Section: Data processing and analysis | AI Programming with Python | NLearning

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Section outline

This section covers essential techniques for processing and analyzing data to extract meaningful insights. You will learn how to clean, transform, and manipulate raw data using Python libraries like Pandas and NumPy. Topics include data wrangling, handling missing values, data normalization, exploratory data analysis (EDA), and basic statistical methods. The focus is on preparing and analyzing data effectively to support decision-making and machine learning model development.
- Select activity Understanding data formats and preprocessing
  
  Understanding data formats and preprocessing Page
- Select activity Data wrangling with Pandas
  
  Data wrangling with Pandas Page
- Select activity Exploratory Data Analysis (EDA) with visualizations
  
  Exploratory Data Analysis (EDA) with visualizations Page
- Select activity Feature engineering and scaling
  
  Feature engineering and scaling Page
- Select activity Section quiz
  
  Section quiz

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