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Google Cloud Training

This is a self-paced lab that takes place in the Google Cloud console.

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This is a self-paced lab that takes place in the Google Cloud console.

In this lab you will build a time series model to forcast demand of multiple products using BigQuery ML. This lab is based on a blog post and featured in an episode of Cloud OnAir.

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What's inside

Syllabus

Building Demand Forecasting with BigQuery ML

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops demand forecasting skills using BigQuery ML, which is standard in industry
Taught by Google Cloud Training, who are recognized for their work in cloud computing
Covers a practical use for BigQuery ML, which is highly relevant to business and data analysis
Hands-on labs provide an interactive learning experience
Part of Google Cloud Training's offerings, which have a strong reputation in the industry
May require additional knowledge of BigQuery and machine learning concepts before taking

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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 Demand Forecasting with BigQuery ML with these activities:
Find a Mentor in Time Series Forecasting
Finding a mentor in time series forecasting will allow you to connect with an experienced professional who can provide guidance and support.
Browse courses on Time Series Forecasting
Show steps
  • Search for a time series forecasting mentor in your network.
  • Reach out to the mentor and ask for their guidance.
  • Meet with the mentor regularly to discuss your progress and get feedback.
Compile a Resource List for Time Series Forecasting
By compiling a resource list for time series forecasting, you will create a valuable reference tool that you can use throughout the course and beyond.
Browse courses on Time Series Forecasting
Show steps
  • Search for online resources on time series forecasting.
  • Create a list of the most relevant and useful resources.
  • Organize the resources into categories or topics.
Review Fundamentals of Time Series Forecasting
By reviewing the fundamentals of time series forecasting, you will be able to build a stronger foundation for the course material.
Browse courses on Time Series Forecasting
Show steps
  • Read an introductory article or tutorial on time series forecasting.
  • Review your notes or study materials from a previous course on time series forecasting.
  • Complete a few practice problems on time series forecasting.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a Time Series Forecasting Workshop
Attending a time series forecasting workshop will allow you to learn from experts in the field and gain hands-on experience with time series forecasting tools.
Browse courses on Time Series Forecasting
Show steps
  • Search for a time series forecasting workshop in your area.
  • Register for the workshop.
  • Attend the workshop and participate in the activities.
Practice Building Time Series Models
Practicing building time series models will help you develop the skills necessary to complete the course projects.
Browse courses on Time Series Modeling
Show steps
  • Find a dataset that contains time series data.
  • Use BigQuery ML to build a time series model for the dataset.
  • Evaluate the performance of the model.
Participate in a Time Series Forecasting Study Group
Participating in a time series forecasting study group will allow you to connect with other students and discuss the course material in a collaborative environment.
Browse courses on Time Series Forecasting
Show steps
  • Find a time series forecasting study group to join.
  • Attend the study group meetings and participate in the discussions.
  • Help other students with the course material.
Mentor a Peer Student
Mentoring a peer student will help you reinforce your understanding of the course material and develop your communication skills.
Browse courses on Time Series Forecasting
Show steps
  • Find a peer student who is struggling with the course material.
  • Offer to help the student by answering their questions and providing guidance.
  • Meet with the student regularly to provide support and encouragement.
Build a Time Series Model for a Real-World Problem
Building a time series model for a real-world problem will allow you to apply the skills you learn in the course to a practical scenario.
Browse courses on Time Series Forecasting
Show steps
  • Identify a real-world problem that can be solved using time series forecasting.
  • Collect data for the problem.
  • Build a time series model for the data.
  • Evaluate the performance of the model.
  • Deploy the model to production.

Career center

Learners who complete Building Demand Forecasting with BigQuery ML will develop knowledge and skills that may be useful to these careers:
Sales Forecasting Manager
Sales Forecasting Managers are responsible for predicting future sales. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to build models that can help businesses predict future sales and make better decisions about their sales strategies.
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning models. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to build and deploy models that can help businesses predict future demand for products or services.
Business Analyst
Business Analysts use data to help businesses identify opportunities and solve problems. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to analyze data and identify trends that can help businesses make better decisions.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical models to solve business problems. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to build models that can help businesses make better decisions about their operations.
Statistician
Statisticians collect, analyze, and interpret data to help businesses make informed decisions. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to analyze data and identify trends that can help businesses predict future demand for products or services.
Data Analyst
A Data Analyst gathers, cleans, and interprets data to help businesses make informed decisions. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to analyze data and identify trends that can help businesses predict future demand for products or services.
Demand Planner
Demand Planners are responsible for forecasting demand for products or services. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to build models that can help businesses predict future demand and make better decisions about their production and inventory levels.
Data Scientist
Data Scientists use data to build machine learning models that can predict future outcomes. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to build models that can help businesses predict future demand for products or services.
Marketing Analyst
Marketing Analysts use data to analyze marketing campaigns and make recommendations about marketing strategies. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to analyze data and identify trends that can help businesses make better decisions about their marketing campaigns.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to build models that can help businesses predict future demand for products or services.
Market Research Analyst
Market Research Analysts study market trends to help businesses understand their customers and make informed decisions. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to analyze data and identify trends that can help businesses make better decisions about their products or services.
Supply Chain Manager
Supply Chain Managers are responsible for managing the flow of goods and services from suppliers to customers. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to build models that can help businesses predict future demand and make better decisions about their supply chains.
Econometrician
Econometricians use statistical methods to analyze economic data. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to build models that can help businesses understand economic trends and make better decisions about their operations.
Financial Analyst
Financial Analysts use data to make recommendations about investments and financial decisions. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to analyze data and identify trends that can help businesses make better financial decisions.
Product Manager
Product Managers are responsible for developing and managing products. By learning to build demand forecasting models with BigQuery ML in this course, you can develop the skills necessary to understand customer需求s and make better decisions about product development.

Reading list

We've selected six 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 Demand Forecasting with BigQuery ML.
Provides a practical guide to forecasting using a variety of methods, including time series analysis, regression, and machine learning.
Provides a practical guide to big data analytics using Java, and includes a chapter on using BigQuery ML for forecasting.
Provides a comprehensive overview of statistical methods for forecasting, and includes a chapter on time series analysis.

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