Course Outline

Introduction to DeepSeek APIs

  • Overview of DeepSeek APIs and their capabilities
  • Understanding API endpoints and authentication
  • Comparing DeepSeek APIs with other AI model APIs

Setting Up the Development Environment

  • Installing required tools and libraries
  • Setting up API keys and authentication methods
  • Making test API calls using Postman or cURL

Integrating DeepSeek APIs into Applications

  • Calling DeepSeek APIs from Python and JavaScript
  • Handling API responses and error management
  • Implementing AI-powered features in web and mobile apps

Building AI Chatbots with DeepSeek APIs

  • Designing chatbot workflows and user interactions
  • Implementing real-time conversational AI
  • Enhancing chatbot responses with context awareness

AI-Powered Automation and Workflows

  • Automating repetitive tasks using DeepSeek APIs
  • Integrating AI with existing enterprise workflows
  • Case studies of AI-powered automation

Optimizing API Performance

  • Managing API rate limits and optimizing API calls
  • Implementing caching and response handling strategies
  • Ensuring security and compliance in API usage

Deploying and Scaling AI Applications

  • Deploying AI applications in cloud environments
  • Scaling AI applications for high traffic
  • Monitoring and maintaining AI-driven applications

Summary and Next Steps

Requirements

  • Experience with API integration
  • Proficiency in a programming language (eg, Python, JavaScript)
  • Basic understanding of machine learning concepts

Audience

  • Developers building AI-powered applications
  • Software engineers integrating AI models into workflows
  • Data scientists leveraging DeepSeek APIs for automation
 14 Hours

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