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Vertex AI Tabular Data

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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 learn how to build a binary classification model from tabular data using Vertex AI.

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What's inside

Syllabus

Vertex AI Tabular Data: Qwik Start

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches practical skills through a hands-on lab environment

Builds a foundation in machine learning through a practical use case

Designed for beginners with no prior knowledge of machine learning

Taught by experienced Google Cloud instructors

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Save Vertex AI Tabular Data: Qwik Start 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 Vertex AI Tabular Data: Qwik Start with these activities:

Refresh Your Understanding of Machine Learning Basics

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Strengthen your foundation by reviewing fundamental machine learning concepts.

Browse courses on Machine Learning

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Review introductory machine learning materials (e.g., books, online courses, videos).

Practice Data Preprocessing for Binary Classification Models

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Sharpen your data preprocessing skills, which are crucial for effective model building.

Browse courses on Data Preprocessing

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Review data preprocessing techniques.
Practice data cleaning, feature scaling, and dimensionality reduction on sample datasets.

Practice Binary Classification Model Building Exercises

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Complete exercises to reinforce your understanding of binary classification model building and put your knowledge into practice.

Browse courses on Vertex AI

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Review the course materials on binary classification model building.
Solve practice problems involving binary classification model building.
Create your own binary classification model using Vertex AI.

Five other activities

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Follow Tutorials on Advanced Binary Classification Model Techniques

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Expand your knowledge by exploring advanced techniques through guided tutorials.

Browse courses on Vertex AI

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Find tutorials on advanced binary classification model building techniques.
Follow the tutorials and complete the exercises.

Collaborate with Peers on a Binary Classification Model Project

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Engage with peers to exchange ideas, troubleshoot problems, and enrich your understanding.

Browse courses on Vertex AI

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Find a study buddy or form a small group.
Discuss course concepts, work on practice problems together, and share resources.

Attend a Workshop on Advanced Binary Classification Model Techniques

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Gain in-depth knowledge and practical experience through a dedicated workshop.

Browse courses on Vertex AI

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Locate and register for a relevant workshop.
Attend the workshop and actively participate in the activities.

Build a Binary Classification Model for a Real-World Problem

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Apply your skills to a real-world problem by building and deploying a binary classification model.

Browse courses on Vertex AI

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Identify a suitable problem and dataset.
Prepare and clean the data.
Build and test your binary classification model.
Deploy your model and evaluate its performance.

Create a Presentation or Blog Post on Binary Classification Models

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Solidify your knowledge by teaching others about binary classification models.

Browse courses on Vertex AI

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Choose a specific topic related to binary classification models.
Research and gather information.
Create a presentation or blog post that explains the topic in a clear and engaging way.

Career center

Learners who complete Vertex AI Tabular Data: Qwik Start will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models. This course may help build a foundation for this role by providing an introduction to machine learning concepts and algorithms. The course will also help you develop skills in data preparation, model training, and model evaluation, which are essential for success in machine learning engineering.

See salaries and explore the career path for Machine Learning Engineer

Statistician

Statisticians use data to collect, analyze, and interpret data. This course may be useful for aspiring Statisticians by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which are essential for success in statistics.

See salaries and explore the career path for Statistician

Data Analyst

Data Analysts collect, clean, and analyze data to help businesses make better decisions. This course may help build a foundation for this role by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which are essential for success in data analysis.

See salaries and explore the career path for Data Analyst

Research Analyst

Research Analysts conduct research and analyze data to provide insights to businesses and organizations. This course may be useful for aspiring Research Analysts by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which are essential for success in research analysis.

See salaries and explore the career path for Research Analyst

Business Analyst

Business Analysts use data to help businesses understand their customers and make better decisions. This course may be useful for aspiring Business Analysts by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which are essential for success in business analysis.

See salaries and explore the career path for Business Analyst

Operations Research Analyst

Operations Research Analysts use data to solve complex problems and improve business operations. This course may be useful for aspiring Operations Research Analysts by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which are essential for success in operations research.

See salaries and explore the career path for Operations Research Analyst

Actuary

Actuaries use data to assess risk and uncertainty. This course may be useful for aspiring Actuaries by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which are essential for success in actuarial science.

See salaries and explore the career path for Actuary

Data Scientist

Data Scientists use data to solve business problems and make predictions. This course may be useful for aspiring Data Scientists by providing an introduction to the fundamentals of data science, including data analysis, machine learning, and statistical modeling. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which are essential for success in data science.

See salaries and explore the career path for Data Scientist

Financial Analyst

Financial Analysts use data to analyze financial performance and make investment recommendations. This course may be useful for aspiring Financial Analysts by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which are essential for success in financial analysis.

See salaries and explore the career path for Financial Analyst

Marketing Analyst

Marketing Analysts use data to understand customer behavior and develop marketing campaigns. This course may be useful for aspiring Marketing Analysts by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which are essential for success in marketing analysis.

See salaries and explore the career path for Marketing Analyst

Consultant

Consultants use data to help businesses solve problems and make better decisions. This course may be useful for aspiring Consultants by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which are essential for success in consulting.

See salaries and explore the career path for Consultant

Data Engineer

Data Engineers build and maintain data pipelines and infrastructure. This course may be useful for aspiring Data Engineers by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which are essential for success in data engineering.

See salaries and explore the career path for Data Engineer

Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. This course may be useful for aspiring Quantitative Analysts by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which are essential for success in quantitative analysis.

See salaries and explore the career path for Quantitative Analyst

Software Engineer

Software Engineers design, develop, and maintain software applications. This course may be useful for aspiring Software Engineers by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which can be helpful for building data-driven applications.

See salaries and explore the career path for Software Engineer

Product Manager

Product Managers are responsible for the development and launch of new products. This course may be useful for aspiring Product Managers by providing an introduction to data analysis and machine learning techniques. The course will also help you develop skills in data cleaning, feature engineering, and model evaluation, which can be helpful for understanding customer needs and making better product decisions.

See salaries and explore the career path for Product Manager

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 Vertex AI Tabular Data: Qwik Start.

Hands-On Machine Learning with Scikit-Learn, Keras,...

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Offers practical guidance on implementing machine learning models using popular libraries such as Scikit-Learn, Keras, and TensorFlow, which are also used in Vertex AI Tabular Data.

Vertex AI Tabular Data

Qwik Start

Three deals to help you save

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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