Demand for Data science talent is exploding. Learn these essentials with experts from MIT 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 US alone. The resulting talent gap must be filled by a new generation of data scientists.
This course is organized into 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 on LinkedIn.
MOOCs stand for Massive Open Online Courses. These arefree online courses from universities around the world (eg. StanfordHarvardMIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you. They also have student discussion forums, homework/assignments, and online quizzes or exams.
Data Science and Machine Learning Essentials is a 5-week introductory data science course offered by Microsoft through edX that focuses on teaching students how to use Microsoft's cloud-based machine learning platform, Azure ML. The course divides content into two tracks, an R track and a Python track, so you can com
Data Science and Machine Learning Essentials is a 5-week introductory data science course offered by Microsoft through edX that focuses on teaching students how to use Microsoft's cloud-based machine learning platform, Azure ML. The course divides content into two tracks, an R track and a Python track, so you can complete the course with either language, but you'll need to know the basics of at least one of the two. Grading is based on 5 weekly reviews and a single 20 question exam.
The course title "Data Science and Machine Learning Essentials" is misleading because this course is not really about data science or machine learning per se. The first week attempts to cram an entire machine learning course or two worth of concepts into a handful of mediocre lectures, while the remainder of the course is all about Azure ML. Weeks 2-5 provide a nice overview of Azure ML and the fact that it has full lectures for both R and Python is a great feature that surely took a lot of extra time and effort to produce. The main lecturer's presentation skills aren't the best, but the videos are still easy to follow. Azure ML offers a lot of interesting functionality, like the ability to use Python and R scrips in the same project and publish projects as web services, but some of the exercises were tedious and ran slowly.
If data "Data Science and Machine Learning Essentials" were renamed "Intro to Azure ML" and only included the content in weeks 2-5, it would be a good course. Weeks 2-5 are definitely worth checking out if you are interested in Azure ML. As it stands now, however, the first week bombards students with far too many concepts explained too quickly to foster real understanding and sets the wrong expectations for the remainder of the course.
I give Data Science and Machine Learning Essentials 2.75 out of 5: mediocre.
I sell Azure ML, and I'm very familiar with it. But this course took a very different look at ML. I'm much better at using and showcasing the studio now. I was surprised to see some very new features (Jupyter, Pandas, etc.) included.