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Training: Working with the OpenAI API

Level

Intermediate

Duration

24h / 3 days

Date

Individually arranged

Price

Individually arranged

Training: Working with the OpenAI API

The “Working with the OpenAI API” training is an intensive, hands-on course designed to help you quickly and effectively leverage artificial intelligence in business and IT projects. Participants will learn how to use the OpenAI API for text generation, data analysis, image and audio processing, as well as for building intelligent applications and process automation. The program combines theory with practice, enabling the design of effective prompts, integration of language models into applications, and optimization of costs and resources. This training equips you with real skills that can be applied immediately in programming, analytics, or project work – enhancing team efficiency and customer experience. It is ideal for anyone looking to apply AI to automation, innovative solutions, and business decision support.

What will you learn?

  • Effectively use the OpenAI API for text, image, and audio generation and processing
  • Create effective prompts and complex interactions with AI models tailored to application needs
  • Design and program intelligent components and AI-based automations
  • Optimize API resource usage to minimize costs and maximize efficiency
  • Understand the principles of the latest language and multimodal models
  • Implement and integrate AI solutions in web applications and automation workflows
Who is this training for?
  • logo infoshare Software developers and engineers who want to integrate AI into their applications
  • logo infoshare Analysts and AI specialists seeking practical skills in working with OpenAI models
  • logo infoshare IT managers, DevOps/DevSecOps team leaders and professionals responsible for business process automation
  • logo infoshare Anyone interested in prompt engineering and managing AI context effectively

Training Program

  1. Day 1: Introduction to OpenAI API and Language Model Basics

  1. Module 1: Introduction to AI and Large Language Models (LLMs)

  • What is AI and Machine Learning (ML)
  • Core concepts: models, training, data, inference
  • Types of AI: supervised, unsupervised, reinforcement learning
  • What are LLMs, how they work, and how they differ from traditional NLP algorithms
  • Example use cases: chatbots, content generation, text analysis, translation, process automation
  • Ethics and risks in AI: bias, data security, responsible usage

  1. Module 2: Architecture and Capabilities of the OpenAI API

  • Overview of the OpenAI platform and available models (GPT-3, GPT-4, Codex, DALL·E, Whisper)
  • API types and typical applications: text generation, completion, classification, NLP tasks
  • How the OpenAI API works – architecture and mechanisms
  • Limits, tokens, and cost management

  1. Module 3: The Art of Prompt Engineering

  • What prompts are and how they influence model output
  • Writing effective prompts – strategies and examples
  • Managing interaction length and context
  • Hands-on exercises: building simple and complex prompts

  1. Day 2: Integration and Practical Use of the OpenAI API

  1. Module 4: Programming with the OpenAI API

  • Basics of API calls in popular languages (Python, JavaScript)
  • Tools and libraries supporting integration
  • REST API overview, handling responses and errors
  • Hands-on workshop: building simple apps and bots

  1. Module 5: Advanced Techniques and Optimization

  • Cost optimization strategies: prompt length control, caching, batching
  • Testing and scaling AI solutions in production environments
  • Managing multiple contexts and long conversations
  • Secure API usage: risk analysis and safeguards
  • Project examples: chatbots, content generators, recommendation systems

  1. Day 3: Extended Capabilities and Use Cases

  1. Module 6: Multimedia Models (DALL·E, Whisper)

  • Text-to-image generation with DALL·E – practical examples
  • Speech recognition and transcription with Whisper
  • Multimodal integration in applications – workshop

  1. Module 7: Building Intelligent Assistants and Automation

  • Designing conversational applications
  • Session management, personalization, and context tracking
  • Data storage and state management for AI systems
  • Monitoring, debugging, and scaling AI applications
  • Business case scenarios and final practical project

Contact us

we will organize training for you tailored to your needs

Przemysław Wołosz

Key Account Manager

przemyslaw.wolosz@infoShareAcademy.com

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