New edX Course: Data Science & Machine Learning Essentials

This post is by Chirag Dhull, Product Marketing Manager in the Data Platform Marketing Team at Microsoft.

We are excited to announce the launch of our very first MOOC – Data Science & Machine Learning Essentials – an exciting five week course that starts on September 24th 2015, free on edX. Our instructors are seasoned experts from academia and industry: Professor Cynthia Rudin of MIT and Dr. Steve Elston, Managing Director, Quantia Analytics.

This course will benefit aspiring data scientists, analytics professionals and students looking to develop skills around applied data science and ML. Students will apply tools such as R, Python and Azure ML, all of which are part of Microsoft’s newly announced cloud suite for big data and advanced analytics, the Cortana Analytics Suite.

Register for the course online today.

Why This Course

Organizations of every stripe are scrambling to extract strategic value from their vast troves of data these days. So much so that it’s sometimes easy to forget that this is still a relatively recent trend and that a job titled “Data Scientist” barely existed a few years ago. Roll the clock a few years, and, as this often-cited Harvard Business Review article put it, Data Scientist is the sexiest job of the 21st century. Furthermore, the article speculated that the shortage of data scientists would constrain several business sectors. Given the growing need for such talent across the board, the objective for our MOOC course is to provide quality data science education at scale.

What Will The Course Cover

The course is organized into 5 weekly modules covering topics such as:

• • The data science process.

• • Overview of data science theory.

• • Data acquisition, ingestion, sampling, quantization, cleaning and transformation.

• • Building data science workflows using Azure ML.

• • Developer tools for data science including R and Python.

• • Data exploration and visualization.

• • Building and evaluating ML models.

• • Publishing ML models using Azure ML.

The complete course syllabus is here. Each module concludes with a quiz followed by a final course assessment. By achieving a passing grade in the assessment you will receive a certificate demonstrating your newly acquired knowledge and skills.

What To Do Next

1. Sign up and be fully engaged: We encourage everyone to sign up first. Then, make the most of the course by interacting with faculty, asking questions in the forum or via live office hours (provided at the half-way point). Getting yourself deeply engaged will help you make the most of this MOOC and complete the course.

2. Adopt or promote the curriculum : We’ve invested a lot in the course and would love for these materials to benefit as many classrooms as possible. If you’re an analytics or data science teacher yourself, look out for additional information on how to use these materials following the completion of the course.

3. Follow this blog: To prepare you for the course, our faculty have agreed to publish a few blog posts to highlight core data science concepts. Their posts will become available right here, on the Microsoft ML blog site – so be sure to subscribe to it today.

We hope many of you will take advantage of this unique training opportunity – and be sure to share your feedback, as always.

Chirag
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Comments

• Anonymous
  September 10, 2015
  Is this course targeted at developers and IT professionals, or at less technical PM's that are interested in data analysis?
  
  Thanks!
• Anonymous
  September 14, 2015
  Hi Lisa,
  
  Basic understanding of statistics concepts and a programming language( r/python) is preferred to derive the most value from the course. However, the course does provide a primer on data science concepts along with intro on how to use Azure machine learning’s drag and drop features to build your first data science model. So these requirements are not mandatory. Less technical audience can still benefit from major portions of the course
  
  Chirag