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David Joyner
Build on your existing knowledge of conditionals, loops, and functions by studying more about complex Python data structures, including strings, lists, dictionaries, and file input and output. Organized into five chapters, this course starts by covering the basics of data structures, then moves on to these four common data structures in Python:
Read more
Build on your existing knowledge of conditionals, loops, and functions by studying more about complex Python data structures, including strings, lists, dictionaries, and file input and output. Organized into five chapters, this course starts by covering the basics of data structures, then moves on to these four common data structures in Python:
Read more
Build on your existing knowledge of conditionals, loops, and functions by studying more about complex Python data structures, including strings, lists, dictionaries, and file input and output. Organized into five chapters, this course starts by covering the basics of data structures, then moves on to these four common data structures in Python:
- Strings let you perform far more complex reasoning with text.
- Lists let you process long lists of data, and even lists of lists of data for more complex reasoning.
- Dictionaries let you more clearly code for complex types of data, and even simulate some basic elements of object-oriented programming.
- File input and output brings your programs to life, allowing you to persist data across executions of the same program.
By the end of this course, you'll be able to write even more complex programs in Python that process and persist complex data structures. For example, you'll be able to write an ongoing gradebook application that tracks and updates your average over time, a program to calculate the net force based on several force magnitudes and directions, or a program that can turn a string like this into a StRiNg LiKe tHiS.
Structurally, the course is comprised of several parts. Instruction is delivered via a series of short (2-3 minute) videos. In between those videos, you'll complete both multiple choice questions and coding problems to demonstrate your knowledge of the material that was just covered.
Register for this course and see more details by visiting:
OpenCourser.com/course/1ua9fl/computing
What's inside
Learning objectives
- Strings, including advanced string methods.
- Tuples and lists, including multi-dimensional lists.
- File input and output, including multiple modes for file access.
- Dictionaries, including replicating object-oriented reasoning using dictionaries.
- Using control structures with data structures, such as looping over lists or error handling with files.
- Strings, including advanced string methods.
- Tuples and lists, including multi-dimensional lists.
- File input and output, including multiple modes for file access.
- Dictionaries, including replicating object-oriented reasoning using dictionaries.
- Using control structures with data structures, such as looping over lists or error handling with files.
Syllabus
Chapter 1. Data Structures. Building the fundamental types of data – Booleans, integers, floating point numbers, and characters -- into more complex strings, lists, and dictionaries that can be persisted in files.
Read more
Syllabus
Chapter 1. Data Structures. Building the fundamental types of data – Booleans, integers, floating point numbers, and characters -- into more complex strings, lists, and dictionaries that can be persisted in files.
Read more
Chapter 2. Strings. Working with series of characters that can represent plaintext messages, passwords, and more, including all the complexities of combining human language with programming code.
Chapter 3. Lists. Taking fundamental data types like strings, integers, and floats and organizing them into tuples or lists that can represent complex structures of data; or for added complexity, creating lists of lists to create 2-dimensional (or more) data structures.
Chapter 4. File Input and Output. Taking information stored in your code and persisting it in an external file that can last after the program has finished executing, or loading data from a file into a program for processing.
Chapter 5. Dictionaries. Organizing key-value pairs (very similar to variables and values) into higher-level structures that can be easily passed around or reused with some intuitive structure.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines Python data structures, a core component for modern coding
Taught by seasoned instructor David Joyner
Develops mastery of data structures
Builds upon foundational knowledge of conditionals, loops, and functions
Emphasizes practical utility with real-world examples
Covers file input and output, a necessary skill for data handling
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Reviews summary
Python data structures: comprehensive and engaging
Learners say "Computing in Python III: Data Structures" is largely positive, with engaging assignments, clear instruction, and a logical progression through Python data structures. This course is well received by learners, especially those new to Python or data structures.
The course is well-suited for learners new to programming or data structures.
"I have followed the XSeries of Computing in Python and about to start the final chapter. This is my first formal training in python and I now feel confident to start more difficult courses."
"This course give me a good space for practicing and implementing new skills with tests and exercises , I learn a lot about dealing, and manipulate data structures."
"This is was a great course to follow for understanding data structures (in general)."
The course covers a wide range of topics related to Python data structures and their real-world applications.
"This course covers the basics of strings, lists, dictionaries and reading and writing to a text file."
"The programming tasks are well thought-out and provide a wide range of problems, mostly related to the real-world."
Practice problems are insightful and help build muscle memory.
"Tons and tons of quizzes and examples and coding problems that really help users build up muscle memory."
The material is well-explained and available in bite-sized chunks for beginners and those needing a refresher.
"The teaching is well balanced between (short) video presentations, textbook work and tests/programming exercises."
