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Online Course

Introduction to Python for Data Science

Microsoft via edX

Overview

Python is a very powerful programming language used for many different applications. Over time, the huge community around this open source language has created quite a few tools to efficiently work with Python. In recent years, a number of tools have been built specifically for data science. As a result, analyzing data with Python has never been easier.

In this practical course, you will start from the very beginning, with basic arithmetic and variables, and learn how to handle data structures, such as Python lists, Numpy arrays, and Pandas DataFrames. Along the way, you'll learn about Python functions and control flow. Plus, you'll look at the world of data visualizations with Python and create your own stunning visualizations based on real data.

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.

Note: These courses will retire in June. Please enroll only if you are able to finish your coursework in time.

Syllabus

Section 1: Python Basics
Take your first steps in the world of Python. Discover the different data types and create your first variable.

Section 2: Python Lists
Get the know the first way to store many different data points under a single name. Create, subset and manipulate Lists in all sorts of ways.

Section 3: Functions and Packages
Learn how to get the most out of other people's efforts by importing Python packages and calling functions.

Section 4: Numpy
Write superfast code with Numerical Python, a package to efficiently store and do calculations with huge amounts of data.

Section 5: Matplotlib
Create different types of visualizations depending on the message you want to convey. Learn how to build complex and customized plots based on real data.

Section 6: Control flow and Pandas
Write conditional constructs to tweak the execution of your scripts and get to know the Pandas DataFrame: the key data structure for Data Science in Python.

Taught by

Filip Schouwenaars

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Reviews

3.8 rating, based on 20 reviews

Start your review of Introduction to Python for Data Science

  • Michael B R completed this course, spending 7 hours a week on it and found the course difficulty to be easy.

    I completed this course in full but as an audit learner. The course is very good with a nice structure and good teachers. A great part of the course is that we get a good amount of practical experience in Jupyter Notebook with Python and numpy, pandas,...
  • Prashant SIngh completed this course, spending 5 hours a week on it and found the course difficulty to be easy.

    This is beginner level course.
    - I finished this in 2 days because I know Python .
    -`Short videos kept me engaging.
    - Introduction of Numpy and Matplotlib was good.
    -Online python console was good.It does not require you install Python IDE.
    -Lecture delivery could be made more interesting and engaging.
    -Good course for beginner.
  • Anonymous

    Anonymous completed this course.

    This is a course for very beginner, like me. It really helped me to peer a bit into the giantic world of Python, but I hope that I will be able to use this tiny gained knowledge in real life. I must practice and practice and practice much more, this is the key.
    Why 4 stars? I needed a summary module from the starting point at the end of the course, because without refreshing I forgot some important things.
  • Arnoud

    Arnoud is taking this course right now, spending 3 hours a week on it and found the course difficulty to be very easy.

    Though auditing the course would seem possible for free, but that not true anymore. When you audit this course, no excercises will work, meaning at this time of writing, you can only watch the video's. You have to pay to actually do the course. I'll probably discontinue this course because of this
  • Procellaria completed this course, spending 5 hours a week on it and found the course difficulty to be medium.

    In my opinion this course is a waste of time, because the lessons are very minimal and badly structured. The programming assignments require a lot of information not provided in the lessons forcing the learner to long searches on the internet.
  • Mwiinga Cheelo completed this course, spending 14 hours a week on it and found the course difficulty to be medium.

    Brilliant course. Extremely relevant for rookies to programming with Python for Data Science like me. I completed the course and got a certificate to give me confidence to do advanced courses in Python. Thanks to the team and keep it up.
  • Poon Ho Chuen completed this course and found the course difficulty to be easy.

    The course offered by DataCamp. It is easy to follow. The final exam is a bit long though. You can either follow the path or join other courses offered by DataCamp, which I also recommend.
  • Numan completed this course, spending 10 hours a week on it and found the course difficulty to be easy.

    This course is probably one of the best python data science introduction course. Instructor is explains the topics very clear and materials are really good.

    It took me about 10 hours of my weekend to complete the course.
  • Yogesh

    Yogesh is taking this course right now and found the course difficulty to be easy.

    very good for bigineer
    first i feel it is very hard but due to this course i feel this is so easy
    so i request to all take this free course and learn
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