Foundational Concepts
Differentiating between data types (quantitative vs. qualitative) and data structures
Basic understanding of databases and how data is stored and accessed
 
Data Cleaning and Preparation
Understanding data types (e.g., integer, float, string) and converting between them
Learning basic data preprocessing techniques: filtering, sorting, grouping
 
Exploratory Data Analysis (EDA)
Using descriptive statistics (mean, median, mode, standard deviation)
Creating basic visualizations (bar charts, histograms, scatter plots)
Identifying patterns, trends, and anomalies in datasets