- Data Wrangling (gathering data from different sources (web-scraping, querying APIs, flat files), assessing the data to check for quality and tidiness issues and cleaning them in order to make the analysis outcome more accurate. - Analyzing and visualizing data using python and its libraries (pandas, numpy, matplotlib, seaborn)