Data Cleaning and Exploratory in Python
Description
This course is designed for data professionals in intermediate level who are interested to apply
exploratory and data cleaning in data analysis projects using Python.
COURSE OBJECTIVES
•To prepare your data for a data analysis project
•To learn how to deal with missing data and outliers to resolve data inconsistencies
•To gain maximum insight from the data set and its
underlying structure
•To improve your understanding of descriptive statistics
•To do feature engineering and extract the most meaningful
features from variables
•To do exploratory analysis using different plots
COURSE SYLLABUS
•Loading and cleaning data in Python
•Data structure investigation
•Relationships and patterns investigation among variables
•Dummy variable interpretation
•Feature engineering and variable transformation
•Missing and duplicate data imputation
•Outlier handling
•Feature scaling
•Correlation testing
•Exploratory data analysis using Python 3 graphical libraries
•Applying the data cleaning exploratory analysis on real data as the final project
Registration fee :
€ 590
Target audience
- IT professionals
- Computer Science and IT Students
- Data Scientists
- Data Analysts
Requirements
- Basic knowledge of Python
- Basic knowledge of descriptive statistics