Installing Jupyter

Basics of data analysis with Pandas

• Introduction to Python packages: Pandas, Numpy.
• Importing non-python datasets (Excel, JSON, Parquet) 
• Basic functions (shape, head, tail, dtype, loc/iloc) functions) 
• Data Cleaning (Duplicates, outliers and missing values)
• Data types (Conversion of data types)
• Renaming and deleting columns 
• Concatenating and transforming 
• Subsetting data frames 
• Filtering and selecting
• Aggregation and grouping 
• Groupby function 
• Reshaping data frames: stack() and unstack()

Correlation analysis (Parametric& non-parametric)

Predictive modelling

• Multiple Linear regression 
• Logistic regression
• Decision tree 
• Random forest 

Dimension reduction methods 

• Explanatory factor analysis 
• Principal component analysis