Unlock the Power of Data with Python: University of Michigan Offers New Programming Specializations on Coursera

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Unlock the Power of Data with Python: University of Michigan Offers New Programming Specializations on Coursera

Python is one of the fastest-growing programming languages, and a main driver of its popularity is data science. Due to its easy learning curve, a rich set of libraries and tools, and strong community support, Python is used widely by data scientists.

The University of Michigan has launched two new Python Specializations in partnership with Coursera. You can learn how to use the power of Python for data analysis with a series of courses covering fundamental theory and project-based learning.

“Data has moved beyond technology to transform every major industry including healthcare, finance, media, government and more,” said Qiaozhu Mei, Associate Professor of Information and Director of the Master of Applied Data Science program at the School of Information. “Our Python Specializations are designed to provide the skills needed to capitalize on the data revolution happening in the world today.”

Both of these Specializations are recommended if you’re considering the University of Michigan Master of Applied Data Science degree program on Coursera. Programming and data analysis skills are a key focus of the program because they empower students to ask meaningful questions and generate evidence-based solutions. You can set an excellent foundation to succeed in the degree program by completing these new Python Specializations.

These fully online courses are designed for learners from varied backgrounds and can be completed at any pace. They are an ideal starting point if you have no prior programming knowledge, or if you are already familiar with another programming language. Python was ranked as the No. 1 language for data science and machine learning in a recent KD nuggets survey. Adding it to your skill set will grant you a significant competitive advantage when it comes to data.

Tackle data with the power of Python

Python 3 Programming: Learn the basics and fundamentals of programming in Python with the first two courses in this Specialization. After that, you can take a deeper dive with three subsequent advanced courses.  After completing the Specialization, you will be able to design, code, and test small Python programs and understand the concepts of object-oriented programming.

Statistics with Python: This three-course Specialization is focused on ways to turn data into actionable insights. You’ll learn where data comes from, the types of data that can be collected, how to summarize and visualize data, and how to apply advanced statistical modeling procedures. You’ll also get access to tutorial videos about creating visualizations and data management within Python.

Get hands-on practical training

Learn from practice-based sessions and complete applied projects for your portfolio. Practice tools and libraries including:

  •   Python imaging library
  •   Python-tesseract
  •   NumPy
  •   SciPy
  •   Matplotlib
  •   Seaborn

If you have completed the popular Python for Everybody Specialization, these Specializations are an ideal next step for your data science education. Increasingly, business success depends on effective utilization of data. Last year, Python was ranked No. 7 on a Forbes list of the top ten technical skills in terms of rising demand. The growth rate for Python-related jobs is 456%!

“From major enterprises to start-ups, companies around the globe are using Python to process an avalanche of data in order to gain key business insights,” said Christopher Brooks, Research Assistant Professor at UMSI, leader of the Applied Data Science with Python specialization on Coursera, and Director of Learning Analytics and Research for Michigan’s Office of Academic Innovation. “The University of Michigan is one of nation’s premier institutions for data science education, and these new Specializations will equip a broad range of professionals with the knowledge they need to launch or advance a career in data science.”