Data Analytics in Automation

Data Analytics in Automation focuses on equipping participants with the essential skills to analyze and interpret data within automated systems. The course emphasizes practical applications, utilizing project-based learning to ensure that participants can apply theoretical concepts to real-world scenarios. By engaging in hands-on projects, attendees will develop a robust understanding of data analytics tools and methodologies tailored for industrial automation.
Participants will explore a variety of analytical techniques, including statistical analysis, machine learning, and data visualization, all within the context of automation systems. The course culminates in a final project where learners will implement a data analytics solution to optimize an automated process, fostering both technical proficiency and innovative thinking. Publishing results in Cademix Magazine is encouraged, providing a platform for participants to share their insights and achievements with a broader audience.
Introduction to Data Analytics in Automation
Overview of Industrial Automation Systems
Data Collection and Management Techniques
Statistical Analysis for Automation
Machine Learning Fundamentals in Automation
Data Visualization Tools and Techniques
Predictive Analytics and Forecasting
Real-time Data Processing and Analysis
Case Studies in Automation Analytics
Final Project: Implementing a Data Analytics Solution

To develop proficiency in data analytics techniques applicable to industrial automation and to complete a capstone project demonstrating these skills.

Graduates, job seekers, business professionals, and optionally researchers or consultants.

A foundational understanding of data analysis and automation principles, along with basic programming skills in Python or R.