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Google Cloud
This course is an introduction to building forecasting solutions with Google Cloud.
Read more
This course is an introduction to building forecasting solutions with Google Cloud.
Read more
This course is an introduction to building forecasting solutions with Google Cloud.
This course is an introduction to building forecasting solutions with Google Cloud. You start with sequence models and time series foundations. You then walk through an end-to-end workflow: from data preparation to model development and deployment with Vertex AI. Finally, you learn the lessons and tips from a retail use case and apply the knowledge by building your own forecasting models.
Register for this course and see more details by visiting:
OpenCourser.com/course/a3e8gq/introduction
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What's inside
Syllabus
Introduction
Time series and forecasting fundamentals
Forecasting options on Google Cloud
Data preparation
Read more
Syllabus
Introduction
Time series and forecasting fundamentals
Forecasting options on Google Cloud
Data preparation
Read more
Model training
Model evaluation
Model deployment
Model monitoring
Vertex forecasting in retail
Summary
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Intended for learners and professionals who want to build and evaluate forecasting models on Google Cloud
Taught by Google Cloud professionals who are authorities in the field of forecasting
Covers how to use Google Cloud's Vertex AI for predictive modeling
Provides hands-on experience with real-world retail datasets
May require additional background knowledge in statistics, machine learning, and data analysis
May not be suitable for complete beginners in forecasting or Google Cloud
Save this course
Save Introduction to Vertex Forecasting and Time Series in Practice 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 Introduction to Vertex Forecasting and Time Series in Practice with these
activities:
Compile course resources from syllabi, lectures, recordings, notes
Show steps
Gather and organize all relevant course materials to foster effective study habits
Browse courses on
C
Show steps
-
Review syllabi and lecture notes
-
Download and label recordings
-
Organize materials into folders
Review the textbook 'Time Series Analysis and Forecasting: Theory and Methods'
Show steps
Supplemental reading can help solidify the complex concepts of the course
View
Time Series Forecasting
on Amazon
Show steps
-
Focus on understanding time series notation and methods
-
Critically evaluate models and their applications
-
Connect theoretical concepts to practical forecasting scenarios
Practice forecasting on publicly available datasets
Show steps
Build proficiency in forecasting by working through numerous examples
Browse courses on
Time Series Analysis
Show steps
-
Identify and collect publicly available datasets
-
Apply forecasting techniques
-
Evaluate the models and refine your approach
Three other activities
Expand to see all activities and additional details
Show all six activities
Explore Vertex AI tutorials for model development
Show steps
Gain hands-on experience and reinforce understanding of model development techniques
Browse courses on
Vertex AI
Show steps
-
Select relevant tutorials from Vertex AI documentation
-
Follow tutorials step-by-step
-
Implement and test models
Create a presentation on forecasting techniques
Show steps
Develop strong communication skills and synthesize what you've learned by presenting your knowledge
Browse courses on
Forecasting Techniques
Show steps
-
Choose a specific forecasting technique
-
Research and gather information
-
Develop slides and visuals
-
Prepare to present your findings
-
Deliver an engaging presentation
Develop a forecasting model for a real-world dataset
Show steps
Apply forecasting concepts and tools to solve a practical problem, deepening knowledge
Browse courses on
Model Development
Show steps
-
Define a forecasting problem
-
Collect and prepare data
-
Choose appropriate forecasting techniques
-
Develop and evaluate models
-
Present and communicate findings
Compile course resources from syllabi, lectures, recordings, notes
Show steps
Gather and organize all relevant course materials to foster effective study habits
Browse courses on
C
Show steps
Show steps
Show steps
- Review syllabi and lecture notes
- Download and label recordings
- Organize materials into folders
Review the textbook 'Time Series Analysis and Forecasting: Theory and Methods'
Show steps
Supplemental reading can help solidify the complex concepts of the course
View
Time Series Forecasting
on Amazon
Show steps
Show steps
Show steps
- Focus on understanding time series notation and methods
- Critically evaluate models and their applications
- Connect theoretical concepts to practical forecasting scenarios
Practice forecasting on publicly available datasets
Show steps
Build proficiency in forecasting by working through numerous examples
Browse courses on
Time Series Analysis
Show steps
Show steps
Show steps
- Identify and collect publicly available datasets
- Apply forecasting techniques
- Evaluate the models and refine your approach
Three other activities
Expand to see all activities and additional details
Show all six activities
Explore Vertex AI tutorials for model development
Show steps
Gain hands-on experience and reinforce understanding of model development techniques
Browse courses on
Vertex AI
Show steps
Show steps
Show steps
- Select relevant tutorials from Vertex AI documentation
- Follow tutorials step-by-step
- Implement and test models
Create a presentation on forecasting techniques
Show steps
Develop strong communication skills and synthesize what you've learned by presenting your knowledge
Browse courses on
Forecasting Techniques
Show steps
Show steps
Show steps
- Choose a specific forecasting technique
- Research and gather information
- Develop slides and visuals
- Prepare to present your findings
- Deliver an engaging presentation
Develop a forecasting model for a real-world dataset
Show steps
Apply forecasting concepts and tools to solve a practical problem, deepening knowledge
Browse courses on
Model Development
Show steps
Show steps
Show steps
- Define a forecasting problem
- Collect and prepare data
- Choose appropriate forecasting techniques
- Develop and evaluate models
- Present and communicate findings
Career center
Learners who complete Introduction to Vertex Forecasting and Time Series in Practice will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. They work closely with data scientists to identify the right problems to solve and the best approaches to use. This course will give you a strong foundation in the fundamentals of machine learning and time series forecasting. You will also learn about the different tools and techniques available on Google Cloud for building and deploying machine learning models.
