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

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Brandon Krakowsky

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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.

Flexible deadlines

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Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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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. 16 hours to complete

English

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.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

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. 16 hours to complete

English

Instructor

Instructor rating

4.44/5 (112 Ratings)

Brandon Krakowsky

Lecturer

School of Engineering and Applied Science

78,197 Learners

7 Courses

Offered by

University of Pennsylvania

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

Week1

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 53sAbout the Instructor : Brandon Krakowsky 1mDownloading & Installing Jupyter Notebook35sUsing Jupyter Notebook3mImporting and reading a file using the csv module 3mCoding demonstration : Analyzing the 500 Greatest Albums of All Time12mCoding demonstration : Catching data errors and sorting7mCoding demonstration : Calculating max and min1m

9 readings

Course Layout & Syllabus15mTips to succeed in this course10mModule 1 Resources (DOWNLOAD RELEVANT CODE AND/OR DATA FILES FOR THIS MODULE HERE)5mReview of dictionaries10mReview of lists5mReview of loops10mReview of functions5mLambda with max and min10mHomework 1 - Instructions10m

2 practice exercises

Quiz 1 - Loading, Querying, & Filtering Data12mQuiz 2 - Catching Errors & Sorting10m

Week2

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 43sLoading data 1mInspecting data 1mQuerying data 47sJoining data 59sCode Along Exercise : Join data 6mSlicing rows 2mQuerying data using boolean indexing6mCode Along Exercise : Dive bar recommendation in Las Vegas 4mComputations - sum() 1mComputations - mean() 47sOther methods 26sUpdating & creating data 43sCode Along Exercise : Add rating column 1m

5 readings

Module 2 Resources (DOWNLOAD RELEVANT CODE AND/OR DATA FILES FOR THIS MODULE HERE)5mHomework 2 - Instructions10mCasting Data5mCleaning data & dealing with missing values3mHomework 3 - Instructions10m

2 practice exercises

Quiz 3 - Loading, Inspecting, & Querying Data10mQuiz 4 - Joining & Filtering Data10m

Week3

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 groups51sThe numpy library 48sPivot tables 29sUsing an index 41sCode Along Exercise : Average review count and rating2mAggregate functions2mJupyter notebook magic functions 21sThe matplotlib library 27sHistograms 36sHistograms Coding Demonstration : To show distribution of data 28sHistograms Coding Demonstration : Preparing data 1mHistograms Coding Demonstration : Setting options for PyPlot 1mHistograms Coding Demonstration : Displaying the visualization 3mScatterplots 34sScatterplots Coding Demonstration : To compare data points on different dimensions12sScatterplots Coding Demonstration : Preparing data 1mScatterplots Coding Demonstration : Setting options for PyPlot 2mScatterplots Coding Demonstration : Displaying the visualization 1m

5 readings

Module 3 Resources (DOWNLOAD RELEVANT CODE AND/OR DATA FILES FOR THIS MODULE HERE)5mHomework 4 - Instructions10mBar charts and plotting pivot tables7mFor reference: Seaborn2mHomework 5 - Instructions10m

2 practice exercises

Quiz 5 - Summarizing Data10mQuiz 6 - Visualizing Data12m

Reviews

4.6

84 reviews

5 stars
69.93%
4 stars
21.56%
3 stars
4.90%
2 stars
1.63%
1 star
1.96%

TOP REVIEWS FROM DATA ANALYSIS USING PYTHON

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 KGApr 12, 2021

Excellent course. Assignments /home work explaination need to be rethought. Special thanks to Jahnavi for helping through out the course.

by EBJan 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.

by LHMay 24, 2021

I'd like for this to be a little more in-depth. I had fun with the data visualisations. However, probably more of manipulating the data would be good.

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

About this Course

What you will learn

Skills you will gain

Instructor

Brandon Krakowsky

Offered by

University of Pennsylvania

Start working towards your Master's degree

Syllabus - What you will learn from this course

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

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

Module 3 : Summarizing & Visualizing Data

Reviews

TOP REVIEWS FROM DATA ANALYSIS USING PYTHON

About the Introduction to Programming with Python and Java Specialization

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Data Analysis Using Python

About this Course

What you will learn

Skills you will gain

Instructor

Brandon Krakowsky

Offered by

University of Pennsylvania

Start working towards your Master's degree

Syllabus - What you will learn from this course

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

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

Module 3 : Summarizing & Visualizing Data

Reviews

TOP REVIEWS FROM DATA ANALYSIS USING PYTHON

About the Introduction to Programming with Python and Java Specialization

Frequently Asked Questions

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Learn Something New

Popular Data Science Courses

Popular Computer Science & IT Courses

Popular Business Courses

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Community

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