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Predict rocket launch delays with machine learning

Offered By: Microsoft via Microsoft Learn

Tags

Machine Learning Courses Python Courses scikit-learn Courses Data Collection Courses Data Manipulation Courses

Course Description

Overview

  • Module 1: Get an introduction to how NASA chooses dates for a rocket launch and discover machine learning fundamentals.

    • In this module, you'll begin to discover:

    • The challenges weather can pose for a rocket launch
    • The data science lifecycle
    • How machine learning works
    • The role ethics play in machine learning

    Tip

    This module is part of a multimodal learning experience. Start the module to see how you can follow along!

  • Module 2: Learn about the steps to import data into Python and clean the data for use in creating machine learning models.

    • In this module, you will:

    • Explore weather data on days crewed and uncrewed rockets were launched
    • Explore weather data on the days surrounding launch days
    • Clean the data in preparation for training the machine learning model

    Tip

    This module is part of a multimodal learning experience. Start the module to see how you can follow along!

  • Module 3: In this module you focus on a local analysis of your data by using scikit-learn, and use a decision tree classifier to gain knowledge from raw weather and rocket launch data.

    • In this module, you'll begin to discover:

    • The importance of column choosing.
    • How to split data to effectively train and test a machine learning algorithm.
    • How to train, test, and score a machine learning algorithm.
    • How to visualize a tree classification model.

    Tip

    This module is part of a multimodal learning experience. Start the module to see how you can follow along!


Syllabus

  • Module 1: Introduction to rocket launches
    • Introduction
    • Data to predict weather years in advance
    • Launch day weather analysis
    • Machine learning and the data science lifecycle
    • Set a goal and get expertise
    • Collect, clean, and manipulate data
    • Choose an algorithm and train and test your model
    • Deploy your machine learning model
    • How humans and machine learning models learn
    • Ethics in data science and machine learning
    • Knowledge check
    • Summary
  • Module 2: Data collection and manipulation
    • Introduction
    • Determine the rocket launch questions to ask
    • Explore the rocket launch data to gain an understanding
    • Exercise - Import Python libraries and rocket launch data
    • Exercise - Clean weather data to analyze rocket launch criteria
    • Exercise - Consider additional data to include
    • Knowledge check
    • Summary
  • Module 3: Build a machine learning model
    • Introduction
    • Exercise - Determine columns to include in a machine learning model
    • Exercise - Choose the machine learning algorithm to predict rocket launch success
    • Exercise - Split data into training and testing datasets
    • Exercise - Train and test the machine learning model to predict rocket launch success
    • Exercise - Score the machine learning model that predicts rocket launch success
    • Exercise - Visualize the machine learning model
    • Exercise - Predict the success of a rocket launch using machine learning
    • Knowledge check
    • Summary

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