Some learners missed practice problems, discussion boards can be inactive, and the course rushed through some topics.
"And there is the problem, u don't have enough practice to be ready for final exams coding problems."
"The discussion boards are not all that active, but it's a sign of how robust the instruction, problem questions and explanations are that, well for the most part you won't need help from discussion boards."
"This class started great with lots of details, but feels like it was very rushed to complete."
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 Computing in Python III: Data Structures with these
activities:
Consolidate and Organize Course Materials
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Stay organized by compiling and organizing your course materials, including notes, assignments, quizzes, and exams, ensuring easy access and a clear understanding of the course content.
Show steps
-
Gather all relevant course materials, such as notes, assignments, quizzes, and exams.
-
Organize the materials into logical sections or categories.
-
Review and consolidate the materials, identifying key concepts and areas for further study.
Review Python Data Structures and File I/O Concepts
Show steps
Refresh your knowledge of Python data structures and file I/O by reviewing previous course materials, textbooks, or online resources.
Browse courses on
Data Structures
Show steps
-
Gather and review course notes, slides, and assignments related to data structures and file I/O.
-
Read relevant sections from the course textbook or other reference materials.
-
Complete practice problems or quizzes to reinforce your understanding.
Mentor Junior Python Developers
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Enhance your understanding by teaching and guiding junior Python developers, providing valuable support and reinforcing your own knowledge of data structures and file I/O.
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-
Identify opportunities to mentor junior Python developers, such as through online forums or local coding groups.
-
Share your knowledge and experience, providing guidance on data structures and file I/O.
-
Answer questions, review code, and provide constructive feedback.
Five other activities
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Show all eight activities
Practice Data Structures with Online Challenges
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Solve coding challenges involving strings, lists, dictionaries, and file input/output to enhance your understanding and proficiency in applying these data structures in Python programs.
Browse courses on
Data Structures
Show steps
-
Identify an online platform or resource for coding challenges.
-
Choose a challenge that involves the use of data structures, such as strings, lists, or dictionaries.
-
Solve the challenge by implementing the appropriate data structures and algorithms in Python.
-
Test and debug your code to ensure it meets the challenge requirements.
Explore Advanced String Manipulation Techniques
Show steps
Enhance your proficiency in string manipulation by following tutorials that cover advanced techniques, such as regular expressions, string formatting, and string operations.
Browse courses on
Strings
Show steps
-
Find online tutorials or resources on advanced string manipulation in Python.
-
Study the concepts and examples presented in the tutorials.
-
Implement the techniques in your own Python code and experiment with different scenarios.
Attend a Python Data Structures and File I/O Workshop
Show steps
Deepen your understanding and practical skills in data structures and file I/O by attending a specialized workshop led by experienced instructors.
Show steps
-
Search for and identify a Python workshop that focuses on data structures and file I/O.
-
Register for the workshop and attend all sessions.
-
Actively participate in exercises and discussions.
-
Apply the knowledge and techniques gained in the workshop to your own Python projects.
Develop a Python Program to Process Complex Data
Show steps
Demonstrate your understanding of complex data structures by building a Python program that processes and manipulates real-world data, such as parsing a large dataset or creating a data visualization.
Show steps
-
Identify a dataset or problem that requires complex data structures for processing.
-
Design and implement a Python program using appropriate data structures, such as lists, dictionaries, and file I/O.
-
Test and debug your program to ensure it processes the data accurately and efficiently.
-
Present your program and its results, showcasing your proficiency in data structures and Python programming.
Attend a Python Programming Bootcamp
Show steps
Enhance your overall Python programming skills, including data structures and file I/O, by participating in an intensive Python programming bootcamp.
Show steps
-
Identify and register for a reputable Python programming bootcamp.
-
Attend all bootcamp sessions and actively participate in exercises and discussions.
-
Complete assignments and projects to demonstrate your understanding and proficiency in Python.
Consolidate and Organize Course Materials
Show steps
Stay organized by compiling and organizing your course materials, including notes, assignments, quizzes, and exams, ensuring easy access and a clear understanding of the course content.
Show steps
Show steps
Show steps
- Gather all relevant course materials, such as notes, assignments, quizzes, and exams.
- Organize the materials into logical sections or categories.
- Review and consolidate the materials, identifying key concepts and areas for further study.
Review Python Data Structures and File I/O Concepts
Show steps
Refresh your knowledge of Python data structures and file I/O by reviewing previous course materials, textbooks, or online resources.
Browse courses on
Data Structures
Show steps
Show steps
Show steps
- Gather and review course notes, slides, and assignments related to data structures and file I/O.
- Read relevant sections from the course textbook or other reference materials.
