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 Duration 14 hours

Course Outline

Foundations of AI/ML in Workflow Automation

  • An overview of automation driven by AI.
  • Understanding AI/ML models specifically for workflow contexts.
  • Introduction to Make’s API landscape and automation features.

Linking AI/ML APIs with Make

  • Leveraging AI/ML services such as OpenAI, Google Cloud AI, and Hugging Face.
  • Executing API calls to AI models to drive automation.
  • Managing API authentication and security protocols.

Sentiment Analysis and Text Processing

  • Extracting actionable insights from customer feedback.
  • Utilizing NLP models for accurate text classification.
  • Automating the generation of responses based on detected sentiment.

Predictive Modeling and Decision Automation

  • Applying ML models for predictive analytics.
  • Automating decisions informed by AI predictions.
  • Embedding forecasting models directly into workflows.

Image and Video Processing Automation

  • Employing AI for image recognition and classification tasks.
  • Implementing object detection within automated processes.
  • Automating content moderation and tagging operations.

Refining AI-Driven Automation Workflows

  • Managing errors and enhancing system reliability.
  • Scaling AI integrations within Make.
  • Continuous monitoring and maintenance of AI-powered workflows.

Testing and Debugging AI Integrations

  • Utilizing Postman for comprehensive API testing.
  • Troubleshooting responses from AI/ML models.
  • Ensuring precision and consistency across automation systems.

Recap and Future Directions

  • Key insights gained from the course.
  • Curated resources for continued learning.
  • Q&A session and concluding remarks.

Requirements

  • Proficiency in utilizing Make for workflow automation.
  • Solid comprehension of APIs and webhooks.
  • Fundamental understanding of AI/ML concepts and models.

Target Audience

  • AI/ML engineers.
  • Data scientists.
  • Technology innovators.

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