Course curriculum

  • 2

    Recorded videos and slides

    • Video 1.1: Data Selection, Pre-Analysis and Feature Selection

    • Slides 1.1: Data Selection, Pre-Analysis and Feature Selection

    • Quiz 1.1

    • Video 1.2: Making Machine learning interpretable

    • Slides 1.2: Making Machine learning interpretable

    • Quiz 1.2

  • 3

    Interactive e-learning

    • Introduction to unsupervised machine learning algorithms

  • 4

    Case Study Notebooks

    • Example: Binning of continuous variable & Data filtering

    • Hands-on Case Study: Interpreting results of ML Algorithms

    • Solution : Interpreting results of ML Algorithms

    • Hands-on Case Study: Detection of interactions between variables

    • Solution: Detection of interactions between variables

    • Example: Vehicle Categorization

  • 5

    Live Lesson

    • Live lesson: Profitability and Competition analysis

    • Slides: Profitability and Competition analysis

  • 6

    Appendix

    • Introducing R and Rstudio

    • A User Guide For Jupyter Notebooks

    • RStudio Helpful Guide (Ref 1)

    • Data Importing Helpful Guide (Ref 2)

    • dplyr Helpful Guide (Ref 3 )

    • ggplot Helpful Guide (Ref 4)

    • List of Relevant Resources from the Resource Library