Professional Development Courses

Gain a practical understanding of how AI and machine learning work—and how to apply them effectively in real-world business and engineering contexts. This course demystifies core concepts like supervised learning, model training, and data preparation so you can make informed decisions and lead AI-driven initiatives.

An updated analytics course for technical leaders, focused on practical tools, Excel-based analysis, and data-driven decision-making.

Master the principles of precision and predictive maintenance (PdM) to optimize equipment reliability, reduce downtime, and cut maintenance costs. This course provides proven strategies and tools to help you improve product quality, anticipate equipment failures, and sustain long-term operational efficiency. Our expert instructor will help you understand which PdM diagnostic technologies are best for your plant.

Unlock the power of statistically designed experiments to identify key process variables, reduce variation, and optimize performance. This self-paced course introduces factorial and fractional factorial designs, equipping participants with practical tools to drive quality improvement in industrial settings.

Advance your skills in Design of Experiments (DOE) by learning how to apply full and fractional factorial designs using Minitab. This hands-on course empowers engineers to optimize processes and make data-driven decisions through structured experimentation.

Learn to build powerful AI chatbots without needing to write code. This course empowers technical professionals to create, deploy, and optimize generative AI systems using Azure AI’s no-code tools.

This course provides water and wastewater professionals with practical knowledge and skills realted to how AI is currently being used in the Water/Wastewater field be used and how it can drive smarter, more efficient, and more resilient design and operations. The course helps professionals understand current implementation, the opportunities and the real-world requirements for successful adoption. Participants learn how to evaluate AI use cases, assess data and system readiness, and make informed decisions about implementation, governance, legal considerations, and long-term value.

Learn to identify, evaluate, and apply AI solutions to engineering challenges, focusing on reliability, real-world use, and innovation in industrial environments.

Learn AI strategy and governance frameworks to address ethical, legal, and operational challenges while aligning AI with organizational and societal values.

Unlock the power of data to drive smarter decisions in engineering and industry. This hands-on course introduces engineers and technical professionals to the tools and methods needed to turn raw data into actionable insights. Using Python, participants will master data preparation, visualization, and advanced analytics techniques such as classification, clustering, and pattern mining. Building on this foundation, the course explores predictive modeling, anomaly detection, deep learning, failure event modeling, and time series forecasting. Designed with real-world applications in mind, the course emphasizes solving practical challenges in manufacturing, reliability, and quality control. Through interactive exercises and guided examples, participants will gain not only technical proficiency but also the confidence to apply analytics for improved performance, efficiency, and innovation in their organizations.