Create Your First LLM-Powered App Without Coding!

You may already be comfortable experimenting with GenAI tools. But turning those experiments into real applications can feel like a black box. Demos look great, yet they rarely explain how things like memory, context, and multi-step reasoning actually work behind the scenes.

In this live, three-hour workshop, you’ll move beyond demos and build a simple LLM-powered application step by step using LangChain. The focus is on how these apps are designed, how the pieces fit together, and what you need to think about when moving toward real-world use.

The workshop concludes with a brief preview of a structured learning path for those who want to move beyond introductory demos and build production-ready GenAI applications through the Applied GenAI Specialization by Michigan Engineering Professional Education.

Feb 25, 2026 | 7:00 PM IST | 8:30 AM ET

Duration: 3 hours

What You’ll Learn in This Session

• How LLM Applications Differ From Traditional Apps: Understand why prompt control, context management, and memory fundamentally change how applications are designed.
• Core Building Blocks of LLM Apps: Learn how prompts, chains, memory, tools, and external data work together in real applications.
• Live Application Build: Follow a step-by-step walkthrough to build a simple but functional LLM-powered application during the session. For example, you will see how an LLM retains context, calls tools, and responds across multiple steps.
• From Demo to Real-World Use: Understand what beginner demos miss and what is required to move toward reliable, production-ready applications.
• Next Steps for GenAI Skill Building: Learn how structured learning paths support readiness for real-world GenAI development work.

Who Should Attend

• Developers and software engineers new to GenAI
• Data professionals exploring LLM application development
• AI enthusiasts who have used tools like ChatGPT and want to build applications
• Professionals evaluating GenAI upskilling programs
• Learners seeking a hands-on introduction to LangChain

Having 2+ years of work experience and a basic understanding of programming concepts and mathematics is preferred.

About the Speaker

Solomon Promise is a data science instructor with extensive experience teaching Python, machine learning, and applied data science to over 1,000 learners. His background combines strong theoretical foundations with hands-on project experience across domains such as fraud detection, healthcare analytics, energy forecasting, and workforce analytics.

He has delivered multiple client-focused projects and achieved a top-tier ranking in competitive data science challenges. In this workshop, he focuses on helping learners understand how GenAI concepts translate into real, working applications.

After the session, registered attendees will receive Top GenAI Career Paths in 2026, a practical career guide that explains how emerging GenAI roles differ from traditional AI or software roles, what skills they require, and how professionals can plan their upskilling path strategically.

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