- Complete practice problems or quizzes to reinforce your understanding.
Mentor Junior Python Developers
Show steps
Enhance your understanding by teaching and guiding junior Python developers, providing valuable support and reinforcing your own knowledge of data structures and file I/O.
Show steps
Show steps
Show steps
- Identify opportunities to mentor junior Python developers, such as through online forums or local coding groups.
- Share your knowledge and experience, providing guidance on data structures and file I/O.
- Answer questions, review code, and provide constructive feedback.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice Data Structures with Online Challenges
Show steps
Solve coding challenges involving strings, lists, dictionaries, and file input/output to enhance your understanding and proficiency in applying these data structures in Python programs.
Browse courses on
Data Structures
Show steps
Show steps
Show steps
- Identify an online platform or resource for coding challenges.
- Choose a challenge that involves the use of data structures, such as strings, lists, or dictionaries.
- Solve the challenge by implementing the appropriate data structures and algorithms in Python.
- Test and debug your code to ensure it meets the challenge requirements.
Explore Advanced String Manipulation Techniques
Show steps
Enhance your proficiency in string manipulation by following tutorials that cover advanced techniques, such as regular expressions, string formatting, and string operations.
Browse courses on
Strings
Show steps
Show steps
Show steps
- Find online tutorials or resources on advanced string manipulation in Python.
- Study the concepts and examples presented in the tutorials.
- Implement the techniques in your own Python code and experiment with different scenarios.
Attend a Python Data Structures and File I/O Workshop
Show steps
Deepen your understanding and practical skills in data structures and file I/O by attending a specialized workshop led by experienced instructors.
Show steps
Show steps
Show steps
- Search for and identify a Python workshop that focuses on data structures and file I/O.
- Register for the workshop and attend all sessions.
- Actively participate in exercises and discussions.
- Apply the knowledge and techniques gained in the workshop to your own Python projects.
Develop a Python Program to Process Complex Data
Show steps
Demonstrate your understanding of complex data structures by building a Python program that processes and manipulates real-world data, such as parsing a large dataset or creating a data visualization.
Show steps
Show steps
Show steps
- Identify a dataset or problem that requires complex data structures for processing.
- Design and implement a Python program using appropriate data structures, such as lists, dictionaries, and file I/O.
- Test and debug your program to ensure it processes the data accurately and efficiently.
- Present your program and its results, showcasing your proficiency in data structures and Python programming.
Attend a Python Programming Bootcamp
Show steps
Enhance your overall Python programming skills, including data structures and file I/O, by participating in an intensive Python programming bootcamp.
Show steps
Show steps
Show steps
- Identify and register for a reputable Python programming bootcamp.
- Attend all bootcamp sessions and actively participate in exercises and discussions.
- Complete assignments and projects to demonstrate your understanding and proficiency in Python.
Career center
Learners who complete Computing in Python III: Data Structures will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer develops and deploys machine learning models to solve problems and develop solutions for businesses. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to represent and manipulate data. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in machine learning, such as data preparation, model training, and model evaluation.
Data Scientist
Data Scientist
A Data Scientist uses complex data structures to solve problems and develop solutions for businesses. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and their uses. The course covers a variety of data structures, including strings, lists, dictionaries, and files, and how to use them to represent and manipulate data. This knowledge can be applied to a variety of tasks in data science, such as data cleaning, data analysis, and machine learning.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to design and implement software systems. The course covers a variety of data structures, including strings, lists, dictionaries, and files, and how to use them to represent and manipulate data. This knowledge can be applied to a variety of tasks in software engineering, such as designing data models, writing code, and testing software.
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, and interprets data to provide insights for businesses. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to represent and manipulate data. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in data analysis, such as data cleaning, data analysis, and data visualization.
Information Security Analyst
Information Security Analyst
An Information Security Analyst protects computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to protect computer systems and networks. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in information security, such as designing security systems, writing security code, and investigating security breaches.
Network Engineer
Network Engineer
A Network Engineer designs, develops, and maintains computer networks. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to design and implement computer networks. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in network engineering, such as designing network architectures, writing network code, and testing network performance.
Database Administrator
Database Administrator
A Database Administrator designs, develops, and maintains databases. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to design and implement databases. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in database administration, such as designing database schemas, writing queries, and managing database performance.
Computer Programmer
Computer Programmer
A Computer Programmer writes, tests, and maintains computer programs. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to write, test, and maintain computer programs. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in computer programming, such as designing program logic, writing code, and testing programs.
Web Developer
Web Developer
A Web Developer designs, develops, and maintains websites and web applications. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to design and implement web applications. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in web development, such as designing data models, writing code, and testing web applications.
