Learn to design and deploy intelligent chatbots using Microsoft Azure’s AI tools—no computer-science degree required. In this hands-on course, you’ll move from generative-AI fundamentals and prompt engineering through Retrieval-Augmented Generation (RAG), prompt flows, and multi-agent systems. By building real applications, you’ll gain practical experience with deployment, testing, and optimization while addressing security, privacy, and content-safety challenges common to modern engineering environments.

• Design and develop a fully functional Generative AI-based RAG chatbot application that can be personalized to the user. 
• Implement and optimize Retrieval-Augmented Generation (RAG) to enhance chatbot responses. 
• Integrate memory management systems to improve context retention in chatbot interactions. 
• Utilize agents to perform specialized tasks within the chatbot framework. 
• Demonstrate the ability to deploy, test, and maintain chatbot applications in a production environment. 

• Engineers, scientists, and “citizen developers” ready to create functional AI assistants without deep coding experience
• Data, IT, and systems professionals looking for applied, low-code experience with Azure AI Studio and Copilot
• Product managers and technical leads seeking to embed AI-driven chatbots and prompt flows into engineering or manufacturing workflows
• Organizational leaders and innovators who need to evaluate AI capabilities, limitations, and safe deployment strategies within technical teams

The course will utilize Microsoft Azure infrastructure for activities.

Anthony Orzechowski

Tony instructs courses in Applied Analytics in several master's programs at the University of Wisconsin – Madison and Northwestern University.  These course focus on providing students with the immediate ability to lead improvement and innovation in their careers through analytics.  

Tony is the recently retired Director of R&D Data Analytics at Abbott Laboratories, where he oversaw a broad spectrum of analytics responsibilities, ranging from statistics, reliability and quality engineering to data management, advanced analytics, and business decision support.

In his role at Abbott, Tony’s organization supported the development of diagnostic products currently contributing over $4 billion in annual worldwide revenue. With nearly 40 years of industry experience, he has served in leadership roles in both the automotive supply and medical diagnostics sectors, where he also championed use of Lean and Six Sigma methods in operations and product development as a Master Black Belt.

In his new entrepreneurial venture, Tony leads Convergent Analytics, an analytics consulting firm. Here, his focus is on helping companies improve through the use data analytics and maximize these capabilities through generative AI. His efforts aim to equip the next generation of engineers, scientists and analysts with the tools and insights needed to solve the complex challenges that industries will face today and tomorrow.