UT Dallas AI & Machine Learning Bootcamp

Build a tracker where users log, categorize, and analyze expenses against a budget, with file-based saving and loading.

Analyze quarterly sales data by region and generate insights to guide data-driven business decisions.

Perform exploratory data analysis and hypothesis testing to identify factors that influence customer acquisition.

Clean HR data, perform EDA and clustering, handle class imbalance with SMOTE, build ML models, and suggest retention strategies.

Use deep learning to predict loan defaults from historical, imbalanced datasets with multiple features.

Create a chatbot using PDFs and vectorization to answer HR policy queries, with a Gradio-based user interface.

Explore OpenAI APIs to generate creative designs from text prompts for real-world scenarios.

Build deep learning models to detect and localize vehicles in images, then analyze the impact of autopilot usage on road safety.

Develop models to classify heritage structures from images and create a recommendation engine to guide tourists.

Forecast item-level sales across restaurants using historical data to enable smarter planning and decision-making.