Reading Data Course. In this course, you’ll learn how to read data from different sources, such as surveys, sensors, and machines, and how to use Python tools to clean, aggregate, and visualize it. You’ll also explore the value of data for different use cases and industries. What you’ll learn: Data is everywhere, but how can you make sense of it? In this Reading Data course, you’ll gain the fundamental ability to identify and read data from different sources and take the first steps toward clean and efficient data analysis. First, you’ll explore the types of real-world data and the value they have for different use cases, so you can determine which data type best fits your use case. Next, you’ll explore common data sources used in different industries (e.g. surveys, sensor data, machine-generated data), their strengths and weaknesses, and how to implement them using Pandas with Python. Next, you’ll implement data aggregation using sqlite3 in Python, which allows you to group and generate summary statistics and trends across multiple data points – an important aspect of data analysis. Finally, you’ll learn how to understand data and create powerful visualizations to convey insights from it. After completing this course, you’ll have the data reading skills and knowledge you need to extract different types of data from different sources and maximize its value through aggregation and visualization, regardless of your use case.