H. Data Science Portfolio Project I

The Data Science Portfolio Project I course aims to enhance expertise in data management, covering fundamental aspects such as Exploratory Data Analysis (EDA), data analysis, Sampling Strategy, and the application of Machine Learning Algorithms like KNN and Decision Tree, including model evaluation. This will enable learners to effectively apply their knowledge in real-world projects.

Participants will learn how to manage data, perform EDA to identify and rectify data issues, and utilize sampling strategies for initial data analysis. They will also apply KNN and Decision Tree algorithms to build predictive models, along with evaluating these models using metrics such as Precision, Recall, and F1-score.

By the end of the course, learners will possess the skills to professionally apply data analysis techniques and create a comprehensive portfolio project that showcases their ability to handle real data challenges effectively.