About this Course
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100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Beginner Level

Approx. 35 hours to complete

Suggested: 4 weeks, 6-8 hours/week...

English

Subtitles: English
User
Learners taking this Course are
  • Technical Writers
  • Auditors
  • Marketing Analysts
  • Financial Analysts
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Skills you will gain

Simple AlgorithmPython ProgrammingProblem SolvingComputation
User
Learners taking this Course are
  • Technical Writers
  • Auditors
  • Marketing Analysts
  • Financial Analysts
  • Traders

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Beginner Level

Approx. 35 hours to complete

Suggested: 4 weeks, 6-8 hours/week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
3 hours to complete

Pillars of Computational Thinking

6 videos (Total 44 min), 6 quizzes
6 videos
1.2 Decomposition6m
1.3 Pattern Recognition5m
1.4 Data Representation and Abstraction7m
1.5 Algorithms8m
1.6 Case Studies11m
4 practice exercises
1.2 Decomposition10m
1.3 Pattern Recognition10m
1.4 Data Representation and Abstraction15m
1.5 Algorithms15m
Week
2
4 hours to complete

Expressing and Analyzing Algorithms

7 videos (Total 69 min), 10 quizzes
7 videos
2.2 Linear Search5m
2.3 Algorithmic Complexity8m
2.4 Binary Search11m
2.5 Brute Force Algorithms13m
2.6 Greedy Algorithms9m
2.7 Case Studies12m
6 practice exercises
2.1 Finding the Largest Value10m
2.2 Linear Search10m
2.3 Algorithmic Complexity10m
2.4 Binary Search10m
2.5 Brute Force Algorithms15m
2.6 Greedy Algorithms10m
Week
3
4 hours to complete

Fundamental Operations of a Modern Computer

6 videos (Total 46 min), 10 quizzes
6 videos
3.2 Intro to the von Neumann Architecture8m
3.3 von Neumann Architecture Data6m
3.4 von Neumann Architecture Control Flow5m
3.5 Expressing Algorithms in Pseudocode8m
3.6 Case Studies10m
5 practice exercises
3.1 A History of the Computer10m
3.2 Intro to the von Neumann Architecture10m
3.3 von Neumann Architecture Data10m
3.4 von Neumann Architecture Control Flow10m
3.5 Expressing Algorithms in Pseudocode10m
Week
4
7 hours to complete

Applied Computational Thinking Using Python

9 videos (Total 91 min), 12 readings, 12 quizzes
9 videos
4.2 Variables13m
4.3 Conditional Statements8m
4.4 Lists7m
4.5 Iteration14m
4.6 Functions10m
4.7 Classes and Objects9m
4.8 Case Studies11m
4.9 Course Conclusion8m
12 readings
Programming on the Coursera Platform10m
Python Playground
Variables Programming Activity20m
Solution to Variables Programming Activity10m
Conditionals Programming Activity20m
Solution to Conditionals Programming Activity10m
Solution to Lists Programming Assignment5m
Solution to Loops Programming Assignment10m
Solution to Functions Programming Assignment10m
Solution to Challenge Programming Assignment10m
Solution to Classes and Objects Programming Assignment10m
Solution to Project Part 410m
12 practice exercises
4.2 Variables10m
4.3 Conditional Statements5m
4.4 Lists10m
Lists Programming Assignment15m
4.5 Iteration10m
Loops Programming Assignment30m
4.6 Functions10m
Functions Programming Assignment20m
(Optional) Challenge Programming Assignment20m
4.7 Classes and Objects10m
Classes and Objects Programming Assignment20m
Project Part 4: Implementing the Solution in Python25m
4.7
117 ReviewsChevron Right

42%

started a new career after completing these courses

35%

got a tangible career benefit from this course

Top reviews from Computational Thinking for Problem Solving

By JDec 19th 2018

Excellent course for beginners with enough depth, programming and computational theory to increase their computer science knowledge to a higher level. It builds a good foundation of how computers work

By AWFeb 4th 2019

The course is very well-designed and it helped me develop understand how to apply computational thinking in solving various types of problems as well as acquire basic skills of programming in Python.

Instructors

Avatar

Susan Davidson

Weiss Professor
Computer & Information Science
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Chris Murphy

Associate Professor of Practice
Computer & Information Science

About University of Pennsylvania

The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies. ...

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • No, definitely not! This course is intended for anyone who has an interest in approaching problems more systematically, developing more efficient solutions, and understanding how computers can be used in the problem solving process. No prior computer science or programming experience is required.

  • Some parts of the course assume familiarity with basic algebra, trigonometry, mathematical functions, exponents, and logarithms. If you don’t remember those concepts or never learned them, don’t worry! As long as you’re comfortable with multiplication, you should still be able to follow along. For everything else, we’ll provide links to references that you can use as a refresher or as supplemental material.

  • This course will help you discover whether you have an aptitude for computational thinking. This is a useful predictor of success in the Master of Computer and Information Technology program at the University of Pennsylvania, which is offered both on-campus and online. In this course you will learn from MCIT instructors and become familiar with the quality and style of MCIT Online courses.

    If you have a bachelor's degree and are interested in learning more about computational thinking, we encourage you to apply to MCIT On-campus (http://www.cis.upenn.edu/prospective-students/graduate/mcit.php) or MCIT Online (https://onlinelearning.seas.upenn.edu/mcit/). Please mention that you have completed this course in the application.

  • Use these links to learn more about MCIT:

    MCIT On-campus: http://www.cis.upenn.edu/prospective-students/graduate/mcit.php

    MCIT Online: https://onlinelearning.seas.upenn.edu/mcit/

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