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Integrating Applications with Gemini 1.0 Pro on Google Cloud

Google Cloud Training

This short course on integrating applications with Gemini 1.0 Pro models on Google Cloud helps you discover the Gemini API and its generative AI models. The course teaches you how to access the Gemini 1.0 Pro and Gemini 1.0 Pro Vision models from code. It lets you test the capabilities of the models with text, image, and video prompts from an app.

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What's inside

Syllabus

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Provides a comprehensive overview of the Gemini API and its generative AI models
Taught by Google Cloud Training, renowned for their expertise in cloud computing
Develops skills in integrating applications with Gemini 1.0 Pro models, which are highly relevant in data science and AI development

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Reviews summary

Practical gemini 1.0 pro integration

According to students, this course offers a highly practical and concise introduction to integrating applications with Gemini 1.0 Pro on Google Cloud. Learners particularly appreciate the clear explanations and well-structured content, making it an excellent starting point for those new to the Gemini API. The course provides valuable hands-on experience through its helpful labs, where students learn to build functional Streamlit applications. While ideal for beginners in Gemini, a background in Python is advisable. The fact that this high-quality content is offered for free is also a significant positive.
Prior Python knowledge is beneficial for optimal understanding.
"It is good to have prior knowledge in Python to understand everything better."
"I found that having some Python experience made the hands-on labs much smoother to follow."
High-quality content is provided at no cost to learners.
"Thank you for providing this course for free."
"The value for a free course like this is truly exceptional."
Provides an effective starting point for learning the Gemini 1.0 Pro API.
"Highly recommended for people who want to start learning about Gemini."
"This course is a quick and effective introduction to the Gemini 1.0 Pro and Vision APIs..."
"Good course that guides you well to start working with Gemini 1.0 pro API... Very good for beginners interested in Gemini."
"It gives a good overview of the subject."
Content is well-structured, clear, and focused on essential concepts.
"Very useful course and well structured, simple and very clear examples."
"Excellent explanation, practical. It's concise and covers the essential."
"The labs are very clear."
"Very good course for quickly understanding and applying... with concrete examples that facilitate the learning process."
"The content is concise and explanatory."
Excellent for practical experience through guided labs and app building.
"It is short but intense and very practical due to the labs. Highly recommended!"
"The labs are really helpful and help you apply what you learn in the videos."
"The hands-on labs are particularly valuable, providing practical experience in building a Streamlit application..."
"This is a great, concise and effective course. It provides a good hands-on experience by building a Streamlit app."
"The course is very useful and very practical. I really like the structure and the labs."

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 Applications with Gemini 1.0 Pro on Google Cloud with these activities:
Follow Tutorials on Generative AI
Seek out and follow tutorials on generative AI to refine your skills and explore different applications.
Browse courses on Generative AI
Show steps
  • Identify reputable sources for generative AI tutorials.
  • Choose tutorials that align with your interests and learning goals.
  • Follow the tutorials step-by-step and experiment with the code.
Seek Mentorship from Generative AI Experts
Find and connect with mentors in the field of generative AI to gain guidance and insights.
Browse courses on Generative AI
Show steps
  • Attend industry events and conferences.
  • Reach out to professionals in your network.
  • Search for online mentoring platforms.
Compile Resources on Generative AI
Gather and compile resources on generative AI to expand your knowledge and stay up-to-date.
Browse courses on Generative AI
Show steps
  • Search for relevant articles, blog posts, and documentation.
  • Identify and evaluate different tools and frameworks for generative AI.
  • Organize and categorize the resources.
  • Share your compilation with others.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Review the Gemini API
Review the Gemini API in advance to gain a stronger foundation before starting the course.
Show steps
  • Read the Gemini API documentation.
  • Explore the Gemini API examples.
  • Create a sample application using the Gemini API.
Practice using the Gemini Models
Practice using the Gemini models to gain confidence and improve proficiency.
Show steps
  • Test the Gemini 1.0 Pro model on different text prompts.
  • Experiment with different image and video prompts for the Gemini 1.0 Pro Vision model.
  • Develop your own use cases for the Gemini models.
Practice Writing Prompts for Generative AI
Practice writing effective prompts for generative AI models to improve your results.
Browse courses on Generative AI
Show steps
  • Understand the different types of prompts.
  • Identify the key elements of a good prompt.
  • Write practice prompts for different use cases.
  • Test your prompts with generative AI models.
Develop an Application Using the Gemini API
Create an application using the Gemini API to apply your knowledge and reinforce your learning.
Browse courses on Application Development
Show steps
  • Design the architecture of your application.
  • Implement the Gemini API into your application.
  • Test and debug your application.
  • Deploy your application.
Contribute to Open Source Generative AI Projects
Contribute to open source generative AI projects to gain practical experience and connect with the community.
Browse courses on Generative AI
Show steps
  • Identify open source generative AI projects that align with your interests.
  • Review the project documentation and code.
  • Make contributions to the project.
  • Collaborate with other contributors.

