Data Science Essentials (edX)

What you'll learn:

- Explore the data science process

- Probability and statistics in data science

- Data exploration and visualization

- Data ingestion, cleansing, and transformation

- Introduction to machine learning

Syllabus

Skip Syllabus Description Explore the data science process – An Introduction

• Understand data science thinking

• Know the data science process

• Use AML to create and publish a first machine learning experiment

• Lab: Creating your first model in Azure Machine Learning

Probability and statistics in data science

• Understand and apply confidence intervals and hypothesis testing

• Understand the meaning and application of correlation Know how to apply simulation

• Lab: Working with probability and statistics

• Lab: Simulation and hypothesis testing

Working with data – Ingestion and preparation

• Know the basics of data ingestion and selection

• Understand the importance and process for data cleaning, integration and transformation

• Lab: Data ingestion and selection - new

• Lab: Data munging with Azure Machine Learning, R, and Python on Azure stack

Data Exploration and Visualization

• Know how to create and interpret basic plot types

• Understand the process of exploring datasets

• Lab: Exploring data with visualization with Azure Machine Learning, R and Python

Introduction to Supervised Machine Learning

• Understand the basic concepts of supervised learning

• Understand the basic concepts of unsupervised learning

• Create simple machine learning models in AML

• Lab: Classification of people by income

• Lab: Auto price prediction with regression

• Lab: K-means clustering with Azure Machine Learning