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David Harris

Google Gemini is a new family of large language models (LLMs) developed by Google DeepMind. This course will teach you more about Google Gemini and how you can implement it to make your work easier.

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Google Gemini is a new family of large language models (LLMs) developed by Google DeepMind. This course will teach you more about Google Gemini and how you can implement it to make your work easier.

Businesses can leverage Gemini to streamline operations and offer innovative services, but many business owners and managers do not fully understand Gemini. In this course, First Look: Google Gemini, you’ll learn about Google Gemini and how you can use it in your day-to-day life. First, you’ll explore the defining features of Google Gemini. Next, you’ll discover how Gemini is used by businesses and individuals. Finally, you’ll learn about any ethical or security issues with using Gemini. When you’re finished with this course, you’ll have the skills and knowledge of Google Gemini needed to use it to improve your business and make your life more simple.

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What's inside

Syllabus

Course Overview
First Look: Google Gemini

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches skills and knowledge that are likely highly relevant in industry, where NLP is now commonly leveraged
Taught by David Harris, who is recognized for their contributions to NLP and language modeling
Develops foundations for beginners in large language models and NLP
Examines Google Gemini from a business perspective, exploring how businesses can use it to improve efficiency and innovate
Builds foundational skills in NLP and large language models, which can be useful for personal growth and career development
Covers ethical and security considerations, offering guidance for responsible use of AI

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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 First Look: Google Gemini with these activities:
Review Prerequisite Math Skills
Building a strong foundation in prerequisite math skills will allow you to easily keep up with the pace of this course.
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  • Review basic algebra concepts
  • Practice solving equations and inequalities
  • Refresh your understanding of functions
Review foundational concepts
Familiarize yourself with the underlying concepts of large language models to strengthen your understanding of Google Gemini.
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  • Review lecture notes or textbooks on natural language processing and AI fundamentals.
  • Attend a webinar or online workshop on large language models.
Review machine learning concepts
Refresh your knowledge of machine learning to enhance your understanding of Google Gemini.
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  • Review the basics of machine learning, including algorithms and techniques.
  • Practice implementing machine learning models using a programming language.
15 other activities
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Review basic programming concepts
Review the basics of programming to prepare for this course.
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  • Review variables, data types, and operators.
  • Practice writing simple programs.
Follow Online Tutorials on Google Gemini
Following comprehensive tutorials will allow you to explore the finer details and nuances of Google Gemini.
Show steps
  • Identify reputable online resources
  • Select tutorials that align with your learning objectives
  • Watch and actively engage with the tutorials
  • Take notes and ask questions to enhance understanding
Follow tutorials on Google Gemini
Familiarize yourself with Google Gemini by following guided tutorials.
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  • Find tutorials on Google Gemini.
  • Follow the steps in the tutorials.
  • Experiment with the code and examples provided in the tutorials.
Participate in Peer-Led Discussion Groups
Engaging in peer discussions provides opportunities to exchange ideas and perspectives, enhancing your understanding.
Show steps
  • Join or create a peer-led discussion group
  • Prepare for discussions by reviewing course materials
  • Actively participate in discussions and ask questions
  • Share insights and provide constructive feedback to peers
Explore Google Gemini tutorials
Gain practical experience with Google Gemini by following step-by-step tutorials.
Show steps
  • Access Google's official documentation and tutorials for Google Gemini.
  • Enroll in an online course or training program that provides hands-on exercises.
Participate in discussion forums on Google Gemini
Engage with other learners and experts to exchange knowledge and insights about Google Gemini.
Browse courses on Google Gemini
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  • Join discussion forums related to Google Gemini.
  • Participate in discussions and ask questions.
  • Share your own experiences and knowledge with others.
Join a study group or online forum
Connect with other learners and exchange knowledge and experiences related to Google Gemini.
Show steps
  • Search for online communities or forums dedicated to Google Gemini.
  • Join a study group with fellow learners of the course.
Practice using Google Gemini API
Gain hands-on experience with Google Gemini by practicing using its API.
Show steps
  • Set up your Google Cloud account and enable the Google Gemini API.
  • Write code to call the Google Gemini API.
  • Test your code and analyze the results.
Write a blog post or article about Google Gemini
Solidify your understanding of Google Gemini by creating content that explains its concepts and applications.
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  • Choose a topic related to Google Gemini.
  • Research the topic and gather information.
  • Write and publish a blog post or article that shares your knowledge.
Practice Implementing Google Gemini in Real-World Scenarios
Applying your knowledge through practice will solidify your understanding of Google Gemini's capabilities.
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  • Identify a practical problem or project
  • Design a solution using Google Gemini
  • Implement and test your solution
  • Evaluate the results and make adjustments
Practice implementing Gemini in projects
Solidify your understanding of Google Gemini by applying it to real-world scenarios.
Show steps
  • Identify a project idea where Google Gemini can be valuable.
  • Develop a plan for implementing Google Gemini in your project.
  • Implement Google Gemini and test its effectiveness.
Build a project using Google Gemini
Apply your knowledge of Google Gemini by building a project that utilizes its capabilities.
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  • Identify a problem or opportunity that can be addressed using Google Gemini.
  • Design and implement a solution using Google Gemini.
  • Test and evaluate your solution.
Participate in Google Gemini challenges
Challenge yourself and showcase your skills by participating in competitions centered around Google Gemini.
Show steps
  • Research upcoming Google Gemini competitions or hackathons.
  • Form a team or work independently to develop a project using Google Gemini.
Mentor junior learners
Sharpen your understanding of Google Gemini by teaching and assisting others.
Show steps
  • Identify opportunities to mentor junior learners in your network or online communities.
  • Prepare materials and resources to support your mentees.
Create a blog or video tutorial
Deepen your understanding of Google Gemini by creating educational content for others.
Show steps
  • Choose a specific topic or aspect of Google Gemini to focus on.
  • Develop an outline and gather relevant information.
  • Create your blog post or video tutorial.

