Brochure
Enquire- Learn the concepts behind how neural networks operate and how we train them using data.
Online
Quick facts
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Medium of instructions
English
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Mode of learning
Self study, Virtual Classroom
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Mode of Delivery
Video and Text Based
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Course overview
There is no doubt that the AI revolution is being driven by deep learning. Machine learning and AI are gaining popularity as it helps make data-driven business decisions. With a deep understanding of AI & ML, you can take your business to an all-new level. PyTorch makes it convenient to build applications used for deep learning. The programme will teach you how to build and train deep neural networks using Pytorch. This practical experience would hone your skills to use them in your personal projects.
Intro to Deep Learning with PyTorch online course explores how to use PyTorch using coding exercises and projects. This will help you implement state-of-the-art AI applications such as text generation and style transfer. This is a free course that offers instructional videos, interactive quizzes, and self-paced learning.
Intro to Deep Learning with PyTorch takes about two weeks to complete. This is an intermediate-level course and requires a working knowledge of Python and its libraries Matplotlib and NumPy. The industry experts for this course are a panel of five educators: Matt Leonard, Soumith Chintala, Luis Serrano, Cezanne Camacho, and Alexis Cook.
The highlights
- Self-paced type learning
- Free training from industry experts
- Quizzes and high-quality content
Program offerings
- Self-paced
- Intermediate level course
- Two months course
- High-quality video lessons
- Free training
- Quizzes
- Industry experts
Course and certificate fees
certificate availability
No
Eligibility criteria
Python
Intro to Deep Learning with PyTorch online training assumes that you are comfortable working with Python and its data processing libraries, namely NumPy and Matplotlib. Also, a basic understanding of calculus and linear algebra would be beneficial. However, it is not compulsory.
What you will learn
Knowledge of deep learning
Intro to Deep Learning with PyTorch syllabus will make you proficient in:
- Deep learning using PyTorch
- Style transfer
- How to recurrent neural networks
- Natural language classification
- Deploying deep learning models using PyTorch
Admission details
- Intro to Deep Learning with PyTorch course admission begins on the web course link.
- Click on the ‘Start Free Course’ and sign in with your Udacity account. Create one if you don’t have it on the sign-up sheet. Once you have signed in, you can begin the training.
Filling the form
Intro to Deep Learning with PyTorch training course needs a profile account with Udacity to secure your admission. For this, you need to provide your first and last name and your email ID. Then, create a password as per the website requirements. Your application will be completed and accepted.
The syllabus
Lesson 1: Welcome to the course!
Lesson 2:Introduction to Neural Networks
Lesson 3: Talking PyTorch with Soumith Chintala
- Hear from Soumith Chintala, the creator of PyTorch, about the past, present, and future of the PyTorch framework.
Lesson 4: Introduction to PyTorch
- Learn how to use PyTorch to build and train deep neural networks. By the end of this lesson, you will build a network that can classify images of dogs and cats with state-of-the-art performance.
Lesson 5: Convolutional Neural Networks
- Learn how to use convolutional neural networks to build state-of-the-art computer vision models.
Lesson 6:Style Transfer
- Use a deep neural network to transfer the artistic style of one image onto another image.
Lesson 7: Recurrent Neural Networks
- Learn how to use recurrent neural networks to learn from sequential data such as text. Build a network that can generate realistic text one letter at a time.
Lesson 8:Sentiment Prediction RNNs
- Here you'll build a recurrent neural network that can accurately predict the sentiment of movie reviews.
Lesson 9 :Deploying PyTorch Models
- In this lesson, we'll walk through a tutorial showing how to deploy PyTorch models with Torch Script.
Scholarship Details
Udacity offers a number of scholarships for their courses. You can check out the Intro to Deep Learning with PyTorch training course page to find out more details.
How it helps
Intro to Deep Learning with PyTorch training is a free course where you can learn from industry experts. It has interactive quizzes to help you evaluate your progress. AI is a fast-growing technology with applications in almost every industry. With the knowledge you gain, your chances of gaining favourable employment will increase further.
Instructors
Mr Luis Serrano
Instructor
Freelancer
Ph.D
Ms Alexis Cook
Instructor
Freelancer
Other Masters
Ms Cezanne Camacho
Instructor
Freelancer
M.S, Other Masters
Mr Mat Leonard
Instructor
Freelancer
Ph.D
FAQs
Do I need to pay any fee to join the Intro to Deep Learning with PyTorch programme?
No. There is no programme fee. Intro to Deep Learning with PyTorch is a free training programme.
Who are the Intro to Deep Learning with PyTorch programme educators?
The educators for the Intro to Deep Learning with PyTorch programme are Matt Leonard, Soumith Chintala, Luis Serrano, Cezanne Camacho, and Alexis Cook.
Can I enrol on the Intro to Deep Learning with PyTorch right away?
Yes. Enrolment for the Intro to Deep Learning with PyTorch is open right now. Visit the course page, sign in with your account and click on ‘Start Free Course’ to begin.
Do I need any prior experience or training to join the Intro to Deep Learning with PyTorch course?
Yes. You need to be comfortable working with Python and its libraries Matplotlib and NumPy. A basic understanding of calculus and linear algebra will also be great, but it is not compulsory.
