Learn to Preprocess, Wrangle and Visualise Data For Practical Data Science Applications in Python
InstructorMinerva SinghEditorial course preview
These 3 complementary views highlight concrete, legible examples from the course presentation.
This introductory slide displays the instructor's name, Minerva Singh, alongside visual indicators of her academic credentials from Oxford University and Cambridge University.
This slide contrasts traditional books and standard courses under the heading 'No More Expensive, Vague & Non Practical', highlighting the specific problems this data wrangling course aims to solve.
A title slide displaying the course topic in bold typography, highlighting data preprocessing, wrangling, and visualization techniques using Python.
The curriculum moves beyond basic cleaning to include technical topics like Principal Component Analysis (PCA) and Recursive Feature Elimination (RFE).
Instructional signals suggest the course is highly approachable for those with no prior coding or statistical modeling background.
One signal suggests disorganized or missing CSV files and potential incompatibilities with the latest Python versions. Note that these reports predate the displayed update date, which does not prove a correction has been made.
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The curriculum aligns with the target of beginners interested in Python and data science.