diff --git a/Main.py b/Main.py
new file mode 100644
index 0000000..a61663d
--- /dev/null
+++ b/Main.py
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+from Prediction import Prediction
+import numpy as np
+import pandas as pd
+import random
+from sklearn.metrics import mean_squared_error
+from sklearn.metrics import mean_absolute_error
+from sklearn.metrics import median_absolute_error
+from math import sqrt
+
+#Prediction of complexity level (the number of levels is variable)
+#Each row is a complexity level, each pair [,] is the note and the time for a question (test with 3 levels)
+
+dataI=pd.read_csv('dataInitial.csv', sep=' ', header=0)
+data=pd.read_csv('data.csv', sep=' ', header=0)
+v1=[]
+v2=[]
+n=0
+#for name,dr in dataI.iterrows():
+for i in range(1):
+
+    #initialization of Beta distribution for all the complexity levels (test with 5 levels)
+    betap=[[1,1],[1,2],[1,3],[1,4],[1,5]]
+
+    #Parameters: previous grades and times, a-priori paameters for beta distribution in each complexity level, step for change beta parameters, value of penalization for time and value of limit between win and loss
+    pred=Prediction(dataI.iloc[i,:], data.iloc[i,:], betap, 0.2, 1/16, 6)
+    pred.CalculateGradePenalization()
+    pred.Calculate()
+    pred.CalculateSW()