OK Google: Build Interactive Apps with Google Assistant

Course Overview

This course provides an overview of how to build interactive applications with Google Assistant. Participants will learn how to use the Dialogflow conversational suite and the Actions and Cloud Functions frameworks to create practical Google Assistant applications integrated with Google Cloud services via APIs. Through five labs, participants will build five different applications that explore useful and fun tools they can extend on their own. No hardware is required, as the cloud-based Google Assistant simulator environment is used for developing and testing. If participants have their own device, such as a Google Home or a Google Hub, additional instructions are provided on how to deploy their apps to their own hardware.

[Applications]
Upon completion of this course, participants should be able to apply their knowledge to create their own Google Assistant applications. They should be able to use the Dialogflow conversational suite and the Actions and Cloud Functions frameworks to create interactive applications. Participants should also be able to deploy their applications to their own hardware, such as a Google Home or a Google Hub.

[Career Paths]
1. Google Assistant Developer: Google Assistant Developers are responsible for creating and maintaining applications for Google Assistant. They must be knowledgeable in the Google Assistant platform, Dialogflow, Actions and Cloud Functions frameworks, and have experience in developing interactive applications. As the demand for Google Assistant applications continues to grow, the need for experienced Google Assistant Developers is expected to increase.

2. Voice User Interface (VUI) Designer: VUI Designers are responsible for designing the user experience for voice-based applications. They must have a strong understanding of user experience design principles, as well as the ability to create intuitive and engaging user interfaces for voice-based applications. As the demand for voice-based applications continues to grow, the need for experienced VUI Designers is expected to increase.

3. Natural Language Processing (NLP) Engineer: NLP Engineers are responsible for developing and maintaining natural language processing algorithms for voice-based applications. They must have a strong understanding of natural language processing techniques, as well as the ability to develop algorithms that can accurately interpret user input. As the demand for voice-based applications continues to grow, the need for experienced NLP Engineers is expected to increase.

4. Cloud Platform Engineer: Cloud Platform Engineers are responsible for developing and maintaining cloud-based applications. They must have a strong understanding of cloud-based technologies, as well as the ability to develop and maintain applications that are hosted on cloud-based platforms. As the demand for cloud-based applications continues to grow, the need for experienced Cloud Platform Engineers is expected to increase.

[Education Paths]
1. Bachelor of Science in Computer Science: This degree path focuses on the fundamentals of computer science, including programming, software engineering, and computer architecture. It also covers topics such as artificial intelligence, machine learning, and data science. With the increasing demand for AI and machine learning, this degree path is becoming increasingly popular and is expected to continue to grow in the coming years.

2. Bachelor of Science in Information Technology: This degree path focuses on the application of technology to solve business problems. It covers topics such as systems analysis, database design, network security, and web development. With the increasing demand for IT professionals, this degree path is becoming increasingly popular and is expected to continue to grow in the coming years.

3. Master of Science in Artificial Intelligence: This degree path focuses on the development of AI systems and their applications. It covers topics such as machine learning, natural language processing, computer vision, and robotics. With the increasing demand for AI professionals, this degree path is becoming increasingly popular and is expected to continue to grow in the coming years.

4. Master of Science in Data Science: This degree path focuses on the analysis and interpretation of large datasets. It covers topics such as data mining, machine learning, and predictive analytics. With the increasing demand for data scientists, this degree path is becoming increasingly popular and is expected to continue to grow in the coming years.