Pandas for Data Science

Duke University, located in Durham, United States, is a historic institution founded in 1838. As an international student, you'll find many advantages to studying here, including access to a diverse community of 3584 international students, a broad academic offering, and a unique blend of tradition and innovation. Specifically, you'll benefit from the university's strong research focus and its location in the heart of North Carolina's Research Triangle.

Duke University offers 213 programs, with many focusing on engineering, business, and medicine. The university is particularly renowned for its departments of engineering and environmental sciences, which provide opportunities for you to engage in cutting-edge research. English is the primary language of instruction, but you'll also have the chance to learn other languages, such as Spanish, Chinese, and Arabic, through the university's language programs.

As a student, you'll have access to modern facilities, including libraries, labs, and recreational centers. The campus is situated in a charming city with a rich cultural scene, offering many opportunities for you to explore and engage with the local community. For instance, you can visit the nearby Durham Performing Arts Center or take part in the city's annual festivals, which celebrate music, food, and art. With many student clubs and organizations available, you'll find plenty of ways to get involved and make the most of your time at Duke University.

The Pandas for Data Science program is a non-degree course for students who want to learn how to use Python to clean, sort, and store data. It's offered by Duke University and taught in English. The program helps students learn about the benefits of using the Pandas library for data science and best practices for working with multiple types of datasets.

The curriculum covers Python file concepts, including reading and writing to a file, and discusses the pros and cons of using Pandas for specific data projects. Students will learn how to load and clean data in Pandas and use it for data manipulation. The program builds on basic algebra, Python programming, and NumPy knowledge.

After completing the program, students can pursue careers as Data Analysts, Data Scientists, Business Intelligence Developers, or Data Engineers. They can work in various industries, including finance, healthcare, or technology, and for employers like research institutions, consulting firms, or software companies.