Learn Google's Gemini and Anthropic's Claude API with Python from Udemy

In this course, you'll learn about both Google's Gemini and Anthropic's Claude 3 API with Python.

Fully updated for Gemini 1.5 Pro API.

Welcome to the Gemini Era. Embrace the Gemini Pro Vision API with Python and Become a Pioneer in Multimodal AI

Prepare to master Google's Gemini Pro Vision API with Python and unleash the power of Google's most capable AI family into your applications.

By the end of this journey, you'll master the Gemini Pro API (1.5 included) and become a pro in LLM prompt engineering, equipped to create groundbreaking and intelligent Python applications using the Gemini API.

Get ready to join the forefront of multimodal AI innovation as we constantly update this course with the latest advancements, equipping you with the skills to thrive in the future.

This course on Google's Gemini Pro Vision API with Python covers everything you need to know about the Gemini family of models and about effective prompt engineering for LLMs.

You'll also learn how to use the Python API for the Anthropic's Claude 3 family of models: Opus, Sonnet and Haiku.

Become a pioneer shaping the technological landscape and reap the benefits of being an early adopter.

In today's world, AI is the key to unlock unprecedented productivity.

Embrace the Gemini Pro Vision API with Python, Google AI Studio, and advanced prompting tactics to stay ahead of the curve.

In this course, you'll learn by doing, with practical projects that will guide you in applying what you learn.

You'll also discover the best practices and tips for effective prompting for LLMs, such as using few examples, finding relevant context information, and exploring different prompt engineering techniques.

By the end of this course, you'll be able to:

Learn how to use Google's Gemini Pro [Vision] API with Python, the most advanced and versatile AI tool from Google
Create freeform and dynamic prompts with Gemini Pro Vision in Google AI Studio
Unlock the Power of Gemini 1.5 Pro API
Use the File API for prompting with media files (audio, video and more)
Generate text from text inputs using Gemini Pro API and Python
Stream model responses
Generate text from image and text inputs using Gemini Pro Vision API and Python
Control how the model generates responses using Gemini API generation parameters: temperature, top_k, top_p, stop sequences and more
Build custom chat conversational agents
Master the art of prompt engineering for LLMs and create effective and natural language queries for any task
You'll learn how to create web interfaces (front-ends) for your LLM apps using Streamlit
Learn how to use Anthropic's Claude 3 API with Python: API setup, generating text, streaming, Claude 3 vision capabilities, and more
Learn how to use Jupyter AI efficiently

This course is suitable for anyone who wants to learn how to use the Gemini Pro Vision API, Google AI Studio, Claude 3 API, and how to leverage the power of multimodal AI for various applications.

If you are ready to take your skills to the next level and master one of the most cutting-edge technologies in AI, enroll in this course today and start your journey to multimodal AI mastery.

What's inside

Learning objectives

Gain a deep understanding of the google's gemini and anthropic's claude 3 api with python
Install python sdk for gemini and claude 3 api and authenticate to gemini
Create freeform prompts with gemini pro vision in google ai studio
Use variables and parameters in gemini prompts in google ai studio
Generate text from text inputs using gemini pro api and python
Stream model responses from gemini and claude
Generate text from image and text inputs using gemini pro vision and claude 3 api and python
Control how the model generates responses using gemini api generation parameters: temperature, top_k, top_p, stop sequences and more

Build custom chat conversational agents
Master prompt-engineering techniques for llms
You'll learn how to create web interfaces (front-ends) for you llm apps using streamlit
Streamlit: main concepts, widgets, session state, callbacks
Learn how to use jupyter ai efficiently
Show more
Show less

Gain a deep understanding of the google's gemini and anthropic's claude 3 api with python
Install python sdk for gemini and claude 3 api and authenticate to gemini
Create freeform prompts with gemini pro vision in google ai studio
Use variables and parameters in gemini prompts in google ai studio
Generate text from text inputs using gemini pro api and python
Stream model responses from gemini and claude
Generate text from image and text inputs using gemini pro vision and claude 3 api and python
Control how the model generates responses using gemini api generation parameters: temperature, top_k, top_p, stop sequences and more
Build custom chat conversational agents
Master prompt-engineering techniques for llms
You'll learn how to create web interfaces (front-ends) for you llm apps using streamlit
Streamlit: main concepts, widgets, session state, callbacks
Learn how to use jupyter ai efficiently
Show more
Show less

Syllabus

Getting Started

How to Get the Most Out of This Course

Python IDEs For This Course

Setting Up the Environment: Jupyter Notebook

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Covers Gemini 1.5 Pro API, which is Google's most advanced AI model, providing learners with access to cutting-edge technology

