Data Science Essentials

Archived
Course
en
English
24 h
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Source
  • From www.edx.org
Conditions
  • Self-paced
  • Free Access
  • Fee-based Certificate
More info
  • 6 Sequences
  • Introductive Level

You can't access an archived course

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Course details

Syllabus

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

Prerequisite

None.

Instructors

  • Dr. Steve Elston
  • Cynthia Rudin

Editor

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