Introduction to Data Analytics; Data and Relations. Getting data: Sources of data, formats of data. Preparing data for analysis: Cleaning and Pre-processing. Forms of analysis: Data Visualization, Correlation, Regression, Forecasting, Classification, Clustering.
? Introduction to Python and basic data analytics libraries (Pandas, SciPy, NumPy, SK-Learn..)
? Introduction to machine learning using Python
? Getting and reading data from multiple sources in variety of formats (structured and semi-structured data)
o Merging data, data wrangling: slicing and dicing, filtering data
? Analyzing data, data exploratory analysis
? Data pre-processing ? Detecting contaminations and cleaning data.
? Data pre-processing - data transformation.
? Data visualizations.