Overview
Key Features
- By the end, you will be able to build a convolutional neural network, including recent variations such as residual networks; apply convolutional networks to visual detection and recognition tasks; and use neural style transfer to generate art and apply these algorithms to a variety of image, video, and other 2D or 3D data.
- The Convolutional Neural Networks course offered by Coursera in partnership with Deeplearning is our foundational programme that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI.
Programme Structure
Courses include:
- Convolutional Neural Networks
- Deep convolutional models: case studies
- Object detection
- Special applications: Face recognition & Neural style transfer
Key information
Duration
- Part-time
- 1 months
- 9 hrs/week
Start dates & application deadlines
Language
Delivered
- Self-paced
Campus Location
- Mountain View, United States
Disciplines
Computer Sciences View 466 other Short Courses in Computer Sciences in United StatesWhat students do after studying
Academic requirements
We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.
English requirements
We are not aware of any English requirements for this programme.
Other requirements
General requirements
Intermediate Python skills:
- basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
Tuition Fees
-
International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
Additional Details
- Audit: free access to course materials except graded items
- Certificate: a trusted way to showcase your skills
- A year of unlimited access with Coursera Plus $399
Funding
Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project.