Microsoft MOOC On Data Science & Machine Learning
To make learning the fundamentals and key concepts of data science and machine learning Microsoft is offering a free online course. This course will help you develop your career as a data scientist. Microsoft is offering this 5-week course via the edX platform. Applicants can apply for a verified certificate for $90.
Course Details In Brief
Length: 5 weeks
Effort: 3-4 hours PW
Institution: Microsoft with edX
Certificate Available: Yes
Best course for applicants
Why Choose Microsoft MOOC?
This is free online course. Applicants don’t have to pay anything for this course. This course comprises 5 weekly modules each concluding with a quiz. By achieving a passing grade in the final course assessment you will receive a certificate demonstrating that you have acquired data science skills and knowledge. Apart from answering your questions on the forum, faculty will host an office hour to address questions you may have while undertaking this course.
Get an ID verified certificate to demonstrate your data science knowledge and share it on Linked in. Verified Certificate will cost $90.
Demand for Data science talent is exploding. Learn these essentials with experts from M.I.T and the industry, partnering with Microsoft to help develop your career as a data scientist. By the end of this course, you will know how to build and derive insights from data science and machine learning models. You will learn key concepts in data acquisition, preparation, exploration and visualization along with examples on how to build a cloud data science solution using Azure Machine Learning, R & Python.Data Science is an essential skill for analyzing and deriving useful insights from data, big and small. McKinsey estimates that by 2018, a 500,000 strong workforce of data scientists will be needed in the US alone. The resulting talent gap must be filled by a new generation of data scientists.
You Will Learn
By the end of the course, you will have knowledge of
- 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