- Level Foundation
- Duration 14 hours
- Course by Google Cloud
-
Offered by
About
The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.Modules
Introduction to the Course
1
Videos
- Course introduction
Get to Know Your Data: Module Introduction
1
Videos
- Introduction
Improve Data through Exploratory Data Analysis
1
Assignment
- Get to know your data: Improve data through Exploratory Data Analysis
2
External Tool
- Lab: Improving data quality
- Lab: Exploratory Data Analysis using Python and BigQuery
8
Videos
- Improve Data Quality
- Getting Started with Google Cloud and Qwiklabs
- Lab intro: Improve the quality of your data
- Lab Demo: Improve the quality of your data
- What is exploratory data analysis
- How is EDA used in machine learning
- Data analysis and visualization
- Lab intro: Explore the data using Python and BigQuery
1
Readings
- Resources: Get to know your data: Improve data through Exploratory Data Analysis
Machine Learning in Practice: Module Introduction
1
Videos
- Introduction
Supervised Learning
1
Assignment
- Machine Learning in Practice
1
External Tool
- Lab: Introduction to linear regression
5
Videos
- Supervised learning
- Linear regression
- Lab intro: Introduction to linear regression
- Lab Demo: Intro to Linear Regression
- Logistic regression
1
Readings
- Resources: Machine Learning in Practice
Training AutoML Models Using Vertex AI: Module Introduction
1
Videos
- Introduction
Train AutoML models using Vertex AI
1
Assignment
- Training AutoML Models Using Vertex AI
4
Videos
- Machine learning vs. deep learning
- What is automated machine learning?
- AutoML regression model
- Evaluate AutoML models
1
Readings
- Resources: Training AutoML Models Using Vertex AI
BigQuery Machine Learning: Module Introduction
1
Videos
- Introduction
Develop ML models where your data lives
1
Assignment
- BigQuery Machine Learning: Develop ML Models Where Your Data Lives
1
External Tool
- Lab: Using BigQuery ML to predict penguin weight
6
Videos
- Training an ML model using BigQuery ML
- BigQuery Machine Learning supported models
- Lab intro: Using BigQuery ML to predict penguin weight (BigQuery ML & Explainable AI)
- Lab Demo: Using BigQuery ML to predict penguin weight (BigQuery ML & Explainable AI)
- BigQuery ML hyperparameter tuning
- How to build and deploy a recommendation system with BigQuery ML
1
Readings
- Resources: BigQuery Machine Learning: Develop ML Models Where Your Data Lives
Optimization: Module Introduction
1
Videos
- Introduction
Defining ML Models
3
Videos
- Defining ML models
- Introducing the course dataset
- Introduction to loss functions
Gradient Descent
3
Videos
- Gradient descent
- Troubleshooting loss curves
- ML model pitfalls
TensorFlow Playground
3
Videos
- Lecture lab: Introducing the TensorFlow Playground
- Lecture lab: TensorFlow Playground - Advanced
- Lecture lab: Practicing with neural networks
Performance Metrics
1
Assignment
- Optimization
2
Videos
- Performance metrics
- Confusion matrix
1
Readings
- Resources: Optimization
Generalization and Sampling: Module Introduction
1
Videos
- Introduction
Generalization
2
Videos
- Generalization and ML models
- When to stop model training
Sampling
1
Assignment
- Generalization and Sampling
2
Videos
- Creating repeatable samples in BigQuery
- Demo: Splitting datasets in BigQuery
1
Readings
- Resources: Generalization and Sampling
Course Summary
4
Readings
- Summary
- Resource: All quiz questions
- Resource: All readings
- Resource: All slides
Auto Summary
"Launching into Machine Learning" is an engaging and foundational course designed for those eager to delve into the world of Data Science and AI. Offered by Coursera, the course starts with essential discussions on improving data quality and performing exploratory data analysis. Learners will explore Vertex AI AutoML, gaining the ability to build, train, and deploy machine learning models effortlessly without any coding. The course also highlights the advantages of using Big Query ML. Beyond model building, participants will learn optimization techniques and how generalization and sampling can aid in assessing model quality for custom training. This 840-minute course is ideal for beginners and is available through a Starter subscription, making it accessible to a wide audience interested in machine learning.

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