Python Data Structures from Coursera

What's inside

Syllabus

Chapter Six: Strings

In this class, we pick up where we left off in the previous class, starting in Chapter 6 of the textbook and covering Strings and moving into data structures. The second week of this class is dedicated to getting Python installed if you want to actually run the applications on your desktop or laptop. If you choose not to install Python, you can just skip to the third week and get a head start.

Unit: Installing and Using Python

In this module you will set things up so you can write Python programs. We do not require installation of Python for this class. You can write and test Python programs in the browser using the "Python Code Playground" in this lesson. Please read the "Using Python in this Class" material for details.

Chapter Seven: Files

Up to now, we have been working with data that is read from the user or data in constants. But real programs process much larger amounts of data by reading and writing files on the secondary storage on your computer. In this chapter we start to write our first programs that read, scan, and process real data.

Chapter Eight: Lists

As we want to solve more complex problems in Python, we need more powerful variables. Up to now we have been using simple variables to store numbers or strings where we have a single value in a variable. Starting with lists we will store many values in a single variable using an indexing scheme to store, organize, and retrieve different values from within a single variable. We call these multi-valued variables "collections" or "data structures".

Chapter Nine: Dictionaries

The Python dictionary is one of its most powerful data structures. Instead of representing values in a linear list, dictionaries store data as key / value pairs. Using key / value pairs gives us a simple in-memory "database" in a single Python variable.

Chapter Ten: Tuples

Tuples are our third and final basic Python data structure. Tuples are a simple version of lists. We often use tuples in conjunction with dictionaries to accomplish multi-step tasks like sorting or looping through all of the data in a dictionary.

Graduation

To celebrate your making it to the halfway point in our Python for Everybody Specialization, we welcome you to attend our online graduation ceremony. It is not very long, and it features a Commencement speaker and very short commencement speech.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Taught by Charles Russell Severance, who is widely recognized for Python development and education

Teaches the foundational Python data structures to effectively perform data analysis

Provides step-by-step instruction on key concepts and practical applications

Covers real-world data analysis scenarios to enhance understanding and make the concepts relatable

Emphasizes the use of Python built-in data structures for efficient and effective data processing

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python Data Structures with these activities:

Organize Course Materials for Future Reference

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Compile and organize course materials such as notes, assignments, and quizzes for easy access and future review.

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Create a dedicated folder or notebook for course materials.
Organize materials by topic or week.
Review materials periodically to reinforce learning.

Participate in Peer Coding Sessions

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Engage in peer coding sessions to collaborate, share knowledge, and collectively solve programming challenges.

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Join or create a peer coding group or forum.
Participate in discussions and ask questions on specific coding topics.
Collaborate on coding projects and provide feedback to peers.

Delve into Python File Handling Operations

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Follow guided tutorials to grasp the fundamentals and advanced techniques of file handling operations in Python.

Browse courses on Files

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Study tutorials on file open, read, write, and close operations.
Practice working with text and binary files.
Explore techniques for handling large files and optimizing file operations.

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Practice with Lists and Dictionaries Data Structures

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Practice working with lists and dictionaries data structures to solidify understanding of their usage and implementation.

Browse courses on Lists

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Create a list of strings and perform operations like indexing, slicing, and concatenation.
Create a dictionary of key-value pairs and perform operations like accessing, adding, and deleting elements.
Solve programming problems that involve manipulating lists and dictionaries.

Explore Advanced String Manipulation Techniques

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Follow guided tutorials to enhance understanding of advanced string manipulation techniques and their applications.

Browse courses on Strings

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Study tutorials on regular expressions and their use in string matching and processing.
Practice using string formatting methods to create complex and dynamic strings.
Explore advanced string algorithms and their implementation in Python.

Develop a Python Script for Data Visualization

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Create a Python script that utilizes libraries like Matplotlib or Seaborn to visualize data and enhance understanding of data patterns and trends.

Browse courses on Data Visualization

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Choose a dataset and gather necessary data.
Write a Python script using Matplotlib or Seaborn to create visualizations like bar charts, line graphs, or scatter plots.
Customize the visualizations by adjusting axis labels, colors, and styles.
Interpret the visualizations and draw insights from the data.

Read 'Python for Data Analysis'

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Review a comprehensive book on Python for data analysis to gain a deeper understanding of data manipulation and analysis techniques.

View Python for Data Analysis on Amazon

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Read chapters related to data structures, file handling, and data analysis.
Work through the practice exercises and examples provided in the book.
Apply the concepts learned to real-world data analysis projects.

Career center

Learners who complete Python Data Structures will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts evaluate and interpret data, and make insights and recommendations. With the aid of tools like Python, they help prevent issues, identify trends, and develop new products and services. This course can help build a foundation in Python for working with data structures, a core aspect of Data Analysis.

See salaries and explore the career path for Data Analyst

Data Scientist

Data Scientists gather and analyze data to identify meaningful insights and trends. Proficiency in Python is helpful because many of the tools used in Data Science, such as NumPy and Pandas, operate within the Python ecosystem. This course helps build a foundation in core Python data structures in support of this work.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers develop and maintain machine learning models. The use of Python in Machine Learning is very widespread, and thus a strong command of Python's data structures is necessary.

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Data Engineer

Data Engineers build, maintain, and improve data pipelines. Familiarity with Python's data structures is very important, as Data Engineers use them to build a wide variety of data pipelines.

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Software Engineer

Software Engineers design, build, and improve software solutions. Proficient knowledge of Python and its data structures is required, as it is one of the most popular and in-demand programming languages used by companies today. This course provides practical experience working with Python's core data structures.

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Web Developer

Web Developers build and maintain websites and web applications. Python is commonly used for web development, particularly for backend development. Familiarity with Python's data structures is fundamental for this role.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical modeling to analyze risk and make investment decisions. Proficient knowledge of Python and its data structures is a requirement for this role, as Python is widely used in the finance industry.

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Business Analyst

Business Analysts help businesses understand their data and make better decisions. Business Analysts use a variety of tools and techniques, including Python, to analyze data and identify trends. This course can help build a foundation in Python and its data structures, which are essential for the role.

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Product Manager

Product Managers are responsible for the development and launch of new products. They work with engineers, designers, and marketers to bring products to market. Familiarity with Python and its data structures may be helpful for organizing and analyzing product data.

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Software Tester

Software Testers test software to ensure that it meets requirements and is free of defects. Familiarity with Python and its data structures may be helpful for developing and executing test cases.

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Database Administrator

Database Administrators manage and maintain databases. Familiarity with Python and its data structures may be helpful for optimizing database performance and managing data.

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Information Security Analyst

Information Security Analysts protect computer systems and networks from cyber attacks. Familiarity with Python and its data structures may be helpful for developing and implementing security solutions.

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Technical Writer

Technical Writers create documentation for software and other technical products. Familiarity with Python and its data structures may be helpful for understanding the products being documented.

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IT Support Specialist

IT Support Specialists provide technical support to users of computers and networks. Familiarity with Python and its data structures may be helpful for troubleshooting technical issues.

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Computer Programmer

Computer Programmers write and maintain computer programs. Familiarity with Python and its data structures is essential for this role.

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