Computer Systems Analyst
Computer Systems Analyst
A Computer Systems Analyst designs, develops, and maintains computer systems. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to design and implement computer systems. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in computer systems analysis, such as designing system architectures, writing system code, and testing system performance.
Project Manager
Project Manager
A Project Manager plans, organizes, and manages projects to achieve specific goals and objectives. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to plan, organize, and manage projects. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in project management, such as planning projects, scheduling tasks, and tracking progress.
Business Analyst
Business Analyst
A Business Analyst analyzes business processes and systems to identify areas for improvement. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to analyze business processes and systems. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in business analysis, such as gathering requirements, analyzing data, and developing solutions.
Technical Writer
Technical Writer
A Technical Writer creates and maintains technical documentation, such as user manuals, training materials, and white papers. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to create and maintain technical documentation. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in technical writing, such as writing user manuals, training materials, and white papers.
Quality Assurance Analyst
Quality Assurance Analyst
A Quality Assurance Analyst tests and evaluates software to ensure that it meets quality standards. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to test and evaluate software. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in quality assurance, such as writing test cases, executing tests, and analyzing test results.
Data Entry Clerk
Data Entry Clerk
A Data Entry Clerk enters data into computer systems. This course, Computing in Python III: Data Structures, may be useful for those looking to gain a foundational understanding of data structures and how to use them to enter data into computer systems. The course covers a variety of data structures, including strings, lists, dictionaries, and files. This knowledge can be applied to a variety of tasks in data entry, such as entering data from paper forms, entering data from electronic files, and verifying data accuracy.
For more career information including salaries, visit:
OpenCourser.com/course/1ua9fl/computing
Reading list
We've selected 18 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Computing in Python III: Data Structures.
Provides a comprehensive overview of data structures and algorithms in Python, making it an excellent resource for supplementing this course. It covers all the essential concepts, including strings, lists, dictionaries, and file input/output.
Save
Provides a deep dive into the Python programming language. It good choice for students who want to learn more about the Python programming language.
Provides a comprehensive overview of data structures and algorithms in Python. It good choice for students who want to learn more about data structures and algorithms in Python.
Teaches students how to use Python to automate tasks. It good choice for students who want to learn how to use Python for practical purposes.
Teaches students how to use Python for web development. It good choice for students who want to learn how to use Python for data science.
Save
Free online textbook that teaches students how to use Python for data analysis. It good choice for students who want to learn how to use Python for data science.
Save
Teaches students how to use Python for deep learning. It good choice for students who want to learn how to use Python for data science.
Teaches students how to use Python for machine learning. It good choice for students who want to learn how to use Python for data science.
Teaches students how to use Python for data analysis. It good choice for students who want to learn how to use Python for data science.
Save
Collection of recipes for solving common programming problems in Python. It good choice for students who want to learn more about Python or who want to find solutions to specific programming problems.
Save
Provides a comprehensive introduction to Python programming, covering data structures, algorithms, and object-oriented programming. It good choice for students who are new to Python or who want to review the basics.
This engaging book uses visual representations and everyday analogies to explain complex algorithms and data structures. It's a great way to develop a deeper understanding of these concepts.
This concise and practical book provides a quick overview of Python data structures, making it a useful reference for beginners who want to get up to speed quickly.
Save
Is an introduction to Python programming for beginners. It good choice for students who are new to programming or who want to learn Python for the first time.
Save
Visual introduction to Python programming. It good choice for students who learn best visually.
Fast-paced introduction to Python programming. It good choice for students who want to learn Python quickly.
Save
Beginner's guide to Python programming. It good choice for students who are new to programming or who want to learn Python for the first time.
Save
Offers advanced techniques for working with Python data structures. It covers topics such as optimizing performance, avoiding common pitfalls, and using advanced data structures like queues and stacks.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1ua9fl/computing
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Effort
9 to 10 hours per week for 5 weeks
Level
Introductory
Via
edX
Institution
The Georgia Institute of Technology
Instructor
David Joyner
Sessions
January 1, 2026
- January 1, 2027
January 1, 2025
- January 1, 2026
January 1, 2024
- December 31, 2024
Language
English
Transcript
English
This course belongs to a
collection
called
Introduction to Python Programming. It's comprised of four courses:
- Computing in Python I: Fundamentals and Procedural Programming
- Computing in Python II: Control Structures
- Computing in Python IV: Objects & Algorithms
- Computing in Python III: Data Structures (viewing)
Good to know
Examines Python data structures, a core component for modern coding
Taught by seasoned instructor David Joyner
Develops mastery of data structures
Builds upon foundational knowledge of conditionals, loops, and functions
Emphasizes practical utility with real-world examples
Covers file input and output, a necessary skill for data handling
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