This course is part of the Introduction to Programming with Python and Java Specialization

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Brandon Krakowsky

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Associated with the Master of Computer and Information Technology degree

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Introduction to Programming with Python and Java SpecializationUniversity of Pennsylvania

About this Course

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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.

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Shareable Certificate

Earn a Certificate upon completion

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Course 2 of 4 in the

Introduction to Programming with Python and Java Specialization

Beginner Level

High school or college math.

“Introduction to Python Programming” Coursera course or equivalent prior knowledge of introductory Python.

Approx. 17 hours to complete

English

Subtitles: English, Korean

What you will learn

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

Skills you will gain

Data Science
Python Libraries
Python Programming
Data Analysis
Data Visualization (DataViz)

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 2 of 4 in the

Introduction to Programming with Python and Java Specialization

Beginner Level

High school or college math.

“Introduction to Python Programming” Coursera course or equivalent prior knowledge of introductory Python.

Approx. 17 hours to complete

English

Subtitles: English, Korean

Instructor

Instructor rating

4.49/5 (82 Ratings)

Brandon Krakowsky

Lecturer

School of Engineering and Applied Science

49,331 Learners

7 Courses

Offered by

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.

Start working towards your Master's degree

This course is related to the 100% online Master of Computer and Information Technology from University of Pennsylvania. It will provide you with a preview of the topics, materials and instructors so you can decide if the full online degree program is right for you.

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Syllabus - What you will learn from this course

Week

Week 1

6 hours to complete

Module 1 : Loading, Querying, & Filtering Data Using the csv Module

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.

6 hours to complete

8 videos (Total 31 min), 9 readings, 3 quizzes

8 videos

Course Introduction 53s

About the Instructor : Brandon Krakowsky 1m

Downloading & Installing Jupyter Notebook35s

Using Jupyter Notebook3m

Importing and reading a file using the csv module 3m

Coding demonstration : Analyzing the 500 Greatest Albums of All Time12m

Coding demonstration : Catching data errors and sorting7m

Coding demonstration : Calculating max and min1m

9 readings

Course Layout & Syllabus15m

Tips to succeed in this course10m

Module 1 Resources (DOWNLOAD RELEVANT CODE AND/OR DATA FILES FOR THIS MODULE HERE)5m

Review of dictionaries10m

Review of lists5m

Review of loops10m

Review of functions5m

Lambda with max and min10m

Homework 1 - Instructions10m

2 practice exercises

Quiz 1 - Loading, Querying, & Filtering Data12m

Quiz 2 - Catching Errors & Sorting10m

Week

Week 2

5 hours to complete

Module 2 : Loading, Querying, Joining & Filtering Data Using pandas

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.

5 hours to complete

14 videos (Total 31 min), 5 readings, 4 quizzes

14 videos

The pandas module 43s

Loading data 1m

Inspecting data 1m

Querying data 47s

Joining data 59s

Code Along Exercise : Join data 6m

Slicing rows 2m

Querying data using boolean indexing6m

Code Along Exercise : Dive bar recommendation in Las Vegas 4m

Computations - sum() 1m

Computations - mean() 47s

Other methods 26s

Updating & creating data 43s

Code Along Exercise : Add rating column 1m

5 readings

Module 2 Resources (DOWNLOAD RELEVANT CODE AND/OR DATA FILES FOR THIS MODULE HERE)5m

Homework 2 - Instructions10m

Casting Data5m

Cleaning data & dealing with missing values3m

Homework 3 - Instructions10m

2 practice exercises

Quiz 3 - Loading, Inspecting, & Querying Data10m

Quiz 4 - Joining & Filtering Data10m

Week

Week 3

5 hours to complete

Module 3 : Summarizing & Visualizing Data

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.

5 hours to complete

18 videos (Total 22 min), 5 readings, 4 quizzes

18 videos

Summarizing groups51s

The numpy library 48s

Pivot tables 29s

Using an index 41s

Code Along Exercise : Average review count and rating2m

Aggregate functions2m

Jupyter notebook magic functions 21s

The matplotlib library 27s

Histograms 36s

Histograms Coding Demonstration : To show distribution of data 28s

Histograms Coding Demonstration : Preparing data 1m

Histograms Coding Demonstration : Setting options for PyPlot 1m

Histograms Coding Demonstration : Displaying the visualization 3m

Scatterplots 34s

Scatterplots Coding Demonstration : To compare data points on different dimensions12s

Scatterplots Coding Demonstration : Preparing data 1m

Scatterplots Coding Demonstration : Setting options for PyPlot 2m

Scatterplots Coding Demonstration : Displaying the visualization 1m

5 readings

Module 3 Resources (DOWNLOAD RELEVANT CODE AND/OR DATA FILES FOR THIS MODULE HERE)5m

Homework 4 - Instructions10m

Bar charts and plotting pivot tables7m

For reference: Seaborn2m

Homework 5 - Instructions10m

2 practice exercises

Quiz 5 - Summarizing Data10m

Quiz 6 - Visualizing Data12m

Reviews

4.6

51 reviews

5 stars
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4 stars
25.44%
3 stars
4.46%
2 stars
1.33%
1 star
1.78%

TOP REVIEWS FROM DATA ANALYSIS USING PYTHON

by KPApr 12, 2021

course is overall good but face some problem in understanding of homework questions, proper explanation is needed

by AMFeb 7, 2021

Videos touching same theme were too short (26 sec, 1 min, etc.) and disruptive. Wish there could be more practices.

by MHApr 14, 2021

A great course to learn data analysis and visualization using Python

by JJMay 3, 2021

this was very useful and well prepared course. Thanks a lot

View all reviews

About the Introduction to Programming with Python and Java Specialization

This Specialization starts out by teaching basic concepts in Python and ramps up to more complex subjects such as object-oriented programming and data structures in Java. By the time learners complete this series of four courses, they will be able to write fully-functional programs in both Python and Java, two of the most well-known and frequently used programming languages in the world today.

Introduction to Programming with Python and Java is for students and professionals who have minimal or no prior programming exposure. It’s for motivated learners who have experience with rigorous coursework, and are looking to gain a competitive edge in advancing their career. It’s for folks who are thinking about applying to the University of Pennsylvania’s online Master of Computer and Information Technology degree and want to sample some of the lecture videos and content from the first course in the program. We hope this Specialization is for you. Topics in this Specialization include language syntax, style, programming techniques, and coding conventions. Learn about best practices and good code design, code testing and test-driven development, code debugging, code and program documentation, and computational thinking.

Frequently Asked Questions

When will I have access to the lectures and assignments?
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.
What will I get if I subscribe to this Specialization?
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.
Is financial aid available?
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.
How much math do I need to know to take this course?
The only math that learners will need for this Specialization is arithmetic and basic concepts in logic.
This course was fun. How can I learn more?
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.

More questions? Visit the Learner Help Center.

Data Analysis Using Python