PyTorch certification offers hands-on training that will teach you the fundamentals of deep learning to help kickstart your career as a data scientist.
A certificate in PyTorch will allow you to show employers that you can apply your skill sets to real-world problems, demonstrate state-of-the-art techniques on real datasets, and solve complex machine learning problems.
Alternatively, suppose you want to learn more about PyTorch. In that case, it’s capable of many things, ranging from building deep neural networks and performing image recognition to enhancing natural language processing.
If this sounds like something you want to do, then check out our guide on getting certified in PyTorch. It’s time to take the first step towards mastering PyTorch and watch your skills grow.
1. Data Scientist Nanodegree Program (Udacity)
The Intro to Machine Learning with PyTorch Nanodegree from Udacity is an introductory program to learning how to leverage machine learning through Python using PyTorch. As machine learning becomes more accessible, the demand for people who are skilled in this field is rising.
The program covers the core concepts of supervised learning and deep learning through real-world applications with Python. By the end of this course, you will be able to implement machine learning models using the PyTorch framework.
- Supervised Learning: part of your project in this course, you will optimize a supervised learner to find the highest yielding donations for a fictitious charity.
- Deep Learning: Learn the basics of deep learning and how to build neural networks for image recognition. Then, put your skills to the test by creating your own neural network and see how it compares against existing ones.
- Unsupervised Learning: This course will teach you how to use unsupervised learning methods to segment customers into categories without any human input.
Apply today to start making a difference in the Intro to Machine Learning with PyTorch Nanodegree from Udacity. You’ll learn through a series of projects involving training neural networks, recognizing objects, and using various clustering techniques. Not only will you explore the world of PyTorch technology through projects, but you’ll also get to learn from experienced mentors and have access to experts who will help guide you throughout your journey.
|Duration||3 months (10 hours per week)|
|Certification||Intro to Machine Learning with PyTorch Nanodegree|
|Skills Acquired||PyTorch, Python, Neural Networks, Supervised Learning, Clustering, and Object Recognition|
2. Introduction to Deep Learning with PyTorch (DataCamp)
The Introduction to Deep Learning with PyTorch track from DataCamp will walk you through the steps necessary to get started with PyTorch so that you can get a successful introduction to machine learning and artificial intelligence. First, it will introduce you to the basics of PyTorch and then teach you how to use this Python library for several applications. Then, it will cover various topics such as artificial neural networks and convolutional neural networks (CNNs). By the end of this project-based course, you will be well-prepared to explore practical applications of deep learning models using PyTorch on your own.
- Introduction to PyTorch: This course is designed for people who have little to no experience with deep learning, but are interested in learning the fundamentals of neural networks and deep learning.
- Artificial Neural Networks: This course will help you understand artificial neural networks in the most accessible, easy to comprehend way possible.
- Convolutional Neural Networks (CNNs): This course teaches you how to make predictions using convolutional neural networks (CNNs), while also studying how to train them.
- Using Convolutional Neural Networks: With this course, you will progress from a basic understanding of how the architecture of a convolutional neural network works to how it is trained and when and why it might be considered for overfitting.
This online deep learning program will help you understand the foundations of PyTorch and deep learning, which is a popular machine learning technique. First, it provides an overview of the core concepts of deep learning, including convolutional networks and recurrent neural networks. Next, it also covers how to work with data in Python using the PyTorch library. Overall, the Introduction to Deep Learning with PyTorch from DataCamp lays a solid foundation to learn PyTorch and deep learning.
|Certification||Introduction to Deep Learning with PyTorch|
|Content||17 videos and 53 exercises|
|Skills Acquired||PyTorch, Convolutional Neural Networks, ReLU Activation, Torchvision|
3. Professional Certificate in Deep Learning (IBM)
With the Professional Certificate in Deep Learning from IBM, you will develop deep learning skills. First, you will start with the basics of building your own feel learning model. Next, you’ll explore PyTorch including convolutional networks and deep learning pipelines. Finally, you’ll conclude the program with an independent capstone project to test your skills and knowledge.
- PyTorch Basics for Machine Learning: Get a strong foundation of machine learning concepts to jump into deep learning and neural network design, leveraging the power of PyTorch.
- Deep Learning with Python and PyTorch: This course is aimed at people who have a basic understanding of PyTorch. It will teach you the concepts and skills you need to design and build deep learning models that can be used for a variety of problems.
- Applied Deep Learning Capstone Project: You will learn a variety of advanced machine learning techniques in this capstone project course. You’ll use either the Keras or PyTorch framework and apply your knowledge to test and develop a deep learning model.
The Professional Certificate in Deep Learning from IBM will teach you the fundamentals of deep learning, with an emphasis on practical applications. You’ll learn how to design, build, and deploy your own deep learning models using multiple frameworks such as PyTorch, TensorFlow, and Keras. In addition to gaining the skills required to create your own deep learning models, this course will also help you understand what makes a successful deep learning model and how it can be implemented in real-world business scenarios with a capstone project.
|Duration||7 months (2 hours per week)|
|Certification||Professional Certificate in Deep Learning|
|Skills Acquired||TensorFlow, PyTorch, Keras, Deep Learning Models|
PyTorch Certification To Kickstart Your Career
PyTorch certification can prove your proficiency using this open-source machine learning framework. For instance, you’ll learn how to create models and train them on images and other types of data sets.
You’ll also be able to use these models as part of your own projects and research solutions for real-world problems. Upon completion of these PyTorch certification courses, it can help give you a kickstart in the AI and data science space.
Not only can it help you stand out from others, but it can also give you an edge in your current career.
Are you thinking about enrolling in any of these PyTorch certification courses? Yes? Then, get started today and break into this booming industry to land your dream job. Otherwise, here are more certification programs in the realm of machine learning, artificial intelligence, and data science.