Explore a comprehensive conference talk on forecasting student mental wellness using Julia programming language. Delve into the importance of mental health for university students and its impact on academic performance. Learn about innovative approaches to analyze mental health data using Julia packages like DataFrames.jl, MLJ.jl, and PyPlot.jl. Discover how to collect and process various data sources, including academic performance, attendance, counseling records, and social media posts. Gain insights into developing predictive models for mental wellness and visualizing results. The presentation covers an introduction to mental health, its significance for students, Julia's applications in mental health analytics, forecasting approaches and models, a basic forecasting model demonstration, results discussion, and concludes with a Q&A session.