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Overview
Key Features
This Smart Analytics, Machine Learning, and AI on Google Cloud course offered by Coursera in partnership with Google Cloud covers ways machine learning can be included in data pipelines on Google Cloud.
For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.
What you'll learn
- Differentiate between ML, AI and deep learning.
- Discuss the use of ML API’s on unstructured data.
- Execute BigQuery commands from notebooks.
- Create ML models by using SQL syntax in BigQuery and without coding using Vertex AI AutoML.
Programme Structure
Courses include:
From ad-hoc data analysis to data-driven decisions
- ML APIs for enriching data
- Using the Natural Language API to Classify Unstructured Text
- BigQuery magic and ties to Pandas
- Ways to do ML on Google Cloud
- BigQuery ML for Quick Model Building
- Predict Bike Trip Duration with a Regression Model in BigQuery ML
Key information
Duration
- Part-time
- 1 days
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
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
- This course is aimed at learners and aspiring data professionals who want to develop skills in applying machine learning and AI within data pipelines on Google Cloud, including using tools like AutoML, BigQuery ML, and Vertex AI.
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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