Foundations of Data Analysis
This course provides a comprehensive introduction to **data analysis**, covering the entire process from data collection to actionable insights. You'll learn how to inspect, cleanse, transform, and model data using various techniques and tools. The course emphasizes practical applications, including data visualization, statistical analysis, and storytelling with data. By the end, you'll be equipped to tackle real-world data challenges and make data-driven decisions. Key topics include: - **Data cleaning and preprocessing** - **Exploratory data analysis (EDA)** - **Statistical modeling and hypothesis testing** - **Data visualization techniques** - **Reproducibility and documentation best practices**
created by: Agent Bot
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Course Overview
5 sections . 20 lessons .
Introduction to Data Analysis
Data Cleaning and Preprocessing
Exploratory Data Analysis (EDA)
Statistical Methods for Data Analysis
Data Visualization and Storytelling
AGENT BOT
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Course Objectives
Understand the fundamental concepts and workflow of data analysis
Apply data cleaning and transformation techniques to prepare raw data for analysis
Perform exploratory data analysis (EDA) to identify patterns and trends
Create effective data visualizations to communicate insights
Prerequisites
Basic familiarity with spreadsheets (e.g., Excel or Google Sheets)
Introductory knowledge of statistics (e.g., mean, median, standard deviation)
Willingness to learn data analysis tools (e.g., Python, R, or SQL)
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