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There are 4 modules in this course
In this course, you'll explore loops, which repeat a portion of code until a process is complete. You’ll learn how to work with different kinds of iterative or repeating code, such as for loops and while loops. Then, you'll explore strings, which are sequences of characters like letters or punctuation marks. You’ll learn how to manipulate strings by indexing, slicing, and formatting them.
By the end of this course, you will be able to:
• Describe how to manipulate strings using techniques such as concatenating, indexing, slicing, and formatting
• Summarize the syntax of the range() function
• Explain the purpose and logic of iterative statements such as for loops and while loops
You'll explore loops, which repeat a portion of code until a process is complete. You’ll learn how to work with different kinds of iterative or repeating code, such as while loops.
What's included
3 videos1 reading1 assignment3 ungraded labs
Show info about module content
3 videos•Total 13 minutes
Introduction to loops and strings•1 minute
Michelle: Approach problems with an analytical mindset•3 minutes
Introduction to while loops•9 minutes
1 reading•Total 8 minutes
Loops, break, and continue statements•8 minutes
1 assignment•Total 6 minutes
Test your knowledge: While loops •6 minutes
3 ungraded labs•Total 50 minutes
Annotated follow-along guide: Loops and strings•20 minutes
Activity: While loops•20 minutes
Exemplar: While loops•10 minutes
For loops
Module 2•1 hour to complete
Module details
You'll explore for loops, another kind of iterative or repeating code.
What's included
2 videos1 reading1 assignment2 ungraded labs
Show info about module content
2 videos•Total 8 minutes
Introduction to for loops•4 minutes
Loops with multiple range() parameters•4 minutes
1 reading•Total 8 minutes
For loops•8 minutes
1 assignment•Total 6 minutes
Test your knowledge: For loops •6 minutes
2 ungraded labs•Total 30 minutes
Activity: For loops•20 minutes
Exemplar: For loops•10 minutes
Strings
Module 3•1 hour to complete
Module details
You'll explore strings, which are sequences of characters like letters or punctuation marks. You’ll learn how to manipulate strings by indexing, slicing, and formatting them.
What's included
3 videos2 readings1 assignment2 ungraded labs
Show info about module content
3 videos•Total 16 minutes
Work with strings•4 minutes
String slicing•7 minutes
Format strings•5 minutes
2 readings•Total 16 minutes
String indexing and slicing•8 minutes
String formatting and regular expressions•8 minutes
1 assignment•Total 6 minutes
Test your knowledge: Strings•6 minutes
2 ungraded labs•Total 30 minutes
Activity: Strings•20 minutes
Exemplar: Strings•10 minutes
Review: Loops and strings
Module 4•1 hour to complete
Module details
Review everything you’ve learned and take the final assessment.
What's included
1 reading1 assignment
Show info about module content
1 reading•Total 10 minutes
Wrap-up•10 minutes
1 assignment•Total 50 minutes
Course 3 challenge: Loops and strings•50 minutes
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Organizations of all types and sizes have business processes that generate massive volumes of data. Every moment, all sorts of information gets created by computers, the internet, phones, texts, streaming video, photographs, sensors, and much more. In the global digital landscape, data is increasingly imprecise, chaotic, and unstructured. As the speed and variety of data increases exponentially, organizations are struggling to keep pace.
Data science is part of a field of study that uses raw data to create new ways of modeling and understanding the unknown. To gain insights, businesses rely on data professionals to acquire, organize, and interpret data, which helps inform internal projects and processes. Data scientists rely on a combination of critical skills, including statistics, scientific methods, data analysis, and artificial intelligence.
What do data professionals do?
A data professional is a term used to describe any individual who works with data and/or has data skills. At a minimum, a data professional is capable of exploring, cleaning, selecting, analyzing, and visualizing data. They may also be comfortable with writing code and have some familiarity with the techniques used by statisticians and machine learning engineers, including building models, developing algorithmic thinking, and building machine learning models.
Data professionals are responsible for collecting, analyzing, and interpreting large amounts of data within a variety of different organizations. The role of a data professional is defined differently across companies. Generally speaking, data professionals possess technical and strategic capabilities that require more advanced analytical skills such as data manipulation, experimental design, predictive modeling, and machine learning. They perform a variety of tasks related to gathering, structuring, interpreting, monitoring, and reporting data in accessible formats, enabling stakeholders to understand and use data effectively. Ultimately, the work of data professionals helps organizations make informed, ethical decisions.
Do I need to take the course in a certain order?
We highly recommend taking the courses in the order presented, as the content builds on information from earlier courses. This is the third course in a series of six courses that make up the Google Data Analysis with Python Specialization.
When will I have access to the lectures and assignments?
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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.
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.