Data Analyst
Data Analyst
Data Analysts are employed across a wide range of industries, including finance, healthcare, and manufacturing. They collect, analyze, and interpret data to help organizations make informed decisions. The course will help you to develop the skills you need to succeed in this role, including data preparation, model training, and model evaluation. You will also learn about the different forecasting options available on Google Cloud.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. They work with businesses to improve efficiency and productivity. This course will give you a strong foundation in the mathematics and statistics you need to succeed in this role. You will also learn about the different forecasting techniques that are used in operations research.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. They work with a variety of organizations to help them make informed decisions. This course will give you a strong foundation in the mathematics and statistics you need to succeed in this role. You will also learn about the different forecasting techniques that are used in statistics.
Data Scientist
Data Scientist
Data Scientists use data to solve a variety of business problems. They work with a variety of organizations to help them make informed decisions. This course will give you a strong foundation in the mathematics, statistics, and programming skills you need to succeed in this role. You will also learn about the different forecasting techniques that are used in data science.
Business Analyst
Business Analyst
Business Analysts use data to help organizations make better decisions. They work with stakeholders to identify the right problems to solve and the best approaches to use. This course will give you a strong foundation in the data analysis techniques that are used in this role. You will also learn about the different forecasting techniques that are used to predict business performance.
Financial Analyst
Financial Analyst
Financial Analysts use financial data to evaluate the performance of companies and make investment recommendations. This course will give you a strong foundation in the financial analysis techniques that are used in this role. You will also learn about the different forecasting techniques that are used to predict financial performance.
Marketing Analyst
Marketing Analyst
Marketing Analysts use data to help organizations make better marketing decisions. They work with marketing teams to identify the right target audience and the best marketing campaigns to use. This course will give you a strong foundation in the data analysis techniques that are used in this role. You will also learn about the different forecasting techniques that are used to predict marketing performance.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. They help investment firms make investment decisions. This course will give you a strong foundation in the mathematics and statistics you need to succeed in this role. You will also learn about the different forecasting techniques that are used in the financial industry.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They work with a variety of organizations to help them achieve their business goals. This course will give you a strong foundation in the computer science skills you need to succeed in this role. You will also learn about the different software development tools and techniques that are used in the software industry.
Computer Scientist
Computer Scientist
Computer Scientists conduct research and develop new computing technologies. They work with a variety of organizations to help them solve complex problems. This course will give you a strong foundation in the computer science skills you need to succeed in this role. You will also learn about the different research areas that are currently being pursued in computer science.
Consultant
Consultant
Consultants provide advice and expertise to organizations on a variety of topics. They work with a variety of organizations to help them solve problems and achieve their goals. This course may give you a strong foundation in the business skills you need to succeed in this role. You may also learn about the different consulting techniques that are used in the consulting industry.
Actuary
Actuary
Actuaries use mathematical and statistical models to assess risk. They work with a variety of organizations to help them make informed decisions about risk management. This course may give you a strong foundation in the mathematics and statistics you need to succeed in this role. You may also learn about the different forecasting techniques that are used in actuarial science.
Economist
Economist
Economists study the production, distribution, and consumption of goods and services. They work with a variety of organizations to help them understand the economy and make informed decisions. This course may give you a strong foundation in the economics concepts you need to succeed in this role. You may also learn about the different forecasting techniques that are used in economics.
Teacher
Teacher
Teachers educate students at all levels. They work with a variety of schools and organizations to help students learn and grow. This course may give you a strong foundation in the teaching skills you need to succeed in this role. You may also learn about the different teaching methods that are used in the education industry.
For more career information including salaries, visit:
OpenCourser.com/course/a3e8gq/introduction
Reading list
We've selected seven 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
Introduction to Vertex Forecasting and Time Series in Practice.
Comprehensive and up-to-date overview of the field of time series analysis and forecasting. It valuable resource for anyone interested in learning more about this topic, regardless of their level of experience.
Save
Provides a comprehensive overview of the field of time series econometrics. It covers a wide range of topics, including time series models, forecasting, and econometric analysis.
Classic in the field of time series analysis and forecasting. It provides a clear and concise introduction to the basic concepts and methods of time series analysis, and it valuable resource for anyone interested in learning more about this topic.
Provides a comprehensive overview of the field of time series analysis and its applications. It covers a wide range of topics, including time series models, forecasting, and econometric analysis.
Provides a comprehensive overview of the field of forecasting. It covers a wide range of topics, including forecasting methods, forecasting applications, and forecasting software.
Provides a comprehensive overview of the field of time series forecasting using machine learning. It covers a wide range of topics, including data preparation, feature engineering, model selection, and model evaluation.
This handbook provides a comprehensive overview of the field of data mining and knowledge discovery. It covers a wide range of topics, including data mining techniques, machine learning algorithms, and data visualization techniques.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/a3e8gq/introduction
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Time
182 hours
Level
Intermediate
Via
Pluralsight
Instructor
Google Cloud
Language
English
Good to know
Intended for learners and professionals who want to build and evaluate forecasting models on Google Cloud
Taught by Google Cloud professionals who are authorities in the field of forecasting
Covers how to use Google Cloud's Vertex AI for predictive modeling
Provides hands-on experience with real-world retail datasets
May require additional background knowledge in statistics, machine learning, and data analysis
May not be suitable for complete beginners in forecasting or Google Cloud
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