I’m in the last stretch of my Computer Science degree and need an extra pair of expert hands to wrap up my final-year assignment, which centers on Data Science with a clear emphasis on predictive analysis. The project is already under way: I have the raw dataset approved by my supervisor and a rough outline of the questions we’re expected to answer. What’s missing is the full predictive pipeline—cleaning, feature engineering, model selection, validation, and a concise write-up linking the results back to the research objectives. Python is my preferred language and I’ve been using Jupyter, pandas, NumPy, scikit-learn, and Matplotlib so far, so sticking to that stack will make integration smooth. To keep everything organized, here’s what I need handed over: • A well-commented notebook (or .py script) that runs end-to-end, from data import through to model evaluation and visualization. • A short report (≈1,500 words) explaining the methodology, justification for the chosen predictive model, key findings, and any limitations or future work. . 10 slide ppt • Any auxiliary files—cleaned datasets, environment.yml / requirements.txt—to ensure results are reproducible on my side. The code must execute without errors and the report should be clear enough for an academic audience, properly referencing any external libraries or sources used. I’ll share the dataset and grading rubric once we start so you can align with the submission standards.