Python for Data Science

This 10-week course is free to enroll and is structured around a total of 80 hours of active learning. This is not an introductory course. It is an advanced look at applying Python to applications in data science.

Created by: Ilkay Altintas

Produced in 2017

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What you will learn

  • The basic process of data science.
  • Jupyter and Python notebooks.
  • Applied Understanding of manipulating and analyzing data sets.
  • Basic statistics and machine learning.
  • Visualizing results.

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Course Description

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data science Awards Best Course Overall

In the information age, data is all around us. Within this data are answers to compelling questions across many societal domains (politics, business, science, etc.). But if you had access to a large dataset, would you be able to find the answers you seek? This course, part of the Data Science MicroMasters program, will introduce you to a collection of powerful, open-source, tools needed to analyze data and to conduct data science. Specifically, you'll learn how to use: python, jupyter notebooks, pandas, numpy, matplotlib, git, and many other tools. You will learn these tools all within the context of solving compelling data science problems. After completing this course, you'll be able to find answers within large datasets by using python tools to import data, explore it, analyze it, learn from it, visualize it, and ultimately generate easily sharable reports. By learning these skills, you'll also become a member of a world-wide community which seeks to build data science tools, explore public datasets, and discuss evidence-based findings. Last but not least, this course will provide you with the foundation you need to succeed in later courses in the Data Science MicroMasters program.

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Pros

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Cons

    • Course teaches by example, giving you a realistic glimpse into legitimate data science.
    • Course encourages peer interaction to build a supportive community that expands learning.
    • All lecture videos include subtitles.
    • Interaction with instructors can be slow and limited.
    • Jupyter section is UNIX heavy and can be troubling to perform on Windows machines.
    • Completing course does not guarantee reception of the certificate.

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Instructor Details

Ilkay Altintas

Ilkay Altintas is the chief data science officer at the San Diego Supercomputer Center (SDSC), UC San Diego, where she is also the founder and director for the Workflows for Data Science Center of Excellence. She received her Ph.D. degree from the University of Amsterdam in the Netherlands with an emphasis on provenance of workflow-driven collaborative science and she is currently an assistant research scientist at UCSD.

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Reviews

4.4

9 total reviews

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By Vikram A on 12/26/2017

It's a great course. I learnt a lot though I had prior Python knowledge. Instructors are great. You are also rewarded for course engagement in addition to assignments. As an audit learner I scored 70% on the course spending 1-2 hours per week.

By Ashlynn P on 8/6/2017

This course gave clear instructions on how to get started in making data science projects with Python and Jupyter Notebooks. Unlike some other courses, the walkthroughs were prepared as Jupyter Notebooks which saved me from having to stop the videos every two seconds to type out notes.

By Elie G on 10/10/2017

One of the best course on Python for data science. the instructors chose carefully the minimum necessary to help you through your own way to data science. I could give 5 but since I was auditing I may have missed the quality of assignments.

By Simon H on 11/15/2017

Great overview of the data science process and great introduction to Python tools such as Pandas and Matplotlib. I am now using these tools on a daily basis.

By Magpiem M on 9/21/2017

Great class! Key python skills + tons of well-organized information for data science. And the peer-review of the projects is the most exciting part

By Mary Mojica on 12/30/2017

I loved this course. The instructors are very clear and there are a lot of resources to take advantage of the lessons. I enjoyed the most the live code sessions because we were able to work with several real databases.

By Juan Diaz on 4/15/2019

do yourself a favor and do not take this course. it is excruciatingly painful just to try to watch a 3 minutes video let alone a 20 plus minutes video, where the instructor is un-enthusiastically talking about the subject. i wrote on the forum asking for help and i never got a reply. when taking the proctor test you will need to download a software and test the software with a microphone. all of these extra steps i found annoying.

By Edward Parrales on 12/15/2017

I'm a business University student, so indeed, I was a complete beginner in the field of IT and Programming. Personally, it was a big challenge for me to complete this course, and I had to spend many extra hours for understanding and learn these new concepts. However, it was relatively easy to follow these lectures, and Python is perfect for non-programmers. I have learned so much from this course, and it motivates me a lot to complete the whole Micromaster program. I've checked other similar courses in Edx, because I would like to start a career as a Data Analyst, and I must say that this is course covers the most relevant requirements that companies expects from an employee in this field. I'm really thankful for this opportunity.

By Student Y on 6/22/2017

One of the best MOOCs in the world and the best course in the python for data science field. I learn from Dr. Altintas many useful and critical skills like numpy , pandas scikit learn, nltk , and more. She is very clear and explain every thing in easy and understandable way. Every thing in this course amazing and the beast thing in this course is the notebook (ipynb). there is one problem in this course which is Dr. Porter don't explain every thing he just progress and when I watch his videos I don't know why he is use this function or this method etc.. and what is the benfit of this.