Smart Analytics, Machine Learning, and AI on GCP
4.0 /5- Offered byCoursera
Smart Analytics, Machine Learning, and AI on GCP at Coursera Overview
Duration | 8 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Smart Analytics, Machine Learning, and AI on GCP at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Intermediate Level
- Approx. 8 hours to complete
- English Subtitles: French, Portuguese (European), Russian, English, Spanish
Smart Analytics, Machine Learning, and AI on GCP at Coursera Course details
- Incorporating machine learning into data pipelines increases the ability of businesses to extract insights from their data. This course covers several ways machine learning can be included in data pipelines on Google Cloud Platform depending on the level of customization required. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces AI Platform Notebooks and BigQuery Machine Learning. Also, this course covers how to productionalize machine learning solutions using Kubeflow. Learners will get hands-on experience building machine learning models on Google Cloud Platform using QwikLabs.
- This course is part of multiple programs
- This course can be applied to multiple Specializations or Professional Certificates programs. Completing this course will count towards your learning in any of the following programs:
- Data Engineering, Big Data, and Machine Learning on GCP Specialization
- Data Engineering with Google Cloud Professional Certificate
Smart Analytics, Machine Learning, and AI on GCP at Coursera Curriculum
Introduction
Course Introduction
Getting Started with Google Cloud and Qwiklabs
What is ML?
Machine Learning and AI
ML options on Google Cloud Platform
Game: Reviewing key ML concepts
Introduction to Analytics and AI
Unstructured Data is Hard
ML APIs for Enriching Data
Lab Intro: Using the Natural Language API to Classify Unstructured Text
Prebuilt ML model APIs for Unstructured Data
What?s a Notebook
BigQuery Magic and Ties to Pandas
Lab Intro: BigQuery in Jupyter Labs on AI Platform
Big Data Analytics with Cloud AI Platform Notebooks
Productionizing Custom ML Models
Phases of ML Projects
Ways to do custom ML on GCP
Kubeflow
AI Hub
Lab Intro: Running ML Pipelines on Kubeflow
Summary
Productionizing Custom ML Models
BigQuery ML for Quick Model Building
Classification, Regregression, and Recommender Models
Unsupervised ML with Clustering Models
Lab Intro: Predict Bike Trip Duration with a Regression Model in BQML
Lab Intro: Movie Recommendations in BigQuery ML
Summary
Custom Model building with SQL in BigQuery ML
Why Auto ML?
Auto ML Vision
Auto ML NLP
Auto ML Tables
Custom Model Building with Cloud AutoML
Course Summary
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