Programming In Python For Data Analytics And Data Science. Learn Statistical Analysis, Data Mining And Visualization
InstructorKirill EremenkoThe curriculum utilizes specific homework assignments, such as Financial Statement Analysis and Basketball Free Throws, to reinforce technical concepts.
Instructional signals suggest the teaching style is engaging and easy to follow for fundamental concepts.
Editorial course preview
These 2 complementary views highlight concrete, legible examples from the course presentation.
This screenshot shows a Jupyter Notebook session where Python code generates a box plot and a violin plot to visualize the distribution of movie critic ratings across different years.
This Jupyter Notebook output displays four distinct data visualizations for movie analytics, including contour plots, a multi-year violin plot, and a correlation heatmap.
Some learners report difficulty completing homework using only the provided lessons, alongside missing instructions for downloading required data files.
One signal indicates that certain content, specifically regarding Seaborn, may not align with the latest library versions.
The curriculum aligns well with the goal of learning Python for data science applications.