- Provider edX
- Cost Free Online Course (Audit)
- Session Self Paced
- Language English
- Effort 3-4 hours a week
- Duration 6 weeks long
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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
• 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
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Reviews for edX's Data Science Essentials Based on 5 reviews
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- 4 star 0%
- 3 stars 40%
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Write a review- 1
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 and ends with training some models using machine learning. Unfortunately subjects are poorly explained (more advanced statistics will be hard to understand without prior knowledge).
Course delivers two parallel paths for R and Python (which is awesome!), but not even a line of code is written during the course - instructo…
- 1
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