Data Exploration for Data Science with Fabric Notebooks

Raw data rarely comes ready for machine learning or statistical analysis. Understanding how to load, clean, and explore your datasets is the first and most critical step in any successful data science workflow. This text-only course guides you through the essentials of data exploration using Fabric notebooks. You will gain the confidence to load diverse datasets, perform exploratory data analysis, and prepare your data for advanced modeling. What you'll learn: - Understand foundational data science concepts and the Fabric environment; - Load and inspect datasets using modern dataframe libraries; - Clean missing values and handle anomalies in your data; - Generate descriptive statistics to summarize key data characteristics; - Create written data profiles and basic visualizations using notebook tools; - Apply data preparation techniques to format features for modeling. Starting with key terminology and environment setup, this course walks you through reading and writing notebook code to analyze real-world datasets. You will transition from basic data loading to advanced statistical profiling and preparing clean data for downstream machine learning tasks. This course is designed for aspiring data scientists, analysts, and beginners who want to learn data exploration using Fabric notebooks. No prior data science experience is required. Start reading today to master the fundamentals of data exploration in Fabric.