Data Science and Machine Learning Essentials: Course by Microsoft

Microsoft conducts online course on 'Data Science and Machine Learning Essentials'. The course focuses on key concepts of data science and machine learning with examples on how to build a cloud data science solution with R, Python and Azure Machine Learning from the Cortana Analytics Suite.

About the Course:

The course enables you to know how to build and derive insights from data science and machine learning models. During the course you will learn The data science process, Overview of data science theory, Data acquisition, ingestion, sampling, quantization, cleaning and transformation, Building data science workflows with Azure ML, Data science tools including R, Python and SQL, Data exploration and visualization, Building and evaluating machine learning models, Publishing machine learning models with the Azure ML.

Course On Data Science,Machine Learning Essentials

 

Course Syllabus:

Module I Introduction

  • Introduction to Data Science
  • Overview of the Data Science process
  • Introduction to Data Science technologies
  • Introduction to Machine Learning
  • Regressions
  • Classification
  • Clustering
  • Recommendation

Module 2: Working with Data in Azure ML

  • Data Acquisition
  • Data Ingestion and Ingress
  • Data Sampling and Quantization
  • Data Cleaning and Transformation

Module 3: Building and Evaluation of Models

  • Data Exploration and Visualization
  • Business Metrics and Cost-Based Metrics
  • Model Evaluation, Comparison and Selection

Module 4: Models in Azure ML, Part 1

  • Regression Models
  • Classification Models
  • Unsupervised Learning Models

Module 5: Models in Azure ML, Part 2

  • Recommendation Models
  • Publishing AML Models
  • Course Exam

Prerequisites:

Candidates should have basic knowledge of mathematics, including linear algebra and programming experience either in R or Python is preferred.

Course Details:

  • Course Starts on: 24 September
  • Course Length: 5 weeks
For details on the course visit the website

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