Programming with Python for Data Science

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9/10 stars
based on  6 reviews
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FREE,
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edX online courses
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Harvard University, the Massachusetts Institute of Technology, and the University of California, Berkeley, are just some of the schools that you have at your fingertips with edX. Through massive open online courses (MOOCs) from the world's best universities, you can develop your knowledge in literature, math, history, food and nutrition, and more. These online classes are taught by highly-regarded experts in the field. If you take a class on computer science through Harvard, you may be taught by David J. Malan, a senior lecturer on computer science at Harvard University for the School of Engineering and Applied Sciences. But there's not just one professor - you have access to the entire teaching staff, allowing you to receive feedback on assignments straight from the experts. Pursue a Verified Certificate to document your achievements and use your coursework for job and school applications, promotions, and more. EdX also works with top universities to conduct research, allowing them to learn more about learning. Using their findings, edX is able to provide students with the best and most effective courses, constantly enhancing the student experience.

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Sciences & Technology
Business & Management
23465 reviews

Course Description

This course is part of the Microsoft Professional Program Certificate in Data Science.

This practical course, developed in partnership with Coding Dojo, targets individuals who have introductory level Python programming experience. The course teaches students how to start looking at data with the lens of a data scientist by applying efficient, well-known mining models in order to unearth useful intelligence, using Python, one of the popular languages for Data Scientists. Topics include data visualization, feature importance and selection, dimensionality reduction, clustering, classification and more! All of the data sets used in this course are gathered live-data or inspired by real-world domains that can benefit from machine learning.

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Reviews 9/10 stars
6 Reviews for Programming with Python for Data Science

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Anton MB profile image
Anton MB profile image

Anton MB

9/10 starsCompleted
2 years, 6 months ago
This course took me the most time in the Dataprofessional series from Microsoft so far. The effort is at least 6*8 = 48 hours rather then 4 x 6 as stated on this 'front page'. It is time well spend however! The course covers some python code but focuses primarily on data science. The lessons are a bit about data collecting, cleaning and preparing but the bulk of the lessons focus on modelling and testing which I liked. Hence the first modules can be made very fast while the last 4 take up 90% of your time. In every phase concepts are introduced, explained and then the basic syntax in python/matplotlib/sklearn is shown. The labs rehearse this first and then go a bit further so you have to find some information yourself online. This is done on purpose because in reality you also have to work in this way. Simultaneously your knowledge of the 'science side' is also deepens by making the labs and quizes. So the balance between coding and... This course took me the most time in the Dataprofessional series from Microsoft so far. The effort is at least 6*8 = 48 hours rather then 4 x 6 as stated on this 'front page'. It is time well spend however! The course covers some python code but focuses primarily on data science. The lessons are a bit about data collecting, cleaning and preparing but the bulk of the lessons focus on modelling and testing which I liked. Hence the first modules can be made very fast while the last 4 take up 90% of your time. In every phase concepts are introduced, explained and then the basic syntax in python/matplotlib/sklearn is shown. The labs rehearse this first and then go a bit further so you have to find some information yourself online. This is done on purpose because in reality you also have to work in this way. Simultaneously your knowledge of the 'science side' is also deepens by making the labs and quizes. So the balance between coding and learing about actual data science is good. It is good to know what a loop is in python, as well knowing what a dataframe and a series is and how to subset them. I found the exercises hard to make because of this subsetting and because I'm not a regular python user so some familiarity with python/pandas is needed in my view. The final exam is quite hard when it comes to the questions on python code. Be sure to summarize the course before making the exam and have basic code in your summary (preferably on a text editor so you can find relevant parts with CRTL+F). You don't want to lose points for writing a 'categorial' in stead of 'category' as a parameter name for example. Mr. Apatira knows a lot the different datascience methods discussed and also their performance in practise. Difficult pieces of code not relating to the primary learning goals of the course is already written and is a good source of inspiration. I recommend this course but I found it quite challenging. Try to scrape every point out of the labs and quizzes because the exam can be hard.
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Venkatesh Gopalarathnam profile image
Venkatesh Gopalarathnam profile image

Venkatesh Gopalarathnam

8/10 starsCompleted
2 years, 7 months ago
This course is not much talked about on the public forums, but I felt it to be of very good content both concept wise and programming assignments. Getting through the required score to earn a certificate was not very easy. Assignments were challenging and every assignment was something new. Great course overall !!
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student

10/10 starsTaking Now
2 years, 7 months ago
I found this course the most useful from the entire Microsoft programme in Data Science. I enjoyed how the labs are set up, they really make you think as a result you learn a lot. It takes time to go through material, but material is very useful and you will apply the knowledge gained in your final project or other data science projects. Highly recommend this course as a beginner python coding and ML course!
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Denis-Alexandre Trottier profile image
Denis-Alexandre Trottier profile image

Denis-Alexandre Trottier

10/10 starsCompleted
2 years, 8 months ago
This is an excellent course offering many Python programming labs that lead us to perform dimensionality reduction, classification, clustering, and other data science related tasks. The course also offers a good intuitive-level reminder of the underlying theory.
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Albin Hasani profile image
Albin Hasani profile image

Albin Hasani

9/10 starsCompleted
2 years, 9 months ago
This course gives a great, easy-to-follow introduction to the field of data science. The assignments were interesting, sometimes difficult but taking the time to solve them sure is rewarding.
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Ali Mohamed Abdillahi profile image
Ali Mohamed Abdillahi profile image

Ali Mohamed Abdillahi

10/10 starsTaking Now
2 years, 9 months ago
I would like that the content will be enough and suitable to increase my career for educational background
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Rankings are based on a provider's overall CourseTalk score, which takes into account both average rating and number of ratings. Stars round to the nearest half.