Build an application to send Chat Prompts using the Gemini model from Coursera

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Build an application to send Chat Prompts using the Gemini model

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Uses Google's Vertex AI SDK, which allows developers to integrate generative AI models into their applications and workflows

Provides hands-on experience with the Gemini model, which is useful for those looking to implement cutting-edge AI in their projects

Presented by Google Cloud, which is known for its innovative cloud computing services and contributions to AI development

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 Build an application to send Chat Prompts using the Gemini model with these activities:

Review Python Fundamentals

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Reinforce your understanding of Python syntax and basic programming concepts, as the Vertex AI SDK is used within a Python environment.

Browse courses on Python

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Complete a Python tutorial covering data types, loops, and functions.
Write small Python scripts to practice using these concepts.

Brush up on API interactions

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Familiarize yourself with the concept of APIs and how to interact with them, as the Gemini model is accessed through an API.

Browse courses on API

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Read articles or watch videos explaining API concepts.
Experiment with a simple API using tools like curl or Postman.

Read 'Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow'

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Gain a broader understanding of machine learning and deep learning concepts, which underpin the Gemini model.

View Hands-On Machine Learning with Scikit-Learn,... on Amazon

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Read the chapters related to neural networks and deep learning.
Experiment with the code examples provided in the book.

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Follow Vertex AI SDK Tutorials

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Practice using the Vertex AI SDK with step-by-step tutorials to solidify your understanding of how to interact with the Gemini model.

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Find tutorials on the Google Cloud documentation or online platforms.
Follow the tutorials, paying close attention to the code examples.
Modify the code to experiment with different parameters and prompts.

Build a Simple Chatbot Interface

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Create a basic chatbot interface using Python and a framework like Flask or Streamlit to interact with the Gemini model.

Browse courses on Chatbot

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Design a simple user interface for the chatbot.
Integrate the Vertex AI SDK to send prompts to the Gemini model.
Display the responses from the Gemini model in the interface.
Add features like conversation history and user input validation.

Write a Blog Post on Your Gemini Chatbot Experience

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Document your experience building a chatbot with the Gemini model to share your knowledge and insights with others.

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Describe the process of building the chatbot, including the challenges you faced.
Share code snippets and examples to illustrate your approach.
Discuss the potential applications of the Gemini model in chatbot development.

Contribute to a Gemini API Wrapper Library

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Contribute to an open-source library that simplifies the process of interacting with the Gemini API, improving its accessibility for other developers.

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Find an existing open-source library for the Gemini API or create a new one.
Identify areas where you can contribute, such as adding new features or fixing bugs.
Submit your contributions to the library following the project's guidelines.

Career center

Learners who complete Build an application to send Chat Prompts using the Gemini model will develop knowledge and skills that may be useful to these careers:

Generative AI Specialist

A Generative AI Specialist focuses on creating and applying generative AI models. This course directly aligns with the core work of a Generative AI Specialist. This course helps build a foundation for interacting with a large language model. By working directly with the Gemini model, you'll gain an understanding of how to build applications with generative AI. Learning how to use chat prompts and interpret various responses is critical for success in this field. This course is excellent for anyone who wants to work with generative AI models directly. The practical experience gained while working in the Google Cloud console is of great value.

See salaries and explore the career path for Generative AI Specialist

AI Application Developer

An AI Application Developer builds applications incorporating artificial intelligence. This course helps build a foundation for developing and implementing AI powered applications. The course provides experience by utilizing the Vertex AI SDK to interact with the Gemini model. With this experience specific to text-based chat prompts, developers can learn to create a new class of applications. The ability to manage both non-streaming and streaming responses is also valuable for AI Application Developers. This is useful when the developer is creating interfaces that interact with users. This course is a great way to learn how to build and customize applications utilizing existing generative AI models.

See salaries and explore the career path for AI Application Developer

Chatbot Developer

A Chatbot Developer creates and maintains conversational AI applications. This course helps build a foundation for developing and deploying chatbots. The experience gained sending text-based chat prompts to the Gemini model, and interpreting the responses, is core to the activity of a Chatbot Developer. Using the Vertex AI SDK is exactly the kind of skill one needs to implement practical chatbot solutions. The hands-on experience of this course provides direct value. This course is very helpful for those interested in building practical chatbot applications. Understanding streaming and non-streaming responses is also critical for developing effective chatbots.

See salaries and explore the career path for Chatbot Developer

Artificial Intelligence Engineer

An Artificial Intelligence Engineer designs and implements AI models and applications. This course helps build a foundation for interacting with large language models, a crucial skill for Artificial Intelligence Engineers. The ability to use the Vertex AI SDK to send text-based chat prompts and receive responses directly translates to developing conversational AI applications. Successful engineers understand how to build applications that leverage powerful generative AI models. This course provides hands-on experience with Gemini, preparing you to engineer and customize AI solutions. It may be useful for a future AI Engineer to build applications that utilize chat prompts and understand how the responses manifest. The focus on both streaming and non-streaming responses is valuable, as those responses are often important for user experience.