Career center

Learners who complete First Look: Google Gemini will develop knowledge and skills that may be useful to these careers:
Data Scientist
A Data Scientist combines programming knowledge with statistical expertise to solve complex business problems. Google Gemini is a powerful tool for analyzing data, making it essential for Data Scientists to master. This course provides a comprehensive overview of Gemini, enabling you to leverage its capabilities for data analysis and problem-solving.
Machine Learning Engineer
Machine Learning Engineers design, develop, and maintain machine learning models. Gemini is a cutting-edge LLM that can enhance the efficiency and accuracy of machine learning models. This course delves into Gemini's architecture and applications, providing you with the knowledge to integrate it into your machine learning projects.
NLP Engineer
NLP Engineers specialize in developing and deploying systems that process and understand human language. Gemini is a large language model with advanced NLP capabilities. This course teaches you how to harness Gemini's NLP features to build better NLP applications.
AI Researcher
AI Researchers explore and develop new theories and techniques in artificial intelligence. Google Gemini represents a significant advancement in AI technology. This course provides insights into Gemini's underlying algorithms and research, enabling you to contribute to the field of AI.
Business Analyst
Business Analysts identify and solve business problems using data analysis and problem-solving techniques. Google Gemini can help Business Analysts gain deeper insights from data, leading to more effective solutions. This course teaches you how to apply Gemini to business analysis, giving you a competitive edge.
Product Manager
Product Managers are responsible for the development and success of products. Google Gemini can provide valuable insights into user needs and preferences. This course equips you with the knowledge to leverage Gemini for product development, enhancing your ability to create successful products.
Marketing Analyst
Marketing Analysts analyze marketing data to understand customer behavior and optimize marketing campaigns. Google Gemini can help Marketing Analysts gain deeper insights into customer demographics, preferences, and behavior. This course teaches you how to use Gemini for marketing analysis, improving your ability to develop effective marketing strategies.
Data Engineer
Data Engineers design and manage data systems that support data analysis and machine learning. Google Gemini requires a scalable and efficient data infrastructure. This course teaches you how to use Google Cloud and other tools to build data pipelines that support Gemini, enabling you to handle large datasets effectively.
Software Engineer
Software Engineers design, develop, and maintain software systems. Google Gemini is built on advanced software algorithms and architectures. This course provides a deep dive into Gemini's software architecture, enabling you to build more robust and scalable software systems.
Data Architect
Data Architects design and manage data architectures that meet the needs of an organization. Google Gemini introduces new challenges and considerations for data architecture. This course teaches you how to design data architectures that support Gemini, ensuring your organization can leverage its capabilities effectively.
Cloud Architect
Cloud Architects design and manage cloud computing solutions. Google Gemini is a cloud-based service. This course provides insights into the cloud architecture and infrastructure that supports Gemini, enabling you to design and deploy Gemini solutions effectively.
DevOps Engineer
DevOps Engineers bridge the gap between development and operations teams. Google Gemini introduces new challenges and considerations for DevOps processes. This course teaches you how to adapt DevOps practices to support Gemini, ensuring smooth and efficient deployment and maintenance of Gemini-based solutions.
IT Manager
IT Managers are responsible for the overall IT infrastructure and operations of an organization. Google Gemini introduces new technologies and considerations for IT management. This course provides insights into the impact of Gemini on IT infrastructure and operations, enabling you to make informed decisions and manage Gemini effectively.
Technical Writer
Technical Writers create and maintain documentation for technical products and systems. Google Gemini introduces new concepts and technologies. This course teaches you how to write clear and concise documentation for Gemini, enabling users to understand and utilize its capabilities effectively.
Technical Support Specialist
Technical Support Specialists provide assistance to users of technical products and systems. Google Gemini introduces new challenges and considerations for technical support. This course provides insights into the operation and troubleshooting of Gemini, enabling you to provide effective support to users.

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 First Look: Google Gemini.
Provides a good background for foundational deep learning concepts which are used by large language models such as Google Gemini.
Broadly covers the theory and practice of natural language processing, which major area of application for large language models such as Gemini. Especially helpful for those who want to understand how Gemini is used in natural language processing, as well as other areas such as computer vision.
Covers how to implement natural language processing applications in Python. While Google Gemini is not covered, it will be useful for individuals who wish to use Gemini for natural language processing, as well as those who are interested in the broader field of large language models.
Provides more practical experience in how to use deep learning frameworks such as PyTorch and Fastai. It provides a good background for those who wish to implement large language models such as Gemini.
Similar to the above book, this book provides a practical background in machine learning using Python libraries. is particularly useful for those who wish to apply large language models to their own datasets.
Provides a more mathematical background for the theory of machine learning. Useful for those who wish to learn more about the theory behind large language models, as well as for those who wish to apply machine learning algorithms to their own datasets.
Another book that provides a strong mathematical background for machine learning. Useful for those who wish to learn more about the theory behind large language models, as well as for those who wish to apply machine learning algorithms to their own datasets.
More general introduction to deep learning. Useful for those who need a broad background in deep learning theory and implementation.
Similar to the textbook by Jurafsky and Martin, this book more comprehensive look at the theory and practice of natural language processing. This textbook is especially useful for those who are interested in the application of large language models to natural language processing.

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