Description
This course is an ideal entry point for anyone aspiring to become a data scientist using Python. It begins by covering the Python libraries essential for data analysis, such as NumPy, pandas, and matplotlib. Learners are guided through importing datasets, cleaning and transforming data, and visualizing insights. The course also covers statistical analysis, data wrangling techniques, and working with real-world datasets. As students progress, they’ll implement linear regression, classification models, and clustering algorithms using libraries like scikit-learn. Each module includes hands-on coding assignments and projects like predictive modeling or customer segmentation. This course prepares learners to take on more specialized data science tasks and sets a solid foundation for machine learning.
福田 健太
Loved the examples and hands-on exercises.
Megan Carter
Great for building real-world projects and applying what you learn.
山口 美咲
A well-structured course that covers all the important topics.
Joshua Scott
初心者にもやさしい説明で、助かりました。