This course includes a dedicated Telegram group where students can ask questions and get help from the instructor and teaching assistants. Students will also have the opportunity to collaborate with each other.

This is a self-paced course, so the amount of time required will depend on each individual student's pace. However, we recommend allocating at least 4-6 hours per week to work through the material and complete the exercises and projects.

Yes, this course emphasizes the practical application of data visualization in real-world scenarios. You will learn how to use Python to visualize data from a variety of sources, such as CSV files and SQL databases, and you will have the opportunity to work on hands-on exercises and projects.

This course covers a wide range of visualizations, including basic line plots, scatter plots, and bar charts, as well as more advanced plot types such as heatmaps, 3D plots, boxplots, and swarmplots. You will also learn how to create interactive visualizations using Bokeh and Plotly.

No, all of the software and tools used in this course are open source and freely available.

Students will need access to a computer with Python installed, as well as popular data visualization libraries such as Matplotlib, Seaborn, Bokeh, and Plotly. We will provide instructions on how to install and set up the necessary software.

This course requires a basic understanding of Python programming language and a statistics. However, we will cover these topics in a crash course at the beginning of the course, so no prior experience is necessary.