Analyzing Data from Scratch in Python

Data Analytics is one of the most important skills for the successful operation of any Data Science team. Especially if the data analysis is done in one of the powerful programming languages such as Python and R. This workshop is designed to introduce you to the world of data analysis and to show you how powerful Python is as a programming language for each segment of data analysis. We will start the lectures with topics about setting up the work environment (Jupyter Notebook & Python), after that we will move on to data preparation for data processing and data cleaning (pre-processing part). When the data is prepared for work, we will first analyze the data using descriptive data analysis and visualization techniques, then using inferential statistics methods (e.g. T-test, ANOVA, MANOVA, Mann-Whitney U etc.), and finally we will go through both correlation (Pearson correlation coefficient and Spearman’s rank correlation coefficient) and linear regression analysis. After each of the conducted statistical analyses, we will present a report with the interpretation of the obtained results and their applications in business.