Generative AI APIs have revolutionized artificial intelligence, empowering developers to utilize pre-trained models for various practical and creative purposes. These APIs provide access to robust language models, enabling text generation, language translation, question answering, and artistic content creation. Integrating generative AI APIs automates content creation, enhances conversational AI, improves customer support with chatbots, assists in language translation, and generates personalized recommendations. In this learning journey, learners will delve into the world of generative AI APIs and explore their potential for practical applications. The journey is divided into three learning paths covering different generative AI aspects. The first path focuses on the fundamentals of generative AI APIs, providing a solid foundation for understanding their usage and integration. The second path dives into harnessing the capabilities of OpenAI APIs, equipping learners with advanced techniques and applications. The final path explores the capabilities of Google's generative AI APIs, with a specific focus on the Bard API, enabling learners to optimize its usage and leverage its advanced features. By the end of the journey, learners will have the knowledge and skills to unlock the full potential of generative AI APIs in their own projects and applications.
Track 1: Fundamentals of Generative AI APIs for Practical Applications
Generative artificial intelligence (AI) has taken the tech and business world by storm. It currently can create stories, text, images, summaries, essays, and much more, with sometimes nothing more than a few words to describe what you want. Unfortunately, it can also be used in ways that can be harmful, such as creating deepfakes and false information. In this course, you will discover the differences between generative AI and general AI and look at the history and future of generative AI. You will explore applications of generative AI and the ethical, safety, security, and privacy concerns associated with its use. Then you will identify common generative AI application programming interfaces (APIs) and best practices when using generative AI. Next, you will find out how to create images and text with generative AI, and you will focus on the challenges of AI integration into processes and workflows. Finally, you will learn how to integrate generative AI APIs to create tools like chatbots.
OpenAI offers an Application Programming Interface (API) that allows users to create, manipulate, and translate text using its available models and endpoints. Understanding how the API works, its limits, and how to effectively use best practices will help you get the most from the interface. In this course, you will explore OpenAI's API, generate an API key, and learn about the impact of social bias and blindness in models. Then, you will discover the ethical usage policy and safety and privacy concerns of OpenAI. Next, you will examine available models and endpoints. You will create a simple text completion, parse a response, troubleshoot common errors, and apply parameters to improve your results. Finally, you will use the language translation API to translate to and from English and identify organizational best practices when using OpenAI to handle scaling, latency, and limits.
Although OpenAI can create text, like short stories or ads, it does have some limits. With planning, however, these limitations can be worked around. OpenAI has a rich Application Programming Interface (API) for working with images, including creating images from a description and being able to manipulate just a part of an image. OpenAI can also translate text to speech and even translate spoken language. In this course, you will explore advanced text creation and manipulation concepts in OpenAI. You will work with image generation and modification using an image mask. You will discover object recognition concepts using OpenAI Contrastive Language-Image Pre-Training (CLIP). Finally, you will use the OpenAI API to convert speech to and from another language.
OpenAI's potential to increase productivity really shows when it comes to generating, completing partially provided code, or fixing already written code. Other handy features are using embeddings to measure or determine relatedness and fine-tuning a model to solve domain-specific problems. In this course, you will explore OpenAI's code generation and completion application programming interface (API). You will discover how to generate code from comments or complete partially provided code and how to use OpenAI to find libraries to solve problems or rewrite code. Next, you will focus on sentiment analysis and the tone of text and how to use embeddings for searching, clustering, recommending, and classifying. Then, you will examine OpenAI fine-tuning. Finally, you will create and fine-tune a customer-facing chatbot to handle specific scenarios.
Google Bard is a generative artificial intelligence (AI) that uses a large language model to facilitate answering questions and creating content for a wide range of topics. Understanding how the models work, its limitations, and what functionality the service provides enables anyone to optimize their usage of the service to accomplish a multitude of tasks. In this course, you will explore the Bard interface and learn to use Bard to answer questions and create content while also understanding Bard's limitations, features, and best practices. Additionally, you will explore the ethics, privacy, and security concerns that can come with using a generative AI like Bard.
Google Bard can be used to write creative content, but it also allows you to share that content, adjust content to reflect a tone, and translate text to and from English. These capabilities can be used by almost anyone in virtually any industry to expedite tasks. In this course, you will learn how to use Bard to create poems, stories, lyrics and other content. You will also learn to create summaries and outlines. Next, you will discover Bard's image object recognition and finding capabilities. Finally, you will be introduced to Bard's translation capabilities.
Google Bard is a useful tool for content creation, translation, and analysis; however, using the PaLM 2 API it is possible to integrate Bard directly into your own processes via the provided application programming interface (API) or the client libraries that are ready to go. This does require some programming and command line interface (CLI) experience but even a small amount should be sufficient to follow along. In this course you will learn about Bard's analytical capabilities, the PaLM 2 API, and how to use the API to accomplish tasks programmatically rather than through the Bard web interface. Additionally, you will explore the PaLM models, support languages and libraries, and the interfaces used for communicating with PaLM.
Python and Google Bard can be combined to create applications and programs via the PaLM 2 API. These programs can solve problems or integrate Bard into workflows or processes. In this course, you will learn to solve code problems with Bard and how to use the Python Client API library to connect and use PaLM to create applications that integrate Bard. In particular, you will explore how to programmatically check content for appropriate communications, adjust parameters to fine-tune responses, troubleshoot common problems, add security to a process, and create a simple chatbot.