Overview
This Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization offered by Coursera in partnership with Google Cloud picks up where “Machine Learning on GCP” left off and teaches you how to build scalable, accurate, and production-ready models for structured data, image data, time-series, and natural language text. It ends with a course on building recommendation systems. Topics introduced in earlier courses are referenced in later courses, so it is recommended that you take the courses in exactly this order.
Applied Learning Project
This specialization incorporates hands-on labs using our Qwiklabs platform.
These hands on components will let you apply the skills you learn in the video lectures. Projects will incorporate topics such as Google Cloud Platform products, which are used and configured within Qwiklabs. You can expect to gain practical hands-on experience with the concepts explained throughout the modules.
Programme Structure
Courses included:
- Production Machine Learning Systems
- Computer Vision with Google Cloud
- Natural Language Processing on Google Cloud
- Recommendation Systems on Google Cloud
Key information
Duration
- Part-time
- 1 months
- 10 hrs/week
Start dates & application deadlines
Language
Delivered
- Self-paced
Campus Location
- Mountain View, United States
Disciplines
Machine Learning View 213 other Short Courses in Machine Learning 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
- Advanced level
- Designed for those already in the industry
Tuition Fees
-
International Applies to you
Applies to youNon-residentsFree - Out-of-StateFree
Additional Details
- This short course is included with Coursera Plus subscription
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.