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Natural Language Processing Engineer

A Natural Language Processing Engineer specializes in the interaction of computers and human language. This course helps build a foundation for natural language processing. By learning to send chat prompts and receive responses using the Vertex AI SDK and the Gemini model, a Natural Language Processing Engineer can better understand how to develop and integrate natural language models. An engineer should know how to work with these models directly. The course helps build an understanding of working with a particular generative AI model as it processes text based input. This course is useful for anyone who wants to work with the specifics of AI chat models and their responses. Specifically, examining streaming and non-streaming responses can be critical to these roles.

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Prompt Engineer

Prompt Engineers design and refine prompts for large language models. This course helps build a foundation in prompt engineering, focusing on how text-based chat prompts elicit different responses from the Gemini model. Prompt Engineers must understand how to work with a large language model. The practical nature of the course, using the Vertex AI SDK to send prompts, provides valuable, hands-on experience. This course is likely to be very helpful for one interested in prompt engineering, as it provides direct experience. By exploring both streaming and non-streaming responses, users can better understand how prompts influence model output.

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Conversational AI Designer

Conversational AI Designers focus on crafting the user experience for AI dialog systems. This course helps build a foundation in the technology underlying conversational interfaces. By working with the Gemini model, and seeing how it responds to text based prompts, designers can learn to better structure those experiences. The course may be useful for those trying to better understand how AI models operate. Seeing first hand how the models handles prompts, and how they output both streaming and non-streaming responses, is invaluable for designers. This course may be useful for those who want to understand the implementation of conversational interfaces.

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Machine Learning Engineer

Machine Learning Engineers create and deploy machine learning models. This course helps build a foundation for this by providing practical experience using a specific generative AI model. By learning to send chat prompts to Gemini using the Vertex AI SDK, you gain a valuable skill in working with and integrating large language models. Machine Learning Engineers need a strong understanding of how to work with machine learning technologies. This lab helps build that understanding, and is especially useful for integrating chat functionality into other applications. This course may be helpful for those interested in working with models, and may be particularly helpful understanding streaming and non-streaming responses.

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AI Product Manager

An AI Product Manager oversees the development and launch of AI-powered products. This course may be useful for those who need to understand the core technology of their products. This course may be particularly useful for product managers overseeing chat-based applications, as it provides insight into how Gemini responds to various prompts, and how the streaming mechanism works. This course can be useful for product managers who need to understand the technical specifics of their product. Any product manager who needs to understand and work with AI models may find this course beneficial.

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Software Developer

A Software Developer designs and develops software applications for any number of uses. This course may be useful for software developers who need to integrate chat functionalities into their applications. By learning how to use the Vertex AI SDK to interact with the Gemini model, this course gives hands on experience with the tools used to create sophisticated chat features. Software developers must know how to incorporate AI capabilities into their software. This course may be helpful for software developers interested in learning how to implement natural language capabilities into software products. Understanding streaming responses can also be important for software developers when creating a seamless user experience.

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Solutions Engineer

Solutions engineers combine technical expertise with sales skills to tailor solutions for clients. This course may be useful for those who need a base understanding of Google Cloud's AI/ML offerings. By learning how to use the Vertex AI SDK to interact with the Gemini model, and specifically the chat interface, this course may be useful for solutions engineers who often need demos and examples for clients. Solutions engineers should understand not only a system's functionality but also its implementation. The hands-on nature of this course can be very valuable. This course may be helpful for those who must be deeply familiar with the offerings they recommend.

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Cloud Solutions Architect

Cloud Solutions Architects design and implement cloud-based solutions. This course may be useful for them, focusing on using the Vertex AI SDK within the Google Cloud environment to interact with the Gemini model. A Cloud Solutions Architect needs to understand the capabilities and integration techniques of various cloud services. This course helps build a foundation for understanding how to incorporate AI capabilities into cloud solutions. Architects who understand Vertex AI may find this course helpful. Knowing how to use the Gemini model to build chat applications can also be valuable to architects building client facing applications.

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Technical Consultant

A Technical Consultant provides expert advice on technology solutions, and this course may be useful in that line of work. Specifically, a technical consultant focused on AI and machine learning may find this course helpful. This course helps build a foundation in using the Vertex AI SDK, and interacting with the Gemini model. A consultant should understand the specifics of the technology they are recommending, and this course can help develop a practical understanding of using generative AI models. This course may be especially helpful to consultants who recommend Google Cloud products. Consultants who need to understand the specifics of text-based chat prompts may find this course very valuable.

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Data Scientist

Data Scientists analyze data to extract insights and develop data-driven solutions. This course may be helpful, giving practical experience interacting with a generative AI model using the Vertex AI SDK for data interaction. Data Scientists may find value in this course if they are analyzing responses from large language models. This course may be useful for those interested in the data coming back from chat models, and in how such models function. Exploring streaming and non-streaming responses can also add to a data scientist's toolkit. This course may be especially helpful for those interested in model inputs and outputs.

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Research Scientist

Research Scientists investigate scientific questions to advance knowledge. Often, they require advanced degrees. This course may be useful for research scientists who investigate machine learning models. By learning how to send text-based chat prompts to the Gemini model, the researcher gains a deeper understanding of how these models operate. The practical nature of the course provides a foundation for future exploration. Researchers studying model inputs and outputs may find this course especially useful. The experience of working with the Vertex AI SDK may also be helpful. This course may be helpful to research projects involving generative AI and large language models.

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Build an application to send Chat Prompts using the Gemini model

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