Career center

Learners who complete Integrating Applications with Gemini 1.0 Pro on Google Cloud will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 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 Applications with Gemini 1.0 Pro on Google Cloud.
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Streamlit for Data Science
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Patterns for API Design
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RESTful Web APIs
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Pattern Recognition and Machine Learning
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Undisturbed REST
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This guide focuses on the design aspects of REST APIs, emphasizing the importance of a well-thought-out design that can evolve over time. It's valuable for understanding the challenges and considerations in creating a robust and maintainable API design.
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Building Microservices
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While not exclusively about APIs, this book is crucial for understanding the architectural style that heavily relies on APIs for communication between services. It covers the principles, benefits, and challenges of building microservices, providing essential context for API integration within such systems. It's a foundational text for anyone working with microservices.
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Python Data Science Handbook
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This handbook comprehensive reference for essential Python libraries for data science, including NumPy, Pandas, Matplotlib, and Scikit-learn. These libraries are foundational for most data applications built with Streamlit. is an excellent resource for deepening understanding of the data science ecosystem around Streamlit.
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Designing Data-Intensive Applications
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Enterprise Integration Patterns
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Applied Text Analysis with Python
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Given the mention of NLP and LLMs in the course titles, this book provides a strong foundation in text analysis using Python. The techniques and concepts covered are directly applicable to building Streamlit applications that involve processing and analyzing text data or integrating with language models.
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Financial Data Analysis Using Python
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The Creative Mind
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Machine Learning for Hackers
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Machine Learning for Hackers: Case Studies and...
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Hands-On Machine Learning with Scikit-Learn, Keras,...
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Provides a practical introduction to machine learning using Python. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning. The author is an experienced machine learning engineer, and the book is written in a clear and accessible style.
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Hands-On Machine Learning with Scikit-Learn, Keras,...
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Natural Language Processing with PyTorch
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Provides a practical introduction to natural language processing using PyTorch. It covers a wide range of topics, including text classification, named entity recognition, and machine translation. The authors are both experienced machine learning engineers, and the book is written in a clear and accessible style.
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Python for Data Analysis
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While not solely focused on Streamlit, this book classic for anyone working with data in Python. It provides a strong foundation in data manipulation and analysis using libraries like Pandas and NumPy, which are essential prerequisites for building data-driven Streamlit applications. It's a valuable reference for data handling techniques often used in Streamlit apps.
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Data Visualization for Social and Policy Research
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Provides an overview of data visualization in both R and Python, covering key libraries like Seaborn and Plotly. For Streamlit developers, the Python visualization chapters are particularly relevant for creating compelling charts and graphs within their applications. It can serve as a good reference for visualization techniques.
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Data Visualization for Social and Policy Research:...
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Fluent Python
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To write efficient and maintainable Streamlit code, a strong understanding of intermediate to advanced Python concepts is beneficial. dives deep into Python's features and best practices, making it an excellent resource for experienced Python developers looking to deepen their language skills for more complex Streamlit projects.
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Storytelling with Data
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Creating effective Streamlit applications often involves telling a story with data through visualizations. focuses on the principles of data storytelling and creating visualizations that resonate with an audience. It's a valuable read for improving the communication aspect of Streamlit data apps.
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storytelling with data podcast
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Introducing Speech and Language Processing
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Provides a concise introduction to computational linguistics. It covers a wide range of topics, including natural language processing, machine translation, and speech recognition. The author leading researcher in the field of NLP, and the book is written in a clear and accessible style.
Introducing Speech and Language Processing...
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Fundamentals of Data Visualization
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While not tied to a specific programming language, this book covers the principles of effective data visualization. Understanding these principles is crucial for creating impactful visualizations in Streamlit apps. It's a valuable resource for anyone serious about presenting data clearly and effectively.
Fundamentals of Data Visualization: A Primer on...
Kindle Edition
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Python Crash Course, 2nd Edition
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This widely recommended book for learning the fundamentals of Python programming. A solid understanding of Python necessary prerequisite for learning Streamlit. provides a project-based approach that helps build a strong programming foundation.
Python Crash Course, 2nd Edition: A Hands-On,...
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Python Crash Course, 2nd Edition: A Hands-On,...
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Python for Data Science For Dummies
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Offers a beginner-friendly introduction to using Python for data science. It covers essential libraries and concepts in a straightforward manner, making it a good starting point for those new to both Python and data science before diving into Streamlit specifics.
Python for Data Science For Dummies (For Dummies...
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Python for Data Science For Dummies (For Dummies...
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Python for Data Science For Dummies (For Dummies...
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Python for Data Science For Dummies
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Python for Data Science For Dummies
Kindle Edition
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Deep Medicine
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Explores the potential applications of generative AI in healthcare, discussing how it could be used to improve patient care and accelerate drug discovery. It is written by Eric Topol, a leading researcher in the field.
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Introductory
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Language
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Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Provides a comprehensive overview of the Gemini API and its generative AI models
Taught by Google Cloud Training, renowned for their expertise in cloud computing
Develops skills in integrating applications with Gemini 1.0 Pro models, which are highly relevant in data science and AI development
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