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. Deployment: Implementing models in real-world applications, often through APIs or integrated software solutions.   https://www.sevenmentor.com/data-science-course-in-pune.php https://www.iteducationcentre.com/ccna-course-in-pune-area.php