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This module introduces the fundamentals of working with datasets, including understanding data structure, identifying patterns, assessing data quality, performing basic data exploration, and using filtering and sorting techniques to make meaningful initial observations for data analysis.
This course introduces the complete data science workflow, covering dataset understanding, data cleaning and preprocessing, exploratory data analysis, basic statistics, data visualization, Python libraries (NumPy and Pandas), and machine learning fundamentals. Learners gain hands-on experience in analyzing, transforming, visualizing, and interpreting data, apply data science techniques to real-world case studies, and complete an end-to-end project with implementation, presentation, and reporting of results.
