Week 1 Task: Data Collection and Preprocessing:

This week, your task is to identify a publicly available dataset related to a social issue of your choice and prepare it for analysis. The objective is to demonstrate your ability to source, clean, and preprocess data in a meaningful and strategic manner. The deliverable is a DOC file detailing the data sourcing process, the preprocessing steps taken, and the final state of the dataset. Your key steps are: 1) Identify the dataset and social issue. 2) Document the data sourcing process. 3) Clean and preprocess the dataset. 4) Write a report detailing the steps taken and the final state of the dataset. Your report will be evaluated on the clarity of the description, the appropriateness of your data cleaning and preprocessing steps, and your ability to articulate your process and decisions.

Week 2 Task: Exploratory Data Analysis:

In this week, your task is to perform an exploratory data analysis (EDA) on the preprocessed dataset from Week 1. The objective is to understand the data, generate insights, and formulate hypotheses for further analysis. The final deliverable will be a DOC file containing the EDA report. Your key steps are: 1) Generate descriptive statistics. 2) Visualize data distributions and relationships. 3) Identify outliers and anomalies. 4) Generate insights and hypotheses. Your report will be evaluated based on the depth of your analysis, the quality of your visualizations, the meaningfulness of your insights, and the soundness of your hypotheses.

Week 3 Task: Predictive Modelling:

This week, you will apply a predictive modeling technique to your dataset. The goal is to build a model that can predict a target variable of your choice. Your deliverable will be a DOC file that documents the model building, evaluation, and validation process. The key steps are: 1) Select a target variable. 2) Choose a suitable predictive model. 3) Train and validate the model. 4) Evaluate the model's performance. Your report will be evaluated based on the appropriateness of the chosen model, the soundness of your training and validation process, the quality of your model evaluation, and your ability to explain your decisions.

Week 4 Task: Communicating Results:

This week, your task is to communicate the results of your analysis and modelling in a way that is accessible to non-technical stakeholders. The goal is to demonstrate your ability to present data-driven findings in a clear, concise, and engaging manner. Your deliverable will be a DOC file containing a written presentation of your findings. The key steps are: 1) Summarize your findings. 2) Discuss the implications of your results. 3) Recommend further steps based on your analysis. Your presentation will be evaluated based on the clarity of your summary, the relevance of your discussion, the soundness of your recommendations, and your ability to engage non-technical audience.