As discussed, here is my offer on WEKA!
1- Select Dataset and describe the data
2- Select Software ( if not traceis, describe it)
3- Data cleaning and preprocessing
a. Normalization b. Discretization c. Deletion
d. etc
4- Data Summary and Graph
a. Mean, Median,variance, std , range etc,etc
b. Scatter plot, boxplot
5- Data group (unsupervised learning) a. Clustering
b. Association rules ( if possible)
6- Classification
a. Decision trees
b. Naïve bays
c. K-NN
d. Advanced algorithms such as (neural nets is a bonus)
7- Prediction
a. Linear regression
b. Advanced (bonus)
8- Model(s) evaluation or comparison
a. Summaries advantage and disadvantages to all algorithms
b. Write summary of the evaluation results
9- Ensemble model
a. Describe it
b. describe its performance