DATA SCIENCE
Data Cleaning: Preparing the data for analysis by removing errors, handling missing values, and ensuring consistency.
Exploratory Data Analysis (EDA): Analyzing the data to discover patterns, trends, and relationships through visualization and summary statistics.
Modeling: Applying statistical and machine learning techniques to make predictions or classify data.
Evaluation: Assessing the performance of models using metrics like accuracy, precision, and recall.
https://www.sevenmentor.com/da....ta-science-course-in