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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 train a simple machine learning model for predicting helpdesk response time using BigQuery Machine Learning.

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What's inside

Syllabus

Integrating BigQuery ML with Dialogflow ES Chatbot

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Appropriate for those new to machine learning
Explores industry-standard BigQuery Machine Learning
Provides practical experience with a self-paced lab

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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 Integrating BigQuery ML with Dialogflow ES Chatbot with these activities:
Practice Exercises on BigQuery ML Query Language
Reinforce understanding of BigQuery ML query language through repetitive exercises, improving syntax proficiency and query optimization skills.
Browse courses on BigQuery ML
Show steps
  • Write queries to predict numerical and categorical values
  • Use advanced query features such as cross-validation and feature importance
Interactive Tutorial on BigQuery ML
Explore and interact with the BigQuery ML API to gain hands-on experience with supervised machine learning.
Browse courses on BigQuery ML
Show steps
  • Sign up for a Google Cloud Platform account
  • Create a Big Query dataset
  • Run a sample linear regression query
Literature Review on BigQuery ML Applications
Enhance understanding of real-world applications of BigQuery ML by reviewing and summarizing research papers and case studies.
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Show steps
  • Search for relevant literature
  • Read and synthesize the findings
  • Create a structured summary or presentation
Four other activities
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Guided Tutorial on Deploying a ML model to Dialogflow
Follow a guided tutorial to integrate a trained ML model with a Dialogflow chatbot, enhancing chatbot responses with predictive insights.
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Show steps
  • Create a Dialogflow agent
  • Build and deploy a Node.js fulfillment function
  • Integrate the ML model with the fulfillment function
Build a Predictive Helpdesk Chatbot Prototype
Demonstrate mastery by creating a functional chatbot prototype that leverages BigQuery ML to predict helpdesk response times, enhancing the user experience.
Browse courses on Dialogflow
Show steps
  • Design the chatbot interface and functionality
  • Implement the chatbot logic and integrate with BigQuery ML
  • Test and refine the chatbot's performance
Contribute to the BigQuery ML Open Source Project
Gain practical experience and contribute to the community by reporting bugs, suggesting enhancements, or contributing code to the BigQuery ML open-source project.
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Show steps
  • Review the project documentation
  • Identify an area for contribution
  • Make a pull request with your proposed changes
Participate in a Machine Learning Hackathon
Challenge oneself and gain valuable experience by participating in a hackathon focused on machine learning, showcasing skills and collaborating with others.
Browse courses on Machine Learning
Show steps
  • Find a hackathon that aligns with interests
  • Form a team or work individually
  • Develop and submit a project that addresses the hackathon challenge

Career center

Learners who complete Integrating BigQuery ML with Dialogflow ES Chatbot will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
A Machine Learning Engineer designs, builds, deploys, and maintains machine learning models. They work with data scientists to gather and prepare data, and they develop algorithms to train and evaluate models. Machine Learning Engineers also work with software engineers to integrate models into applications. This course may be useful for Machine Learning Engineers who want to learn how to use BigQuery Machine Learning to train and deploy models.
Data Scientist
A Data Scientist uses data to solve business problems. They collect, clean, and analyze data to identify patterns and trends. Data Scientists also develop models to predict future outcomes and make recommendations. This course may be useful for Data Scientists who want to learn how to use BigQuery Machine Learning to train and deploy models.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. They work with users to gather requirements and design software solutions. Software Engineers also write code, test applications, and deploy them to production. This course may be useful for Software Engineers who want to learn how to integrate BigQuery Machine Learning models into applications.
Business Analyst
A Business Analyst identifies and solves business problems using data. They work with stakeholders to understand business needs and develop solutions that meet those needs. Business Analysts also track and measure the success of solutions. This course may be useful for Business Analysts who want to learn how to use BigQuery Machine Learning to identify and solve business problems.
Product Manager
A Product Manager is responsible for the development and launch of new products. They work with engineers, designers, and marketers to create products that meet customer needs. Product Managers also track and measure the success of products. This course may be useful for Product Managers who want to learn how to use BigQuery Machine Learning to identify and solve customer problems.
Marketing Analyst
A Marketing Analyst uses data to measure the effectiveness of marketing campaigns. They collect, clean, and analyze data to identify trends and patterns. Marketing Analysts also develop models to predict future outcomes and make recommendations. This course may be useful for Marketing Analysts who want to learn how to use BigQuery Machine Learning to measure the effectiveness of marketing campaigns.
Financial Analyst
A Financial Analyst uses data to make investment decisions. They collect, clean, and analyze data to identify trends and patterns. Financial Analysts also develop models to predict future outcomes and make recommendations. This course may be useful for Financial Analysts who want to learn how to use BigQuery Machine Learning to make investment decisions.
Operations Research Analyst
An Operations Research Analyst uses data to solve business problems. They work with businesses to identify and solve problems related to logistics, scheduling, and inventory management. Operations Research Analysts also develop models to predict future outcomes and make recommendations. This course may be useful for Operations Research Analysts who want to learn how to use BigQuery Machine Learning to solve business problems.
Statistician
A Statistician collects, analyzes, interprets, and presents data. They work with businesses and organizations to help them understand their data and make informed decisions. Statisticians also develop models to predict future outcomes and make recommendations. This course may be useful for Statisticians who want to learn how to use BigQuery Machine Learning to analyze data and make predictions.
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines. They work with data scientists and engineers to collect, clean, and transform data. Data Engineers also develop tools and processes to automate data processing tasks. This course may be useful for Data Engineers who want to learn how to use BigQuery Machine Learning to train and deploy models.
Database Administrator
A Database Administrator manages and maintains databases. They work with database users to ensure that data is accurate and accessible. Database Administrators also develop and implement security measures to protect data. This course may be useful for Database Administrators who want to learn how to use BigQuery Machine Learning to analyze data and identify trends.
Systems Analyst
A Systems Analyst designs, develops, and implements computer systems. They work with businesses and organizations to identify and solve business problems. Systems Analysts also develop and implement security measures to protect data. This course may be useful for Systems Analysts who want to learn how to use BigQuery Machine Learning to analyze data and identify trends.
Information Security Analyst
An Information Security Analyst protects computer systems and data from unauthorized access. They work with businesses and organizations to identify and mitigate security risks. Information Security Analysts also develop and implement security measures to protect data. This course may be useful for Information Security Analysts who want to learn how to use BigQuery Machine Learning to identify and mitigate security risks.
Network Administrator
A Network Administrator manages and maintains computer networks. They work with businesses and organizations to ensure that networks are reliable and secure. Network Administrators also develop and implement security measures to protect data. This course may be useful for Network Administrators who want to learn how to use BigQuery Machine Learning to analyze data and identify trends.
Computer Programmer
A Computer Programmer writes and maintains computer code. They work with businesses and organizations to develop and implement computer systems. Computer Programmers also develop and implement security measures to protect data. This course may be useful for Computer Programmers who want to learn how to use BigQuery Machine Learning to analyze data and identify trends.

Reading list

We've selected nine 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 Integrating BigQuery ML with Dialogflow ES Chatbot.
Provides a comprehensive overview of natural language processing, including topics such as tokenization, stemming, and machine learning. Useful for providing background knowledge on natural language processing.
Provides a comprehensive overview of deep learning, including topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. Useful for providing more depth on the machine learning aspect of the course.
Provides a practical guide to data analytics. Useful for providing additional reading on how to use data analytics in practice.
Provides a comprehensive overview of Python for data analysis. Useful for providing additional reading on how to use Python for data analysis.
Provides a comprehensive overview of R for data science. Useful for providing additional reading on how to use R for data science.

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