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University of Michigan via Coursera

Python Debugging: A Systematic Approach

4.011 ratings at Coursera

Overview

In “Python Debugging: A Systematic Approach,” you will develop essential coding skills for data science, focusing on writing, testing, and debugging code. You will learn foundational Python concepts, such as looping, control structures, variables, and basic debugging techniques. You will also learn how a structured debugging procedure can help you debug more effectively and efficiently.

Throughout the course, you’ll practice essential programming concepts such as map, filter, and list comprehension. You’ll learn how to take a systematic approach to debugging with the OILER framework – Orient, Investigate, Locate, Experiment, and Reflect – allowing you to spot errors more easily and adjust your code. In addition to frameworks to help you improve your code, you’ll explore how documentation, internet resources, and even large language models (LLMs) can help you identify and fix errors. By the end of this course, you should feel confident in your abilities to write clean, efficient, and reusable code.

This is the first course in the four-course series, “Data-Oriented Python Programming and Debugging,” where you’ll work to strengthen your programming capabilities and enhance your problem-solving skills.

Syllabus 4

  1. Review and Setup 3.5 hours
  2. The Debugging Framework 6 hours
  3. Framework Skills 6 hours
  4. Stop Bugs Before They Happen 4.5 hours

Advantages and disadvantages

Advantages

  • Structured courses with graded quizzes, assignments and deadlines you can reset.
  • A shareable certificate from the university or company when you pay.
  • Financial aid is often approved for students in India (apply 15 days before you need it).
  • From University of Michigan, a well-regarded name.
  • Self-paced: start any time.
  • A clear syllabus (4 parts) you can see before you start.

Disadvantages

  • Paid after a 7-day free trial (Coursera Plus or per course).
  • Some courses can be audited for free, but graded work and certificates need payment.

Some points apply to every course of this kind; see how we rank.

This course is paid. Here is how to take it for free

  • Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
  • Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.

Taught by

  • Elle O'BrienLecturer IV & Research Investigator, School of Information
  • Anthony WhyteLecturer IV in Information, School of Information
  • Paul ResnickMichael D. Cohen Collegiate Professor of Information, School of Information

University of Michigan is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (86/100).

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