This specialization develops learners’ analytics mindset and knowledge of data analytics tools and techniques. Specifically, this specialization develops learners' analytics skills by first introducing an analytic mindset, data preparation, visualization, and analysis using Excel. Next, this specialization develops learners' skills of using Python for data preparation, data visualization, data analysis, and data interpretation and the ability to apply these skills to issues relevant to accounting. This specialization also develops learners’ skills in machine learning algorithms (using Python), including classification, regression, clustering, text analysis, time series analysis, and model optimization, as well as their ability to apply these machine learning skills to real-world problems.
Applied Learning Project
Projects included in this specialization allow learners to apply the skills developed within the data analytics specialization to real-world problems. Learners will be able to articulate the general process of the CRISP-DM framework, demonstrate data analytics skills in data preparation, data visualization, modeling, and model evaluation, and apply data analytics knowledge and skills to real-world problems. For example, in the capstone project, learners will develop a machine learning model in order to predict whether a loan is to be fully paid and construct a loan portfolio with the help of the analysis.
