By the end of this course, learners will differentiate core AI concepts, construct deep neural networks, apply image and text models, develop attention-based NLP systems, and design recommender solutions.
Deep Learning: Build & Optimize Neural Networks
Saving $160 on access to 10,000+ programs is a holiday treat. Save now.
Gain insight into a topic and learn the fundamentals.
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Build and optimize deep neural networks using PyTorch.
Apply AI models to vision, NLP, and recommendation tasks.
Implement attention and transformer architectures effectively.
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
November 2025
Assessments
22 assignments
Taught in English
See how employees at top companies are mastering in-demand skills
There are 6 modules in this course
This module introduces learners to the core principles of machine learning and deep learning, exploring their methods, applications, and the evolution from perceptrons to deep neural networks.
What's included
12 videos3 assignments
This module provides hands-on exposure to essential coding platforms, tools, and frameworks like Jupyter, Google Colab, and PyTorch, while building foundational skills with tensors, gradients, and basic networks.
What's included
15 videos4 assignments
This module explores image classification through practical case studies, guiding learners to preprocess, transform, and visualize datasets, then build, train, and test deep neural networks on benchmarks like MNIST and CIFAR-10.
What's included
18 videos4 assignments
This module introduces natural language processing (NLP) tasks, including text classification with CNNs and text generation with transformers, focusing on preparing textual data, building models, and evaluating results.
What's included
15 videos4 assignments
This module dives deeper into NLP using attention-based architectures, covering sequence-to-sequence models for text translation, encoder-decoder frameworks, and best practices for training and evaluation.
What's included
14 videos4 assignments
This module extends deep learning applications to structured tabular data and recommender systems, demonstrating predictive modeling and approaches like collaborative and content-based filtering.
What's included
7 videos3 assignments
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
More questions
Financial aid available,