In simple words: A strong presentation explains evidence and limitations in plain language.
Tell the story in order
State the business or research question, describe the data and labels, explain why the selected model fits, show how you trained and tested it, and report the result. Include a simple visual of the data-to-prediction flow.
Discuss limits
Show at least one mistaken prediction, possible bias, and what you would improve next. If you did not train a model, say so and present a concept or prototype honestly. The course outline names cohort presentations for Sessions 14 and 15, but the exact assessment instructions must come from your instructor.
See the flow
A team presents a review-sentiment prototype: 300 labelled reviews, an NLP model, accuracy plus recall, one mixed-review mistake, and a plan for more data.
Remember: A strong presentation explains evidence and limitations in plain language.