README

DAT203.1x: Data Science Essentials

https://github.com/MicrosoftLearning/Data-Science-Essentials

https://github.com/sblack4/Data-Science-Essentials

About

course I completed in late 2016

Contents

Before You Start

  • Course Introduction

  • Lab Overview

  • Setting Up Azure Machine Learning

  • Installing R or Python

Module 1: Introduction to Data Science

Principles of Data Science

  • What Is Data Science?

  • Data Analytic Thinking

  • The Data Science Process

  • Further Reading

    Data Science Technologies

  • Introduction to Data Science Technologies

  • An Overview of Data Science Technology

  • Azure Machine Learning

  • Using Code in Azure ML

  • Jupyter Notebooks

  • Creating a Machine Learning Model

  • Further Reading

    Lab

  • Lab

Module 2: Probability and Statistics for Data Science

Probability and Random Variables

  • Overview of Probability and Random Variables

  • Introduction to Probability

  • Discrete Random Variables

  • Discrete Probability Distributions

  • Binomial Distribution Examples

  • Poisson Distributions

  • Continuous Probability Distributions

  • Cumulative Distribution Functions

  • Central Limit Theorem

  • Further Reading

    Introduction to Statistics

  • Overview of Statistics

  • Descriptive Statistics

  • Summary Statistics

  • Demo: Viewing Summary Statistics

  • Z-Scores

  • Correlation

  • Demo: Viewing Correlation

  • Simpson's Paradox

  • Further Reading

    Lab

  • Lab This content is graded

  • Lab Instructions

  • Lab Verification

    Module 3: Simulation and Hypothesis Testing

    Simulation and Confidence Intervals

  • Introduction to Simulation and Hypothesis Testing

  • Simulation

  • Demo: Performing a Simulation

  • Confidence Intervals

  • Demo: Confidence Intervals

  • Further Reading

    Hypothesis Testing

  • Overview of Hypothesis Testing

  • Introduction to Hypothesis Testing

  • Z-Tests, T-Tests, and Other Tests

  • Hypothesis Test Examples

  • Type 1 and Type 2 Errors

  • Demo: Hypothesis Testing

  • Misconceptions About Hypothesis Testing

  • Further Reading

    Lab

  • Lab This content is graded

  • Lab Instructions

  • Lab Verification

    Module 4: Exploring and Visualizing Data

    Exploring Data

  • Introduction to Data Exploration

  • Data and Data Frames

  • Working with Data in Code

  • Demo: Getting Started with Data Frames

  • Working with Data Frames in Azure ML

  • Demo: Working with Data Frames in Azure ML

  • Metadata

  • Demo: Working with Metadata

  • Further Reading

    Visualizing Data

  • Overview of Data Visualization

  • Introduction to Data Visualization

  • Conditioned Plots

  • Plotting in R or Python

  • Demo: Plotting in R or Python

  • Demo: Plotting in Azure ML

  • Further Reading

    Lab

  • Lab This content is graded

  • Lab Instructions

  • Lab Verification

    Module 5: Data Cleansing and Manipulation

    Data Ingestion and Flow

  • Overview of Data Ingestion and Flow

  • Data Flow in Azure ML

  • Joining Data Sets

  • Demo: Ingesting and Joining Data

  • Demo: Joins in R or Python

  • Further Reading

    Data Cleansing

  • Introduction to Data Cleansing

  • Overview of Data Cleansing

  • Missing and Repeated Values

  • Demo: Handling Missing and Repeated Values

  • Feature Engineering

  • Outliers and Errors

  • Demo: Finding Outliers

  • Demo: Handling Outliers in Azure ML

  • Demo: Cleaning Data with R or Python

  • Introduction to Data Scaling

  • Demo: Scaling Data in Azure ML

  • Demo: Scaling Data in R or Python

  • Further Reading

    Lab

  • Lab This content is graded

  • Lab Instructions

  • Lab Verification

    Module 6: Introduction to Machine Learning

    Getting Started with Machine Learning

  • Machine Learing Overview

  • Introduction to Machine Learning - Classification

  • Evaluating Classifiers

  • Demo: Creating a Classification Model in Azure ML

  • Regression

  • Evaluating Regression Models

  • Demo: Creating a Regression Model

  • Clustering

  • Demo: K-Means Clustering

  • Further Reading

    Publishing a Machine Learning Web Service

  • Introduction to Azure ML Web Services

  • Overview of Publishing a Web Service

  • Demo: Publishing a Web Service

  • Demo: Consuming a Web Service

  • Custom Code Considerations

  • Key Points and Further Reading

    Lab

    Final Exam and Survey

    Course Exam

    Post-Course Survey

https://github.com/MicrosoftLearning/Data-Science-Essentials

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