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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console.
In this lab you will use Vertex AI to train and serve a model with tabular data. You will build a fraud detection model to determine whether a particular credit card transaction should be classified as fraudulent.
Register for this course and see more details by visiting:
OpenCourser.com/course/rovqxa/building
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines industry-standard tools and practices for fraud detection
Explores fraud detection models using tabular data, which is commonly used in financial institutions
Provides hands-on experience in building and deploying machine learning models using Vertex AI, a popular platform for AI development
Taught by Google Cloud Training, a reputable organization in the field of cloud computing
Suitable for those with basic knowledge of machine learning and data analysis
Requires prior experience in programming and data science concepts
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Save Building a Fraud Detection Model with Vertex AI AutoML to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Building a Fraud Detection Model with Vertex AI AutoML with these
activities:
Review tabular data fundamentals
Show steps
Reviewing tabular data fundamentals will help you better understand the data you will be working with in this course.
Browse courses on
Tabular Data
Show steps
-
Review the basics of tabular data, including data types, data structures, and data manipulation.
-
Practice working with tabular data in a spreadsheet or data analysis software.
Practice data cleaning and preparation for machine learning
Show steps
Practicing data cleaning and preparation for machine learning will help you improve your ability to work with real-world data.
Show steps
-
Find a dataset that you want to use for machine learning.
-
Clean the data by removing errors, inconsistencies, and outliers.
-
Prepare the data for modeling by converting it into a format that is compatible with your machine learning algorithm.
Follow a tutorial on Vertex AI
Show steps
Following a tutorial on Vertex AI will help you get started with the platform and learn how to use its features.
Show steps
-
Find a tutorial on Vertex AI that is relevant to your interests.
-
Follow the steps in the tutorial carefully.
-
Experiment with the Vertex AI features that you learn about in the tutorial.
Two other activities
Expand to see all activities and additional details
Show all five activities
Discuss fraud detection techniques with other students
Show steps
Discussing fraud detection techniques with other students will help you learn from their experiences and insights.
Show steps
-
Find a study group or online forum where you can connect with other students who are interested in fraud detection.
-
Start a discussion about fraud detection techniques.
-
Share your own experiences and insights, and learn from others.
Build a fraud detection model using Vertex AI
Show steps
Building a fraud detection model using Vertex AI will help you apply the skills you learn in this course to a real-world problem.
Show steps
-
Gather data for your fraud detection model.
-
Prepare the data for modeling.
-
Train a fraud detection model using Vertex AI.
-
Evaluate the performance of your fraud detection model.
Review tabular data fundamentals
Show steps
Reviewing tabular data fundamentals will help you better understand the data you will be working with in this course.
Browse courses on
Tabular Data
Show steps
Show steps
Show steps
- Review the basics of tabular data, including data types, data structures, and data manipulation.
- Practice working with tabular data in a spreadsheet or data analysis software.
Practice data cleaning and preparation for machine learning
Show steps
Practicing data cleaning and preparation for machine learning will help you improve your ability to work with real-world data.
Show steps
Show steps
Show steps
- Find a dataset that you want to use for machine learning.
- Clean the data by removing errors, inconsistencies, and outliers.
- Prepare the data for modeling by converting it into a format that is compatible with your machine learning algorithm.
Follow a tutorial on Vertex AI
Show steps
Following a tutorial on Vertex AI will help you get started with the platform and learn how to use its features.
Show steps
Show steps
Show steps
- Find a tutorial on Vertex AI that is relevant to your interests.
- Follow the steps in the tutorial carefully.
- Experiment with the Vertex AI features that you learn about in the tutorial.
Two other activities
Expand to see all activities and additional details
Show all five activities
Discuss fraud detection techniques with other students
Show steps
Discussing fraud detection techniques with other students will help you learn from their experiences and insights.
Show steps
Show steps
Show steps
- Find a study group or online forum where you can connect with other students who are interested in fraud detection.
