and deploy deep learning models for data analysis tasks. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

See salaries and explore the career path for Data Analyst

Business Intelligence Analyst

Business Intelligence Analysts use data to help businesses understand their performance and make strategic decisions. PyTorch, a powerful deep learning framework, can enhance business intelligence capabilities. This course introduces the basics of PyTorch, providing you with the skills to build and deploy deep learning models for business intelligence tasks. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

See salaries and explore the career path for Business Intelligence Analyst

Software Engineer

Software Engineers design, develop, and maintain software systems. PyTorch is a popular framework for deep learning, which is a rapidly growing field in software engineering. This course provides a comprehensive introduction to PyTorch, helping you develop the skills necessary to succeed in this role. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

See salaries and explore the career path for Software Engineer

Quantitative Analyst

Quantitative Analysts use mathematical and statistical methods to analyze financial data. PyTorch, a powerful deep learning framework, can enhance quantitative analysis capabilities. This course introduces the basics of PyTorch, providing you with the skills to build and deploy deep learning models for quantitative analysis tasks. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

See salaries and explore the career path for Quantitative Analyst

Research Scientist

Research Scientists conduct research in various scientific fields. PyTorch, a powerful deep learning framework, is widely used in scientific research. This course provides a comprehensive introduction to PyTorch, helping you develop the skills necessary to succeed in this role. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

See salaries and explore the career path for Research Scientist

Data Engineer

Data Engineers design, build, and maintain data infrastructure. PyTorch, a powerful deep learning framework, can enhance data engineering capabilities. This course introduces the basics of PyTorch, providing you with the skills to build and deploy deep learning models for data engineering tasks. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

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Project Manager

Project Managers plan, execute, and close projects. PyTorch, a powerful deep learning framework, can enhance project management capabilities. This course introduces the basics of PyTorch, providing you with the skills to build and deploy deep learning models for project management tasks. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

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Product Manager

Product Managers define the vision and roadmap for products. PyTorch, a powerful deep learning framework, is increasingly used in product development. This course provides a comprehensive introduction to PyTorch, helping you develop the skills necessary to succeed in this role. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

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Consultant

Consultants provide advice and guidance to organizations. PyTorch, a powerful deep learning framework, can enhance consulting capabilities. This course introduces the basics of PyTorch, providing you with the skills to build and deploy deep learning models for consulting tasks. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

See salaries and explore the career path for Consultant

Analyst

Analysts gather, analyze, and interpret data to help organizations make informed decisions. PyTorch, a powerful deep learning framework, can enhance analytical capabilities. This course introduces the basics of PyTorch, providing you with the skills to build and deploy deep learning models for analytical tasks. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

See salaries and explore the career path for Analyst

Software Developer

Software Developers design, develop, and maintain software applications. PyTorch, a powerful deep learning framework, is increasingly used in software development. This course provides a comprehensive introduction to PyTorch, helping you develop the skills necessary to succeed in this role. You will learn how to load and manipulate data, utilize GPUs for performance optimization, and implement linear regression and neural network models.

See salaries and explore the career path for Software Developer

Reading list

We've selected 13 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 Getting Started with PyTorch.

Deep Learning

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Provides a comprehensive overview of deep learning, covering both theoretical and practical aspects. It great resource for anyone who wants to learn more about deep learning and how to apply it to real-world problems.

Getting Started with PyTorch

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Reviews summary

Pytorch basic introduction

Activities

Career center

Reading list

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