| Module 1 | Introduction to Data Analytics
- Understand common processes and key analytical skills used by data analysts in their day-to-day (which you will develop throughout this course);
- Understand the data life-cycle and the common data analysis processes.
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| Module 2 | Data wrangling with Python - Know Pandas fundamental.
- Know how to prepare your data for analysis and run basic statistics.
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| Module 3 | Exploratory Data Analysis - Understand what EDA is and why we need it.
- Know how to apply EDA to a real-world example using the Pandas library. To understand the full EDA process, this unit is further complemented with Descriptive Statistics and Visualizations units in order to fully equip you to independently implement EDA on any dataset.
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| Module 4 | Descriptive Statistics - Know how to describe data from various dimensions: central tendency, dispersion, shape of the data
- Understand what univariate analysis is and how to implement it
- Understand what bivariate analysis is and how to implement it.
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| Module 5 | Visualization and Storytelling - Understand the importance of data visualization;
- Know how to use Plotly in Python to create powerful visualizations;
- Know how to effectively present and communicate your insights through data storytelling.
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