Teaches prompt engineering techniques, which are essential for effectively using LLMs and creating natural language queries for various tasks

Explores Streamlit, which allows learners to create web interfaces for their LLM applications, enhancing their ability to deploy and share their projects

Includes coverage of Anthropic's Claude 3 API, giving learners exposure to multiple state-of-the-art language models and expanding their skill set

Requires learners to obtain API keys for Gemini and Claude 3, which may involve a separate registration process and potential costs depending on usage

Uses Jupyter AI, which may require learners to set up and configure their Jupyter Notebook environment, potentially adding a layer of complexity for beginners

Reviews summary

Learn gemini and claude apis with python

According to learners, this course provides a strong foundation in using both Google's Gemini and Anthropic's Claude 3 APIs with Python. Many find the hands-on coding examples and projects to be particularly valuable for practical application. Reviewers appreciate the inclusion of recent model updates like Gemini 1.5 and Claude 3. The course covers essential topics such as API setup, generating text and images, streaming responses, and various prompt engineering techniques. Some note that having a basic understanding of Python is helpful, though resources are provided. Overall, the feedback is largely positive, highlighting its relevance for those looking to build AI applications.

Helpful to have some Python background.

"While an appendix is provided, learners will benefit most if they are already somewhat familiar with Python."

"The pace was good, but basic Python comfort is definitely a plus."

"I'd recommend brushing up on Python fundamentals if you're completely new before starting."

Teaches valuable prompting tactics.

"The section on prompt engineering was very insightful and provided concrete tactics I could apply immediately."

"Learning how to structure prompts effectively for both models was a key takeaway."

"I gained a much better understanding of how to get the desired output using the prompt engineering lessons."

Uses recent Gemini 1.5 and Claude 3.

"It's great that the course is updated to include Gemini 1.5 Pro and the latest Claude 3 models. It feels current."

"The content on Gemini 1.5 features like the File API was very timely and useful."

"Knowing I was learning with the most recent versions gave me confidence in the course's relevance."

Includes hands-on code for application.

"The code examples were clear and easy to follow, which made learning the APIs much smoother."

"Building the conversational agent project helped solidify my understanding significantly."

"I found the practical implementation sections invaluable for seeing how the APIs work in real code."

Covers both Gemini and Claude 3 APIs.

"I appreciated the dual focus on both Gemini and Claude. It gave me a broader understanding of the current LLM landscape."

"Having both APIs covered in one place was really convenient. It helped me compare and contrast their features."

"The course delivered well on its promise to teach both Gemini and Claude APIs with Python."

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 Learn Google's Gemini and Anthropic's Claude API with Python with these activities:

Review Python Fundamentals

Show steps

Strengthen your Python foundation to better understand the API interactions and code examples used throughout the course.

Browse courses on Python Basics

Show steps

Review basic data types and operators.
Practice writing simple functions and loops.
Familiarize yourself with list comprehensions.

Read 'Effective Python' by Brett Slatkin

Show steps

Improve your Python coding skills to better implement and customize the Gemini and Claude API integrations.

View Effective Python: 125 Specific Ways to Write... on Amazon

Show steps

Read the first few chapters covering basic Python idioms.
Focus on sections related to functions and classes.
Try implementing some of the examples in the book.

Practice Prompt Engineering

Show steps

Refine your prompt engineering skills to get the most out of the Gemini and Claude APIs.

Show steps

Experiment with different prompting techniques.
Analyze the responses and iterate on your prompts.
Try few-shot prompting with different examples.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Document Your Prompt Engineering Experiments

Show steps

Solidify your understanding of prompt engineering by documenting your experiments and findings.

Show steps

Create a document to record your prompts and results.
Analyze the effectiveness of different prompts.
Share your findings with other students.

Build a Simple Q&A App with Gemini or Claude

Show steps

Apply your knowledge by building a practical application that uses the Gemini or Claude API to answer questions.

Show steps

Choose either Gemini or Claude API for your project.
Design the user interface for your Q&A app.
Implement the API calls to get answers from the model.
Test and refine your application.

Create a Streamlit Web App for your LLM project

Show steps

Enhance your project by creating a web interface using Streamlit, allowing others to easily interact with your LLM application.

Show steps

Design the layout of your Streamlit app.
Implement widgets for user input and output.
Integrate your LLM project with the Streamlit interface.
Deploy your Streamlit app for others to use.

Read 'Generative AI with Python and TensorFlow 2'

Show steps

Gain a deeper understanding of the underlying principles of generative AI to better utilize the Gemini and Claude APIs.

