Course curriculum

  1. 01

    • Installation

    • Intro

    • Installation confirmation

    • Supporting notebooks
  2. 02

    • Hubble data

    • Plotting data

    • Loops

    • Conditional statements

    • Quiz 1 - variables and loops

    • Project 1 upload
  3. 03

    • Data setup

    • Using Numpy and X

    • Classifiers

    • Decision Tree

    • Decision Tree concepts

    • Optimising

    • Project 2 upload
  4. 04

    • Data setup

    • Data scaling

    • Neural Networks

    • Training

    • Confusion Matrix

    • ROC curves

    • Quiz 2 questions

    • Project 3 upload
  5. 05

    • Loading data

    • Image data

    • PyTorch Neural Network

    • Loss and SGD

    • Training

    • Metrics (ROC)

    • Optimising

    • Quiz 3 - Machine Learning data

    • Project 4 upload
  6. 06

    • Straight lines

    • Differences

    • Learning Rate

    • Optimising

    • Optimising c

    • Quiz 4 - Machine Learning algorithms

    • Project 5 upload