WSQ Data Analytics & Visualization (SF) (Synchronous and Asynchronous E-Learning)

About This Course

The "Data Analytics & Visualization" module equips learners with the necessary knowledge and skills to perform data analysis and visualization tasks using Python. Through a series of Instructional Units (IU), learners will acquire proficiency in various key areas.
In the initial learning units, learners will gain an introduction to Python programming, including essential concepts such as functions, conditionals, and file handling. This foundational knowledge will provide learners with the necessary programming skills to work with data effectively. Learners will also explore the functionalities of NumPy, a fundamental library for numerical computing in Python. They will acquire skills in array manipulation, mathematical operations, and statistical analysis using NumPy.
In addition, the module also covers data manipulation using Pandas, a powerful data manipulation library in Python. Learners will learn how to load, clean, and transform data using Pandas, enabling them to perform various data wrangling tasks efficiently. The module culminates with a focus on data visualization using Matplotlib and Seaborn. Learners will learn how to create visually appealing and informative plots, charts, and graphs to effectively communicate insights derived from data analysis.
Through the module's projects, learners will have the opportunity to apply their acquired knowledge and skills in a real-world context. They will develop a Python project centered around analysing and visualizing sales data using Pandas, Matplotlib and Seaborn. This project will allow learners to practice data manipulation techniques, extract meaningful insights from the data, and present their findings through compelling visualizations.
By the end of the module, learners will have gained proficiency to perform data analysis tasks, apply statistical techniques, and effectively communicate their findings through visualizations.