Final Exam: Leveraging Generative AI APIs

WHAT YOU WILL LEARN

• 

  Apply best practices when using generative ai
  

  identify the roots, emerging trends, and advancements of generative ai
  

  describe how generative ai can have a real-world impact on many industries
  

  navigate the ethical concerns and implications that generative ai can create, such as bias and misuse
  

  use generative ais to create text, short stories, ads, or summaries
  

  identify and describe multiple common generative ai apis and their features
  

  work with generative ais to generate images by providing textual descriptions
  

  describe how generative ais can be embedded into business processes or workflows
  

  parse a response to get results and troubleshoot likely and common errors
  

  how gpt artificial intelligence (ai) works and outline the capabilities and features of the openai api
  

  apply parameters, like temperature, to acquire different or better results
  

  describe how tokens and models affect the pricing of openai and the soft and hard limits for usage of the models
  

  describe the different api endpoints and their associated models
  

  create a simple text completion using a model and endpoint
  

  identify organizational best practices when using openai to handle scaling, latency, and limits
  

  use the translation api to translate to and from english
  

  use advanced text generation features to do more complex completions and handle longer input situations
  

  translate audio speech to and from english with openai
  

  outline how to use openai prompts to help improve audio and speech translation
  

  describe the speech recognition features and capabilities in openai
  

  use openai to generate an image based on a textual description
  

  outline the process of using openai contrastive language-image pre-training (clip) for object recognition
  

  describe the process of converting text into speech with openai and adjusting parameters to control the output
  

  describe how to translate audio speech from one language to another using speech translation in openai
  

  use fine-tuning to create a custom classification feature
  

  create a simple customer-facing chatbot that can answer questions
  

  work with the sentiment analysis api to get feedback about the tone of text
  

  describe how embeddings can be used for searching, clustering, recommending, and classifying by measuring relatedness
  

  use embeddings to handle relatedness in terms of clustering and making recommendations
  

  create similarity measurements and apply classifications to text
• 

  use fine-tuning to customize a chatbot to handle specific scenarios or questions
  

  outline what bard is, how it can be used, its history, and its significance to artificial intelligence (ai)
  

  use bard to generate text content like summaries and descriptions of events
  

  distinguish the features of bard from other conversation ai offerings like openai's chatgpt
  

  identify the privacy and ethical concerns of using a generative ai including understanding bias, inaccuracies, and hallucinations
  

  work with the bard web interface, including the components, sidebar, and chat interface
  

  recognize the requirements to create a google account to use bard and the acceptable usage of bard
  

  work with bard to ask questions, get feedback, modify responses, and leverage feedback and drafts
  

  use the bard web interface with images of animals, places, or objects and have it find an appropriate image
  

  use the bard web interface to export bard code responses to sites like colab and replit
  

  use the bard api to create a story, poem, and song lyric
  

  use the bard api to integrate a tone that will influence the output response from bard
  

  use the bard api to create an outline for a potential course and create summaries of content
  

  use the bard api to translate foreign languages passages to english
  

  identify the languages and capabilities that bard provides for translating languages to and from english
  

  use the bard api to translate english into other languages and leverage drafts to get a better translation
  

  list the features and capabilities of bard's analytics
  

  use bard to analyze data and get suggestions based on the analysis
  

  control the output formatting of data in responses
  

  outline the pathways language model (palm) and how it is used to power bard
  

  identify the features of the palm api and how it can be used
  

  create a palm api key and verify it works by making a simple request
  

  recognize the coding languages supported by the palm api and client libraries that can be used to facilitate development
  

  troubleshoot and diagnose issues that can cause problems when using bard or the api
  

  add comments to analyze what code is doing and have bard fix bugs
  

  outline the use of the python client application programming interface (api) library for accessing and using palm
  

  apply parameters like temperature, candidate count, topp, and topk to affect output
  

  use optimization techniques to reduce resource usage and improve performance
  

  outline how safety filters affect responses and can be used to block inappropriate communications
  

  use the safety filters to check content for explicit material