Smart Workflow Automation: AI & Machine Learning with Make

• Experience using Make for workflow automation
• Understanding of APIs and webhooks
• Basic knowledge of AI/ML concepts and models

Audience

• AI/ML engineers
• Data scientists
• Tech innovators

AI and machine learning are transforming automation by enabling predictive, intelligent workflows. By integrating AI/ML services into Make, users can automate decision-making, extract insights from data, and create dynamic, self-improving workflows.

This instructor-led, live training (online or onsite) is aimed at advanced-level AI/ML engineers, data scientists, and tech innovators who wish to integrate AI capabilities into Make workflows to optimize and automate processes.

By the end of this training, participants will be able to:

• Understand AI and machine learning capabilities in automation.
• Integrate AI/ML models into Make workflows using APIs.
• Implement sentiment analysis, predictive modeling, and data-driven decision-making.
• Optimize and scale AI-driven automation workflows.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to AI/ML in Workflow Automation

• Overview of AI-driven automation
• Understanding AI/ML models for workflows
• Introduction to Make’s API and automation capabilities

Connecting AI/ML APIs to Make

• Using AI/ML services (OpenAI, Google Cloud AI, Hugging Face)
• Making API calls to AI models for automation
• Handling API authentication and security

Sentiment Analysis and Text Processing

• Extracting insights from customer feedback
• Using NLP models for text classification
• Automating response generation based on sentiment

Predictive Modeling and Decision Automation

• Using ML models for predictive analytics
• Automating decision-making based on AI predictions
• Integrating forecasting models into workflows

Automating Image and Video Processing

• Using AI for image recognition and classification
• Applying object detection in automation
• Automating content moderation and tagging

Optimizing AI-Driven Automation Workflows

• Handling errors and improving reliability
• Scaling AI integrations in Make
• Monitoring and maintaining AI-driven workflows

Testing and Debugging AI Integrations

• Using Postman for API testing
• Debugging AI/ML model responses
• Ensuring accuracy and consistency in automation

Summary and Next Steps

• Key takeaways from the course
• Resources for further learning
• Q&A and closing remarks