Learn and master the Data Science, Python for Machine Learning, Math for Machine Learning, Statistics for Data Science
InstructorJitesh Khurkhuriya
Coupon
The curriculum provides detailed coverage of linear algebra, calculus, and both descriptive and inferential statistics.
Instructional signals indicate that complicated topics are broken down into accessible, scientific explanations.
Editorial course preview
This view highlights a concrete, legible example from the course presentation.
This curriculum overview slide outlines the course structure across six key pillars: Mathematics, Statistics, Data Wrangling, Machine Learning, Programming Languages, and Data Visualisation.
One signal suggests the study materials may be outdated, while another indicates a lack of instructor assistance for questions.
One sampled review suggests that some learners have noted that certain Python concepts are glossed over before transitioning to data preprocessing.
While the curriculum aligns with beginner goals, signals of inactive support may impact the experience for those needing guidance.