What Is Design Management?
April 17, 2024
Article
This course is part of Introduction to Programming with Python and Java Specialization
Instructor: Brandon Krakowsky
30,285 already enrolled
Included with
(413 reviews)
Recommended experience
Beginner level
High school or college math.
“Introduction to Python Programming” Coursera course or equivalent prior knowledge of introductory Python.
(413 reviews)
Recommended experience
Beginner level
High school or college math.
“Introduction to Python Programming” Coursera course or equivalent prior knowledge of introductory Python.
Apply basic data science techniques using Python
Understand and apply core concepts like Data Frames and joining data, and use data analysis libraries like pandas, numpy, and matplotlib
Demonstrate how to load, inspect, and query real-world data, and answer basic questions about that data
Analyze data further by applying learned skills in data aggregation and summarization, as well as basic data visualization
Add to your LinkedIn profile
7 assignments
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
This course provides an introduction to basic data science techniques using Python. Students are introduced to core concepts like Data Frames and joining data, and learn how to use data analysis libraries like pandas, numpy, and matplotlib. This course provides an overview of loading, inspecting, and querying real-world data, and how to answer basic questions about that data. Students will gain skills in data aggregation and summarization, as well as basic data visualization.
This first module provides students with an overview of loading, inspecting, and exploring data using Python's simple csv library. To get started, this module includes a brief overview of Jupyter Notebook and a concise review of basic Python, including data structures, loops, and functions. This module showcases to the students an in-depth analysis of data stored in a .csv file, including basic querying, approaches for dealing with data errors, and how to filter and sort data based on a variety of criteria.
8 videos10 readings3 assignments1 programming assignment
In this module, students are introduced to core concepts like the Data Frame and joining data. Students will get experience using pandas, an industry-standard data analysis library, to load and query real-world data and to answer questions about that data. This module demonstrates how to do advanced filtering and indexing, slice subsets of data, restrict data attributes in query results, and do basic computations over the data. Includes how to build a simple recommendation system, and approaches for cleaning data, dealing with missing values, and creating new data.
14 videos5 readings2 assignments2 programming assignments
This module takes data analysis a step further by providing an overview of the process of aggregating, summarizing, and visualizing data. Students are introduced to the concept of grouping and indexing data, and how to display results in a pivot table using pandas. This module also demonstrates how to prepare and visualize data using a histogram and scatterplot in Jupyter Notebook. Students will gain skills in data aggregation and summarization, as well as basic data visualization. In addition, students will get experience using data analysis libraries like numpy and matplotlib.
18 videos6 readings2 assignments2 programming assignments
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
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.
Course
Course
University of Michigan
Course
Course
413 reviews
69%
22.03%
4.84%
1.45%
2.66%
Showing 3 of 413
Reviewed on Feb 7, 2021
Videos touching same theme were too short (26 sec, 1 min, etc.) and disruptive. Wish there could be more practices.
Reviewed on Jan 14, 2022
This is a good course! I hope University of Pennsylvania will offer the more advanced course so I can enroll, too! Kudos to the instruction and to the staff.
Reviewed on Nov 12, 2022
Good! It is probably challenging sometimes, but it is not very tough generally speaking. A little drawback might be that it didn't help me build up data analytical thinking vey much.
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
The only math that learners will need for this Specialization is arithmetic and basic concepts in logic.
If you enjoyed this course, we recommend Courses 1, 3 and 4 in the series!
If you would like to learn the fundamentals of computer science beyond the basics of programming, consider applying to the Master of Computer and Information and Technology (MCIT) at the University of Pennsylvania, an Ivy League computer science master’s program for people without a computer science background. For an on-campus experience, explore here. If you prefer an online setting, apply to MCIT Online. In fact, the lectures in this series are also used in the online degree program! The Specialization certificate will be viewed favorably by the admissions committee, so be sure to mention it when you apply.
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. 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.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.