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Python for Data Science

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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UCSanDiegoX

Rating 4.4 based on 41 ratings
Length 10 weeks
Effort 8 - 10 hours per week
Starts Sep 4 (21 weeks ago)
Cost $350
From UCSanDiegoX via edX
Instructors Ilkay Altintas, Leo Porter
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Analysis & Statistics

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What people are saying

We analyzed reviews for this course to surface learners' thoughts about it

jupyter notebook in 10 reviews

The best thing about the course are the jupyter notebook notes and exercises.

Good work-through several tools and python libraries using jupyter notebook that gets you started right away.

It will introduce you to jupyter notebook and python scientific libraries such as numpy, pandas, matplotlib... etc Valuable content and learning methodology of doing.

for data science in 7 reviews

Practical introductory course for data science using python and its major data science libraries (numpy, pandas, matplotlib, ...).

One of the best course on Python for data science.

Take this course if you are new to python for data science and you will not regret your time.

It's a really good introduction (and more) to Python tools necessary for data science.

Overall the course is good and would recommend anyone wanting to pursue python for Data Science.

Excellent course to get in touch with Python and Jupyter notebooks for data science.

This is the best introductory course for data science.

Key python skills + tons of well-organized information for data science.

jupyter notebooks in 7 reviews

The jupyter notebooks are great and I reference them even after completing the course.

An extremely good introduction to jupyter notebooks, pandas, numpy and others.

However, I liked the pervasive use of Jupyter Notebooks, since so far I always was a command line hacker, and Jupyter is the first IDE that I like.

The use of jupyter notebooks encourages to dive into it and explore in further detail.

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.

Great course, gave me a solid introduction to Python, Jupyter Notebooks and the fundamentals of data analysis.

machine learning in 5 reviews

I didn't rate this 5 stars because there was at least one time where I asked a forum question to the course staff, which was also echoed by another classmate regarding potential erratum in the machine learning section that wasn't major, but had me wondering if I had misunderstood some concepts of parallel plots but the edx staff never responded to the question.

The later weeks do throw a lot of material at you (machine learning, natural language processing, databases) but don't dive into it deeply.

Also an quick introduction to machine learning and looking forward to the subsequent course on machine learning in depth.

The python notebooks were excellent starting points to play around with the different data processing and machine learning techniques.

It includes machine learning and linux aspects too.

other courses in 4 reviews

I hope to continue with the other courses in this series!

This course is better combined with other courses.

The professors are awesome, excited for the other courses in the micromasters!

very good in 3 reviews

its a great cause,the teachers are both very good.

The course is very good.

Of course you must put extra hours to get the best from this course, but is a very good introductory approach to Data Science, using Python.

Careers

An overview of related careers and their average salaries in the US. Bars indicate income percentile.

AD, Data Science $47k

Associate Data Science Supervisor $55k

Science writer / data analyst $63k

Genomic Data Science Programmer $75k

Volunteer Director of Data Science $78k

Expert Data Science Supervisor $79k

Supervisor 1 Data Science Supervisor $91k

Guest Director of Data Science $101k

Data Science Architect $105k

Head of Data Science $131k

Assistant Director 1 of Data Science $133k

Owner Director of Data Science $149k

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edX

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UCSanDiegoX

Rating 4.4 based on 41 ratings
Length 10 weeks
Effort 8 - 10 hours per week
Starts Sep 4 (21 weeks ago)
Cost $350
From UCSanDiegoX via edX
Instructors Ilkay Altintas, Leo Porter
Download Videos On all desktop and mobile devices
Language English
Subjects Programming Data Science
Tags Computer Science Data Analysis & Statistics