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Overview
What is machine learning, and what kinds of problems can it solve? How can you build, train, and deploy machine learning models at scale without writing a single line of code? When should you use automated machine learning or custom training?
This Machine Learning on Google Cloud Specialization offered by Coursera in partnership with Google Cloud teaches how to build Vertex AI AutoML models without writing code; create BigQuery ML models using basic SQL; develop Vertex AI custom training jobs deployed with containers, requiring minimal Docker knowledge; and use Feature Store for data management and governance. The specialization also covers feature engineering for model improvement, selection of appropriate data preprocessing techniques, and the use of Vertex Vizier for hyperparameter tuning to achieve accurate and well‑generalized models.
In addition, it provides theoretical foundations for solving specific machine learning problems, demonstrates how to write distributed and scalable machine learning models using TensorFlow, and applies best practices for implementing machine learning solutions on Google Cloud.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 include:
AI and Machine Learning on Google Cloud
- Data-to-AI Technologies
- Generative AI Capabilities
- Vertex AI
- Build, Train and Deploy ML Models with Keras on Google Cloud
- Feature Engineering
- Machine Learning in the Enterprise
Key information
Duration
- Part-time
- 1 months
- 10 hrs/week
Start dates & application deadlines
You can apply for and start this programme anytime.
Language
English
Delivered
Online
- Self-paced
Campus Location
- Mountain View, United States
Disciplines
Computer Sciences Web Technologies & Cloud Computing Machine Learning View 203 other Short Courses in Machine Learning in United StatesWhat students do after studying
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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 Level
- It would be helpful to review topics covered in the Google ML Crash Course, and for Python programming review the Google Python Class.
- This specialization is aimed at learners and professionals who want to develop practical skills in building, training, and deploying machine learning models on Google Cloud, including both automated and custom approaches for real‑world applications.
Tuition Fees
Additional Details
Course is free for the first 7 days. After 7 days, the course can be accessed with the Coursera Plus Subscription
Funding
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