View Generative AI with Python and TensorFlow 2:... on Amazon

Show steps

Read the chapters on generative models and techniques.
Focus on the sections related to language models.
Experiment with the code examples provided in the book.

Career center

Learners who complete Learn Google's Gemini and Anthropic's Claude API with Python will develop knowledge and skills that may be useful to these careers:

Prompt Engineer

A Prompt Engineer crafts effective prompts for large language models (LLMs). This course is ideally suited for those looking to become a prompt engineer as it teaches how to effectively use Google's Gemini API as well as Anthropic's Claude API. You will learn techniques on how to design prompts that generate desirable responses, including using few examples, finding relevant context, and exploring different strategies. This practical, hands-on experience is essential to a prompt engineer. Additionally, the course covers the use of parameters, text generation, and creating chat agents, all of which are critical tasks.

See salaries and explore the career path for Prompt Engineer

Chatbot Developer

A Chatbot Developer creates conversational AI systems, which are a key focus of this course, that teaches how to use the Gemini and Claude APIs to build custom chat conversational agents. This job requires skills in prompt engineering, which is also covered in detail. This includes how to generate text, stream model responses, and control generation parameters. The practical projects in the course give a Chatbot Developer hands-on experience in building and testing conversational AI. Learning Streamlit for web interfaces is also valuable for deploying functional chatbots.

See salaries and explore the career path for Chatbot Developer

AI Application Developer

An AI Application Developer designs and builds applications that use AI. This course in Gemini and Claude APIs will help build a foundation for this role. The course teaches how to use the Gemini Pro Vision API with Python to manage text and multimodal inputs, and how to build custom chat agents. This is directly relevant to building AI-enabled applications. The course also teaches how to create web interfaces using Streamlit, which is a crucial skill for deploying AI-powered applications. The lessons on prompt engineering enable an AI application developer to fine-tune their application for optimal performance.

See salaries and explore the career path for AI Application Developer

Artificial Intelligence Engineer

An Artificial Intelligence Engineer develops and implements AI models and applications. This role involves using tools like Google's Gemini and Anthropic's Claude APIs, with skills in prompt engineering. This course will help you learn how to integrate large language models (LLMs) into various applications by teaching the core concepts of using Gemini and Claude APIs with Python. You'll also learn how to build custom chat agents and web interfaces for AI applications. Understanding how to use the Gemini Pro Vision API with Python, as covered in this course, is directly applicable to building multimodal AI applications. By mastering prompt engineering, an AI Engineer can tailor their models to perform optimally.

See salaries and explore the career path for Artificial Intelligence Engineer

Machine Learning Engineer

A Machine Learning Engineer builds, trains, and deploys machine learning models. This role requires familiarity with a variety of models such as those offered by Google's Gemini and Anthropic's Claude. This course teaches how to utilize the Gemini and Claude APIs via Python, along with techniques for prompt engineering. This is invaluable to a Machine Learning Engineer. The course's focus on practical projects would enable one to build experience integrating LLMs into a range of applications. The exploration of the Gemini Pro Vision API and multimodal AI is directly applicable to a Machine Learning Engineer who needs to work with complex data types.

See salaries and explore the career path for Machine Learning Engineer

Natural Language Processing Engineer

A Natural Language Processing Engineer designs systems that allow machines to understand and process human language. This course provides a solid foundation through its exploration of Google's Gemini API as well as Anthropic's Claude API. These tools are critical for many NLP tasks. This role requires a strong understanding of prompt engineering, which this course covers in detail. Moreover, the ability to generate text, stream model responses, and build conversational agents is highly relevant. Learning to use the Gemini Pro Vision API with Python is useful for any NLP Engineer who works with multimodal inputs.

See salaries and explore the career path for Natural Language Processing Engineer

Computational Linguist

A Computational Linguist develops computational models of language. This role benefits from a strong understanding of natural language processing, which this course helps with by teaching the Gemini and Claude APIs. These APIs are useful in exploring how large language models process and generate text. This course provides practical instruction on how to use these tools with Python, which directly supports the needs of a computational linguist. By learning prompt engineering techniques, you'll gain experience in controlling the models' behavior, which is invaluable in the field.

See salaries and explore the career path for Computational Linguist

Computer Vision Engineer

A Computer Vision Engineer develops systems that enable computers to 'see' and interpret images and videos. This role is closely related to the technologies explored in this course. The Gemini Pro Vision API provides tools for managing multimodal data, including image and video. The course teaches how to use this API via Python while also providing practical experience with prompt engineering. This is critical to extracting accurate information. Also, the course focus on media handling could be valuable to a Computer Vision Engineer.

