The Specialization can typically be completed within 6 to 8 weeks, with learners dedicating an average of 3–4 hours per week. This flexible schedule is designed to accommodate both working professionals and students, allowing learners to progress steadily through the courses while building strong, hands-on proficiency in data wrangling and visualization using Python’s Seaborn library. By the end of the program, participants will have gained practical, job-ready skills to create and interpret advanced data visualizations for real-world applications.

Learners should have a basic understanding of Python programming, including working with data structures and libraries such as Pandas. Prior exposure to statistics or data analysis concepts is helpful but not required.

Yes, it is recommended to take the courses in the suggested order. The curriculum is designed to build progressively—from foundational visualizations to advanced statistical analysis—ensuring learners develop a structured, step-by-step mastery of Seaborn.