Smart Analytics, Machine Learning, and AI on GCP
- 4.6
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Course Summary
This course provides an introduction to smart analytics, machine learning, and AI using Google Cloud Platform. It covers a range of topics such as data analysis, feature engineering, model training, and evaluation.Key Learning Points
- Learn how to use Google Cloud Platform for smart analytics, machine learning, and AI
- Gain hands-on experience with real-world datasets and tools
- Develop skills in data analysis, feature engineering, model training, and evaluation
Job Positions & Salaries of people who have taken this course might have
- USA: $113,309
- India: ₹1,194,536
- Spain: €33,000
- USA: $113,309
- India: ₹1,194,536
- Spain: €33,000
- USA: $117,276
- India: ₹1,662,717
- Spain: €37,000
- USA: $113,309
- India: ₹1,194,536
- Spain: €33,000
- USA: $117,276
- India: ₹1,662,717
- Spain: €37,000
- USA: $120,000
- India: ₹1,800,000
- Spain: €40,000
Related Topics for further study
Learning Outcomes
- Develop skills in using Google Cloud Platform for smart analytics, machine learning, and AI
- Gain hands-on experience with real-world datasets and tools
- Learn how to analyze data, engineer features, and train and evaluate models
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of programming
- Familiarity with statistics and linear algebra
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
- Video lectures
- Hands-on projects
Similar Courses
- Applied Data Science with Python
- Data Mining
- Machine Learning
Related Education Paths
- Google Cloud Certified - Professional Data Engineer
- Google Cloud Certified - Professional Machine Learning Engineer
- Google Cloud Certified - Professional Cloud Architect
Notable People in This Field
- Andrew Ng
- Fei-Fei Li
Related Books
Description
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.
Outline
- Introduction
- Course Introduction
- Getting Started with Google Cloud and Qwiklabs
- Introduction to Analytics and AI
- What is ML?
- Machine Learning and AI
- ML options on Google Cloud Platform
- Game: Reviewing key ML concepts
- Introduction to Analytics and AI
- Prebuilt ML model APIs for Unstructured Data
- 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
- Big Data Analytics with Cloud AI Platform Notebooks
- 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
- Custom Model building with SQL in BigQuery ML
- 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
- Custom Model Building with Cloud AutoML
- Why Auto ML?
- Auto ML Vision
- Auto ML NLP
- Auto ML Tables
- Custom Model Building with Cloud AutoML
- Summary
- Course Summary
Summary of User Reviews
Discover the power of smart analytics, machine learning, and AI with GCP. This course has received great reviews for its comprehensive coverage and practical exercises. Many users found the course to be a perfect starting point for building their skills in this field.Key Aspect Users Liked About This Course
The course provides practical exercises to reinforce learningPros from User Reviews
- Comprehensive coverage of smart analytics, machine learning, and AI
- Hands-on exercises to reinforce learning
- Great starting point for beginners
- Excellent instructors with real-world experience
Cons from User Reviews
- Some users found the course material to be too basic
- Some users reported technical difficulties with the platform
- Lack of interaction with instructors
- Some users found the pace of the course to be too slow
Google Cloud Training
4.6 Raiting
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