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Google Cloud Training

This is a Google Cloud Self-Paced Lab. In this hands-on lab, you will use Apps Script to call the Natural Language API from Google Docs to analyze the sentiment of selected text in the document.

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What's inside

Syllabus

Using the Natural Language API from Google Docs

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches learners basic concepts of the Natural Language API and Google Cloud Platform. This strengthens a foundation for intermediate learners
Develops skills in natural language processing, which are core skills for data scientists and AI engineers
Offers hands-on labs, which allow learners to immediately apply their new knowledge

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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 Using the Natural Language API from Google Docs with these activities:
Review your notes and assignments from a previous course on natural language processing
Refresh your memory on key NLP concepts to prepare for this course.
Show steps
  • Locate your previous notes and assignments
  • Review the materials
Analyze text sentiment using the Natural Language API
Develop your skills in using the Natural Language API by completing exercises.
Browse courses on Sentiment Analysis
Show steps
  • Find practice problems or exercises
  • Analyze text sentiment using the Natural Language API
  • Check your answers
Join a study group or discussion forum for this course
Engage with your peers to reinforce your understanding of course concepts.
Browse courses on Natural Language API
Show steps
  • Find a study group or discussion forum
  • Participate in discussions
  • Collaborate with your peers
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow a tutorial on using the Natural Language API in Apps Script
Gain hands-on experience with the Natural Language API by following a guided tutorial.
Browse courses on Apps Script
Show steps
  • Find a tutorial
  • Follow the tutorial step-by-step
  • Deploy the solution
Volunteer at a local organization that uses natural language processing
Gain practical experience in the field of natural language processing.
Show steps
  • Identify volunteer opportunities
  • Apply for a volunteer position
  • Assist with natural language processing tasks
Create a compilation of resources on natural language processing
Expand your knowledge of natural language processing by gathering and organizing resources.
Show steps
  • Identify relevant resources
  • Organize the resources into a compilation
  • Share the compilation with others
Build a web app that analyzes text sentiment
Demonstrate your understanding of the Natural Language API by building a real-world application.
Browse courses on Sentiment Analysis
Show steps
  • Create a Cloud Function
  • Connect the Cloud Function to the Natural Language API
  • Deploy your Cloud Function
  • Build a user interface for your web app
Create a text analysis tool
Apply your understanding of the Natural Language API to build a useful tool.
Browse courses on Sentiment Analysis
Show steps
  • Identify a problem to solve
  • Design your tool
  • Develop your tool
  • Deploy your tool

Career center

Learners who complete Using the Natural Language API from Google Docs will develop knowledge and skills that may be useful to these careers:
Natural Language Processing Engineer
The Natural Language Processing Engineer is responsible for designing and developing natural language processing (NLP) systems. NLP systems are used to analyze and understand human language, and they are used in a variety of applications, such as machine translation, speech recognition, and text summarization. This course is highly relevant to the role of the Natural Language Processing Engineer, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many NLP applications.
Machine Learning Engineer
The Machine Learning Engineer is responsible for designing and developing machine learning models. Machine learning models are used to make predictions or decisions based on data, and they are used in a variety of applications, such as image recognition, fraud detection, and predictive analytics. This course is highly relevant to the role of the Machine Learning Engineer, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many machine learning applications.
Data Scientist
The Data Scientist is responsible for collecting, cleaning, and analyzing data to identify trends and patterns. Data scientists use their findings to make recommendations and develop solutions to business problems. This course is highly relevant to the role of the Data Scientist, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many data science applications.
Software Engineer
The Software Engineer is responsible for designing, developing, and maintaining software applications. Software engineers use their knowledge of programming languages and software development tools to create software that meets the needs of users. This course is highly relevant to the role of the Software Engineer, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many software applications.
Product Manager
The Product Manager is responsible for defining and managing the product roadmap. Product managers work with engineers, designers, and other stakeholders to ensure that products are built to meet the needs of users. This course may be useful to the Product Manager, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many product management applications.
Business Analyst
The Business Analyst is responsible for analyzing business processes and identifying opportunities for improvement. Business analysts use their knowledge of business and technology to help organizations make better decisions. This course may be useful to the Business Analyst, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many business analysis applications.
Technical Writer
The Technical Writer is responsible for creating and maintaining technical documentation. Technical writers use their knowledge of writing and technology to create documentation that is clear and easy to understand. This course may be useful to the Technical Writer, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many technical writing applications.
Content Writer
The Content Writer is responsible for creating and maintaining content for websites and other digital platforms. Content writers use their knowledge of writing and digital marketing to create content that is engaging and informative. This course may be useful to the Content Writer, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many content writing applications.
Financial Manager
The Financial Manager is responsible for planning, executing, and controlling the financial function of an organization. Financial managers work with their team to develop and implement financial plans, and they also track and measure the performance of their financial function. This course may be useful to the Financial Manager, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many financial management applications.
Marketing Manager
The Marketing Manager is responsible for planning and executing marketing campaigns. Marketing managers work with their team to develop and implement marketing strategies, and they also track and measure the results of their campaigns. This course may be useful to the Marketing Manager, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many marketing management applications.
Project Manager
The Project Manager is responsible for planning, executing, and closing projects. Project managers work with their team to develop and execute project plans, and they also track and measure the progress of their projects. This course may be useful to the Project Manager, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many project management applications.
Sales Manager
The Sales Manager is responsible for leading and motivating a sales team. Sales managers work with their team to develop and execute sales strategies, and they also provide training and support. This course may be useful to the Sales Manager, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many sales management applications.
Operations Manager
The Operations Manager is responsible for planning, executing, and controlling the day-to-day operations of an organization. Operations managers work with their team to develop and implement operational plans, and they also track and measure the performance of their operations. This course may be useful to the Operations Manager, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many operations management applications.
Customer Success Manager
The Customer Success Manager is responsible for ensuring that customers are satisfied with their products and services. Customer success managers work with customers to identify and resolve issues, and they also provide training and support. This course may be useful to the Customer Success Manager, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many customer success management applications.
Human Resources Manager
The Human Resources Manager is responsible for planning, executing, and controlling the human resources function of an organization. Human resources managers work with their team to develop and implement human resources policies, and they also track and measure the performance of their human resources function. This course may be useful to the Human Resources Manager, as it provides an introduction to the Natural Language API from Google Docs. This API can be used to analyze the sentiment of text, which is a key task in many human resources management applications.

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 Using the Natural Language API from Google Docs.
Provides a comprehensive overview of natural language processing (NLP) techniques, including sentiment analysis. It valuable resource for anyone interested in learning more about NLP and its applications.
Provides a comprehensive overview of deep learning techniques for natural language processing. It valuable resource for anyone interested in learning more about deep learning and its applications to NLP.
Provides a comprehensive overview of sentiment analysis and opinion mining. It covers a wide range of topics, including how to collect and prepare data, and how to build and evaluate sentiment analysis models.
Provides a comprehensive overview of deep learning techniques for natural language processing. It valuable resource for anyone interested in learning more about deep learning and its applications to NLP.
Provides a comprehensive overview of natural language processing techniques, including sentiment analysis. It valuable resource for anyone interested in learning more about NLP and its applications.
Provides a practical guide to using natural language processing for social science research. It covers a wide range of topics, including sentiment analysis.

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