- Start a discussion about fraud detection techniques.
- Share your own experiences and insights, and learn from others.
Build a fraud detection model using Vertex AI
Show steps
Building a fraud detection model using Vertex AI will help you apply the skills you learn in this course to a real-world problem.
Show steps
Show steps
Show steps
- Gather data for your fraud detection model.
- Prepare the data for modeling.
- Train a fraud detection model using Vertex AI.
- Evaluate the performance of your fraud detection model.
Career center
Learners who complete Building a Fraud Detection Model with Vertex AI AutoML will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts use their knowledge of data to solve problems and make informed decisions. Through the use of statistical modeling, machine learning, and data visualization, a Data Analyst can help a company prevent fraud, conduct market research, or even target certain demographics for ad campaigns. The Building a Fraud Detection Model with Vertex AI AutoML course can help someone who aspires to be a Data Analyst by providing them with the skills necessary to process and collect data, wrangle and clean it, and then use it to train and serve their own model.
Data Scientist
Data Scientist
Data Scientists use their expertise in mathematics, statistics, and computer science to solve complex problems through data. They often collaborate with other members of an organization to find solutions to business problems. The Building a Fraud Detection Model with Vertex AI AutoML course can be a great stepping stone for those looking to become a Data Scientist. By taking this course, you will gain experience in using machine learning to solve real-world problems.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for developing, deploying, and maintaining machine learning models. They work with data scientists to identify problems that can be solved with machine learning and then design and implement solutions. The Building a Fraud Detection Model with Vertex AI AutoML course can provide someone interested in becoming a Machine Learning Engineer with hands-on experience in using machine learning to solve a real-world problem.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use their knowledge of mathematics, statistics, and computer science to analyze financial data and make investment decisions. They play a vital role in the financial industry and are responsible for developing and implementing trading strategies. The Building a Fraud Detection Model with Vertex AI AutoML course can help someone who aspires to be a Quantitative Analyst with the skills necessary to analyze financial data and make informed investment decisions.
Risk Analyst
Risk Analyst
Risk Analysts assess and quantify the risks that a company faces. They use their knowledge of finance, statistics, and machine learning to identify and mitigate risks. The Building a Fraud Detection Model with Vertex AI AutoML course can help someone who aspires to be a Risk Analyst by providing them with the skills necessary to assess and quantify risk.
Fraud Investigator
Fraud Investigator
Fraud Investigators investigate and prevent fraud. They work with law enforcement and other organizations to track down and prosecute fraudsters. The Building a Fraud Detection Model with Vertex AI AutoML course can help someone who aspires to be a Fraud Investigator by providing them with the skills necessary to identify and investigate fraud.
Business Analyst
Business Analyst
Business Analysts help organizations improve their performance by analyzing data and identifying opportunities for improvement. They work with stakeholders to define and solve problems and may also develop and implement solutions. The Building a Fraud Detection Model with Vertex AI AutoML course can help someone who aspires to be a Business Analyst by providing them with the skills necessary to analyze data and identify opportunities for improvement.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain the infrastructure that is used to store and process data. They work with data scientists and other IT professionals to ensure that data is available and accessible to those who need it. The Building a Fraud Detection Model with Vertex AI AutoML course can help someone who aspires to be a Data Engineer by providing them with the skills necessary to design and build data infrastructure.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with other members of a development team to create software that meets the needs of users. The Building a Fraud Detection Model with Vertex AI AutoML course may be useful for someone who aspires to be a Software Engineer by providing them with some experience in software development.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. They work in a variety of fields, including finance, healthcare, and marketing. The Building a Fraud Detection Model with Vertex AI AutoML course may be useful for someone who aspires to be a Statistician by providing them with some experience in data analysis.
Actuary
Actuary
Actuaries use their knowledge of mathematics and statistics to assess risk and uncertainty. They work in a variety of fields, including insurance, finance, and consulting. The Building a Fraud Detection Model with Vertex AI AutoML course may be useful for someone who aspires to be an Actuary by providing them with some experience in risk assessment.
