- Thread Starter
- #1
Published 7/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 22m | Size: 758 MB
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 22m | Size: 758 MB
Master Predictive Maintenance with Python: AI, Sensors, Reliability Engineering & Industrial IoT Techniques
What you'll learn
Design and simulate predictive maintenance systems using Python, machine learning models, and synthetic industrial data for real-time insights.
Deploy interactive Grafana dashboards to visualize equipment health, predict failures, and support data-driven industrial decision-making.
Integrate condition monitoring and sensor data into ML pipelines to detect anomalies, reduce downtime, and improve asset reliability.
Validate PdM performance with A/B testing and KPIs, and build scalable CMMS-compatible solutions for manufacturing and industrial settings.
Requirements
Basic understanding of Python programming (variables, functions, loops). Interest in industrial maintenance, reliability, or data analytics. No prior experience with Grafana or predictive maintenance required. A computer with internet access to install Python libraries and Grafana.
Description
Unlock the power of Predictive Maintenance (PdM) with this hands-on, industry-relevant training designed for engineers, analysts, and professionals looking to transform maintenance strategies using Python, Artificial Intelligence, and Industrial IoT. This course walks you through the complete deployment of PdM systems-from theoretical foundations to full simulations and real-world case studies.You'll begin by exploring the fundamentals of Reliability Engineering, including failure modes, life data analysis, and reliability metrics. Then, dive into the most important PdM techniques, including vibration analysis, thermal imaging, oil analysis, and advanced condition monitoring with sensors. Learn how to extract meaningful insights from sensor data, build predictive models using Machine Learning algorithms, and create dashboards using Python and Grafana.Through real-life examples and step-by-step projects, you'll gain confidence in building scalable, end-to-end PdM solutions for smart factories and digital transformation initiatives. Whether you're working in manufacturing, aerospace, energy, automotive, or industrial maintenance, this course equips you with essential skills to reduce downtime, improve equipment performance, and drive cost-effective asset management.No prior experience with PdM is required-only basic Python knowledge and a willingness to learn. Join today and elevate your career in reliability, maintenance, and AI-powered industry 4.0 No prior experience with PdM is required-only basic Python knowledge and a willingness to learn. Join today and elevate your career in reliability, maintenance, and AI-powered industry 4.0
Who this course is for
Maintenance engineers and industrial technicians aiming to implement predictive strategies. Data analysts and Python developers seeking to apply AI in industrial environments. Reliability and asset management professionals focused on optimizing equipment uptime. Engineering students and tech enthusiasts interested in Industry 4.0 and smart maintenance.
Homepage:
Screenshots
Download link
rapidgator.net:
You must reply in thread to view hidden text.
nitroflare.com:
You must reply in thread to view hidden text.
