Data Scientist-Participant
CurrentA 480-hour, in-class, project-based course, where I covered:1-Collect, extract, query, clean, and aggregate data for analysis.2-Perform visual and statistical analysis on data using UNIX, Git, SQL, Python, and its associated libraries and tools.3-Build and implement appropriate Machine Learning models and algorithms to evaluate data science problems spanning finance, public policy, and more.4-Craft and share compelling narratives through data visualization.5-Compile clear stakeholder reports to communicate the nuances of your analyses.6-Identify big data problems and articulate how distributed systems and parallel computing technologies solve these challenges.7-Apply question, modelling, and validation problem-solving processes to data sets from various industries to provide insight into real-world problems and solutions.