Financial Analyst
Financial Analyst
Financial Analysts use their knowledge of finance and economics to make investment recommendations. They work with clients to develop and manage investment portfolios. The Building a Fraud Detection Model with Vertex AI AutoML course may be useful for someone who aspires to be a Financial Analyst by providing them with some experience in financial analysis.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their knowledge of mathematics and statistics to solve problems in a variety of fields, including logistics, manufacturing, and healthcare. The Building a Fraud Detection Model with Vertex AI AutoML course may be useful for someone who aspires to be an Operations Research Analyst by providing them with some experience in problem-solving.
Quantitative Researcher
Quantitative Researcher
Quantitative Researchers use their knowledge of mathematics, statistics, and computer science to develop and implement trading strategies. They work with portfolio managers to identify and execute trades. The Building a Fraud Detection Model with Vertex AI AutoML course may be useful for someone who aspires to be a Quantitative Researcher by providing them with some experience in developing and implementing trading strategies.
Data Management Analyst
Data Management Analyst
Data Management Analysts work with data to ensure that it is accurate, consistent, and accessible. They develop and implement data management policies and procedures. The Building a Fraud Detection Model with Vertex AI AutoML course may be useful for someone who aspires to be a Data Management Analyst by providing them with some experience in data management.
For more career information including salaries, visit:
OpenCourser.com/course/rovqxa/building
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Building a Fraud Detection Model with Vertex AI AutoML.
Comprehensive guide to pattern recognition and machine learning, covering a wide range of topics, from supervised learning to unsupervised learning. It good resource for students and practitioners who want to learn more about pattern recognition and machine learning.
Comprehensive guide to statistical methods for machine learning, covering a wide range of topics, from probability to Bayesian inference. It good resource for students and practitioners who want to learn more about statistical methods for machine learning.
Classic textbook on statistical learning, covering a wide range of topics, including supervised learning, unsupervised learning, and model selection. It valuable resource for students and practitioners who want to learn more about statistical learning.
Practical guide to machine learning using R, covering a wide range of topics, from data preprocessing to model evaluation. It good hands-on resource for students and practitioners who want to learn more about machine learning.
Save
Comprehensive guide to data mining, covering a wide range of topics, from data preprocessing to model evaluation. It good resource for students and practitioners who want to learn more about data mining.
Hands-on introduction to machine learning using R. It covers a wide range of topics, from data preprocessing to model evaluation. It useful reference for students and practitioners who want to learn more about machine learning.
Save
Comprehensive guide to machine learning, covering a wide range of topics, from supervised learning to unsupervised learning. It good resource for students and practitioners who want to learn more about machine learning.
Comprehensive introduction to data mining for business intelligence, covering the latest techniques and applications. It is written in R but can be used by students and practitioners with other programming backgrounds.
Practical guide to machine learning for hackers, covering a wide range of topics, from data preprocessing to model evaluation. It good hands-on resource for students and practitioners who want to learn more about machine learning.
Practical guide to machine learning, covering a wide range of topics, from data preprocessing to model evaluation. It good hands-on resource for students and practitioners who want to learn more about machine learning.
Gentle introduction to machine learning using Python, covering the basics of supervised learning, unsupervised learning, and model evaluation. It good starting point for students and practitioners who are new to machine learning.
Gentle introduction to machine learning, covering the basics of supervised learning, unsupervised learning, and model evaluation. It good starting point for students and practitioners who are new to machine learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/rovqxa/building
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Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Good to know
Examines industry-standard tools and practices for fraud detection
Explores fraud detection models using tabular data, which is commonly used in financial institutions
Provides hands-on experience in building and deploying machine learning models using Vertex AI, a popular platform for AI development
Taught by Google Cloud Training, a reputable organization in the field of cloud computing
Suitable for those with basic knowledge of machine learning and data analysis
Requires prior experience in programming and data science concepts
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