Welcome to Tier 1 of our Coding Bootcamp - Data Analysis. This tier introduces you to the vast and exciting world of data-driven insights. As we venture beyond basic coding to the manipulation and understanding of data, here's what you will learn:
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Data Reading and Cleaning: Start by learning how to import data from various formats like CSV, Excel, and databases. You'll explore how to handle missing, inconsistent, and erroneous data to clean your datasets and make them ready for analysis.
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Data Visualization: Visual storytelling is an important part of data analysis. You'll learn how to create insightful and interactive plots using libraries like Matplotlib and Seaborn, which can help reveal trends, patterns, and correlations in your data.
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Descriptive Statistics: You'll learn how to summarize and describe the main features of a dataset through measures like the mean, median, mode, and range, among others.
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Inferential Statistics: Discover how to make predictions about a population based on a sample of data. You'll learn about hypothesis testing, regression analysis, and more.
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Data Transformations: Transform your data to suit your analytical needs. You'll work with functions to sort, filter, group, and reshape data, and understand the different types of data structures suitable for these tasks.
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Data Wrangling: Dive deeper into data preparation with data wrangling techniques. Learn how to handle outliers, merge datasets, pivot data, and more. This module prepares you to deal with the messiness of real-world data and convert it into a format that is easier to analyze.
Each module will have a main_lesson.md file linking to individual lesson files, as well as practice problems and homework assignments with solutions. This ensures that you learn and apply these concepts practically. Remember, the best way to learn data analysis is by doing - you'll be working hands-on with actual datasets, extracting insights, and visualizing your findings.