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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.
Testimonials (1)
real life examples