Data Science Essentials
Overview
This course is part of the Microsoft Professional Program Certificate in Data Science and Microsoft Professional Program in Artificial Intelligence.
Demand for data science talent is exploding. Develop your career as a data scientist, as you explore essential skills and principles with experts from Duke University and Microsoft.
In this data science course, you will learn key concepts in data acquisition, preparation, exploration, and visualization taught alongside practical application oriented examples such as how to build a cloud data science solution using Microsoft Azure Machine Learning platform, or with R, and Python on Azure stack.
edX offers financial assistance for learners who want to earn Verified Certificates but who may not be able to pay the fee. To apply for financial assistance, enroll in the course, then follow this link to complete an application for assistance.
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
Taught by
Dr. Steve Elston and Cynthia Rudin
Related Courses
Reviews
3.6 rating, based on 5 reviews
-
Berbelek completed this course, spending 4 hours a week on it and found the course difficulty to be medium.
I've completed the course with a bit mixed fillings. The subject in general and the course's topics in particular are very interesting. The course tries to give you some background in statistics and lead you to overview of data science, its methods... -
Manny
1Manny completed this course, spending 5 hours a week on it and found the course difficulty to be easy.
Gives basic understanding of statistics for data science using Azure ML. Do not expect on learning either Python or R in this course. This course is just making you familiar with tools that will be used in Data science. -
S Salman
S Salman completed this course.
First of all this course is not for newbi, course has designed for Microsoft professional program in Data science student. Pre knowledge is required to complete this course. If you are a student from Microsoft professional program in Data science then it should look quite fruitful and enjoyable. -
Abel Loredo
Abel Loredo is taking this course right now, spending 2 hours a week on it and found the course difficulty to be easy.
The course is too boring, bad edited and the instructor don't make you be interested in the topic. I don't recommended. -
Sonsoles López completed this course.
Never Stop Learning!