See salaries and explore the career path for Computer Vision Engineer

Robotics Engineer

A Robotics Engineer designs, builds, and programs robots. This role may involve integrating computer vision, natural language processing, and other forms of AI. This course may be useful for a robotics engineer. It provides a foundational understanding of building multimodal AI systems using the Gemini Pro Vision API with Python. This is in addition to learning how to manage text, audio, and image data through effective prompt engineering. Knowledge of Gemini and Claude APIs for text generation is also beneficial when developing AI components.

See salaries and explore the career path for Robotics Engineer

Research Scientist

A Research Scientist conducts studies and experiments to advance knowledge. This role often requires a high degree of proficiency with advanced technologies such as large language models. The course will be helpful as it provides an understanding of both the Gemini and Claude APIs. It also teaches the implementation of these models via Python. The skill of prompt engineering is particularly useful for experimenting with different model inputs and use cases. This course could help a research scientist stay current with the most recent innovations in AI.

See salaries and explore the career path for Research Scientist

Data Scientist

A Data Scientist analyzes large datasets to extract meaningful insights. While this role is broad, the skills developed in this course on Google's Gemini API and Anthropic's Claude API can be very beneficial, especially to those working with unstructured data. This course provides the context and technical know-how to perform AI-driven data analysis, using techniques for prompt engineering, generating text, and the processing of multimodal inputs. The knowledge of using APIs and Python for model interaction is helpful to any data scientist interested in integrating generative AI features into their work.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst examines data to identify trends and insights. This course may be helpful because it teaches how to manage text, and other media types via the Gemini Pro Vision API and Claude APIs in Python. This could provide a data analyst with more tools for exploring complicated data sets. Furthermore, a data analyst may find the ability to create custom chat agents and learn prompt engineering techniques to be a way to efficiently explore unstructured data sets. The use of Streamlit to display data could also be valuable for a Data Analyst.

See salaries and explore the career path for Data Analyst

Software Developer

A Software Developer designs and implements software applications. This course may be useful to a Software Developer, especially one who is working with or plans to integrate AI into software. Learning how to use Google's Gemini API and Anthropic's Claude API can allow a developer to experiment with a variety of AI models. You can use Python to integrate these models into software. The course also touches on how to use Streamlit, useful for building web-based front-ends. Understanding advanced techniques like prompt engineering are helpful in any context.

See salaries and explore the career path for Software Developer

Technical Writer

A Technical Writer creates documentation for technical products and services. This course may be useful for Technical Writers who need better understanding of AI models. The course provides practical techniques using the Gemini and Claude APIs, including generating text and handling multimodal inputs. This knowledge may help a technical writer create documentation about prompt engineering best practices, or to better explain the use of Gemini and Claude AI models. The course’s focus on generating text and using APIs is directly applicable to AI technical writing.

See salaries and explore the career path for Technical Writer

AI Consultant

An AI Consultant advises organizations on how to use AI technologies to meet business goals. Understanding the technical aspects of AI is crucial for this role. This course may be useful by introducing the Gemini and Claude APIs using Python. Prompt engineering, text generation, and building chat agents is practical experience that could help inform your consultations. The course also touches on Streamlit for web interfaces, which helps showcase AI applications. Knowledge of the Gemini Pro Vision API could be useful in recommending AI solutions.

See salaries and explore the career path for AI Consultant

Reading list

We've selected two 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 Learn Google's Gemini and Anthropic's Claude API with Python.

Effective Python

Save

Provides practical advice on writing clean, efficient, and maintainable Python code. It covers a wide range of topics, including best practices for using Python's built-in features, writing concurrent code, and debugging. While not directly focused on AI APIs, it will improve your overall Python skills, making it easier to work with the Gemini and Claude APIs. It is valuable as additional reading.

Effective Python: 125 Specific Ways to Write Better...

Kindle Edition

Generative AI with Python and TensorFlow 2

Save

Provides a comprehensive guide to generative AI techniques using Python and TensorFlow 2. While the course focuses on Gemini and Claude, understanding the underlying principles of generative AI can enhance your ability to effectively use these APIs. This book is more valuable as additional reading than as a current reference. It can help you understand the broader context of LLMs.

Generative AI with Python and TensorFlow 2: Create...

Paperback

Generative AI with Python and TensorFlow 2: Create...

Kindle Edition

Learn Google's Gemini and Anthropic's Claude API with Python

What's inside

Learning objectives

Syllabus

Traffic lights

Save this course

Reviews summary

Learn gemini and claude apis with python

Activities

Career center

Reading list

Share

Similar courses