Week 3 | Why AI Hallucinates and How to Build More Reliable AI Systems

About this event

Artificial Intelligence can write code, answer questions, summarize documents, and even generate creative content.

But it can also produce answers that sound completely convincing—while being entirely incorrect.

These incorrect yet confident responses are known as AI Hallucinations, and they are one of the biggest challenges faced by organizations building AI-powered applications.

In this live hands-on session, you'll discover why AI hallucinates, how Large Language Models generate responses, and the practical techniques used by AI engineers to significantly improve response accuracy.

Rather than simply accepting AI outputs, you'll learn how to identify unreliable responses and build AI systems that users can trust.

Through live demonstrations and real-world examples, you'll see AI make mistakes, understand why those mistakes happen, and learn the engineering approaches used to reduce them.

💡 Live Demonstrations

Watch AI answer real questions and discover:

• When AI provides accurate answers
• When AI confidently gives incorrect information
• How different prompts affect AI responses
• Why missing context causes hallucinations
• How enterprises improve AI reliability

One exciting demonstration will include asking AI unexpected questions—such as fictional or misleading prompts—to observe how confidently it generates incorrect answers and why that happens.

📚 What You'll Learn

• What AI Hallucinations Really Are
• How Large Language Models Generate Responses
• Temperature and AI Creativity
• The Importance of Context Windows
• Prompt Engineering Best Practices
• Embeddings Explained Simply
• Retrieval-Augmented Generation (RAG)
• Why Retrieval Improves AI Accuracy
• Common Causes of Hallucinations
• Industry Best Practices for Building Reliable AI Applications

🎯 Session Agenda

Understanding AI Hallucinations

Learn why AI sometimes generates believable but inaccurate information.

Inside Large Language Models

Understand how AI predicts the next word instead of "thinking" like humans.

Temperature and Creativity

See how different temperature settings affect response accuracy and creativity.

Context Windows

Learn why providing the right context dramatically improves AI responses.

Prompt Engineering

Discover techniques for writing prompts that reduce hallucinations.

Embeddings Explained

Understand how AI represents knowledge and semantic meaning.

Retrieval-Augmented Generation (RAG)

See why enterprise AI systems retrieve trusted information before generating responses.

Live Demonstrations

Watch real examples of hallucinations, analyze the causes, and apply techniques to improve reliability.

Industry Discussion

Explore how organizations monitor AI quality, evaluate responses, and build trustworthy AI solutions.

Interactive Q&A

Get your questions answered and deepen your understanding of reliable AI engineering.

👥 Who Should Attend?

🎓 College Students

🎓 Final Year Students

💼 Fresh Graduates

👨‍💻 Software Engineers

🐍 Python Developers

📊 Data Analysts

☁️ Cloud & DevOps Engineers

🤖 AI Enthusiasts

Anyone interested in building reliable, enterprise-grade AI applications.

🎁 Exclusive Participant Benefits

Every participant attending the live session will receive:

🏆 CareerByteCode Recognized Live Participant Certificate

• Downloadable Digital Certificate
• Unique Certificate Verification Link
• Add your verified certificate directly to the Licenses & Certifications section of your LinkedIn profile
• Showcase your AI learning journey to recruiters and hiring managers

💻 Access to Practice Code

Participants who wish to receive the complete session resources should:

• Share their learning and key takeaways on LinkedIn
• Tag Jenefer Rexee George
• Tag CareerByteCode
• Tag at least 2–3 friends

Eligible participants will receive the complete practice code and supporting materials after the session.

🚀 AI isn't perfect but great AI engineers know how to make it more reliable. Join this session to understand the science behind AI hallucinations and learn practical techniques used by leading AI teams to build trustworthy, production-ready AI applications.