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Daniel Bauer

This self-paced, asynchronous course is recommended for learners who want to establish a solid knowledge base in data structures and basic programming in Python.

Learners can expect to review the technical coursework as well as complete a self-assessment.

What's inside

Learning objectives

  • This course will enable students to:
  • Understand the components of python programs, including control structures, variables and data types and object oriented programming.

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Provides a strong foundation for beginners in data structures and basic programming in Python
Taught by Daniel Bauer, an experienced instructor in data structures and programming

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Reviews summary

Python programming and data structures foundation

According to students, this course provides a solid foundation in Python programming and data structures, with many appreciating the clear explanations and practical assignments that reinforce concepts. Learners highlight its effectiveness in demystifying object-oriented programming and preparing them for advanced topics. While praised for its self-paced format, a notable point raised is that it may require supplemental material for those with minimal or no prior Python experience, suggesting it's not ideal for absolute beginners. Overall, it's largely seen as a rewarding and valuable experience for developing core programming skills.
Offers flexibility but may limit direct instructor interaction.
"It's self-paced, which is great, but it also means less direct interaction when I had questions."
"I appreciated the flexibility of the self-paced format, which suited my schedule perfectly."
"This asynchronous course structure required self-discipline, but allowed me to deepen my understanding effectively."
Python basics felt rushed to some, while others found the pace suitable.
"The Python basics covered felt a bit rushed, so if you're a complete beginner, I think you might need supplemental material."
"I felt the pacing was just right for a self-paced format, allowing me to learn at my own speed."
"I think it tries to cover too much in a limited time, leading to some confusing parts."
Hands-on exercises deepen understanding and skill acquisition.
"The assignments really reinforce the concepts. I particularly enjoyed the section on linked lists and hash tables."
"I found the practical exercises essential for applying what I learned."
"The hands-on coding and projects were the strongest part of the course for me, making concepts stick."
Establishes a strong base in Python, data structures, and OOP.
"This course is absolutely fantastic for anyone looking to solidy their understanding of Python programming and fundamental data structures."
"I found this course excellent for strengthening core programming skills, especially the object-oriented programming section."
"As someone with prior programming experience, this course was perfect for formalizing my understanding of data structures and OOP in Python."
Not suitable for absolute beginners in Python programming.
"I struggled with this course. While the content outline seemed good, the delivery was not always beginner-friendly."
"I wouldn't recommend this to anyone starting from scratch. I felt it needs more basic content."
"If you're a complete beginner, you might need supplemental material for Python syntax to keep up with the pace."

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 Programming & Data Structures with these activities:
Complete an introductory Python tutorial
Guided tutorials offer a structured approach to learning the basics of Python, ensuring a solid foundation for the course.
Browse courses on Python
Show steps
  • Identify a reputable online tutorial or course.
  • Follow the tutorial step-by-step, completing all exercises and activities.
  • Take notes and ask questions as needed.
Review basic data structures
Revising basic data structures strengthens the foundation for understanding more complex data structures covered in the course, aiding in comprehension and retention.
Browse courses on Data Structures
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  • Review notes or materials from previous courses on data structures.
  • Go through online resources or tutorials on data structures.
  • Solve simple exercises or problems related to data structures.
Read 'Python Crash Course'
This book provides a comprehensive overview of Python, reinforcing concepts learned in the course and offering additional insights and examples.
Show steps
  • Purchase or borrow the book.
  • Read the book thoroughly, taking notes and highlighting important concepts.
  • Complete the exercises and activities included in the book.
Five other activities
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Show all eight activities
Join a study group for Python
Engaging in peer sessions provides opportunities for students to collaborate, discuss concepts, and work through challenges together, leading to improved understanding and retention.
Browse courses on Python
Show steps
  • Find a study group online or in your area.
  • Attend study sessions regularly and actively participate in discussions.
  • Share knowledge and assist other group members.
Solve Python coding challenges
Practice drills provide hands-on experience in applying Python concepts, enhancing understanding and solidifying skills.
Browse courses on Python
Show steps
  • Find online coding challenges or exercises.
  • Attempt to solve the challenges independently.
  • Review solutions and identify areas for improvement.
Organize course notes and materials
Organizing materials helps students stay on top of the course materials, making it easier to review and reinforce concepts.
Show steps
  • Gather all notes, handouts, slides, and assignments.
  • Create a system for organizing the materials, such as using folders or a digital note-taking app.
  • Review the organized materials regularly.
Build a simple Python project
Creating a project allows students to apply their Python skills in a practical setting, strengthening their understanding and developing their problem-solving abilities.
Browse courses on Python
Show steps
  • Identify a project idea that aligns with the course content.
  • Design the project, including the problem it solves and the features it will have.
  • Implement the project using Python code.
  • Test and debug the project to ensure it functions correctly.
Contribute to an open-source Python project
Participating in an open-source project provides practical experience in Python development, exposes students to real-world codebases, and fosters collaboration and problem-solving skills.
Browse courses on Python
Show steps
  • Identify an open-source Python project that aligns with your interests and skills.
  • Familiarize yourself with the project's codebase and documentation.
  • Identify an area where you can contribute, such as bug fixes or feature enhancements.
  • Submit a pull request to the project.

Career center

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

Reading list

We've selected 50 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 Programming & Data Structures.
Often referred to as "CLRS," this book comprehensive and widely-used textbook for undergraduate and graduate-level algorithms courses. It provides in-depth knowledge of data structures and algorithms, including their analysis and implementation. While it assumes some mathematical familiarity, it's an encyclopedic reference valuable for both learning and as a long-term resource.
Gathers hundreds of battle-tested recipes covering network programming, memory management, data structures, and functional decorators for veteran application developers.
Seminal work in the field of object-oriented design. It introduces 23 classic software design patterns that provide solutions to common design problems. While not a beginner's book, it is invaluable for deepening understanding and must-read for anyone serious about software architecture and design. It's widely referenced and considered a standard text for professional developers.
Delivers the canonical blueprint for numeric analysis from the creator of pandas, thoroughly detailing NumPy structures, data cleaning, and high-speed transformations.
Introduces clean architecture, domain-driven design, and event-driven microservices to Python developers, demonstrating repository patterns and dependency inversion.
This textbook focuses exclusively on the logic and design principles of programming, independent of a specific programming language. It provides in-depth coverage of pseudocode, flowcharts, and the fundamental control structures (sequence, selection, repetition) used to build algorithms. It is excellent for developing strong logical thinking and problem-solving skills essential for effective programming.
Demystifies programming for practical utility, guiding beginners through real-world automation projects including web scraping, spreadsheet generation, and file audits.
Focuses on static typing, structural subtyping, and defensive design techniques, demonstrating how modern type annotations prevent regressions in enterprise codebases.
This introductory programming textbook is specifically structured to teach fundamental concepts starting with control structures and progressing to objects. It provides clear explanations, numerous examples, and exercises to help beginners grasp the basics of programming logic and implementation in C++. It is commonly used in introductory programming courses.
Provides a comprehensive overview of variables in Python. It covers topics such as data types, scope, and memory management. It valuable resource for students and professionals who want to gain a deeper understanding of variables in Python.
Focusing on writing readable, maintainable, and well-structured code, this book is essential for any developer, regardless of their experience level. It emphasizes the importance of writing clean code within the context of object-oriented principles and is considered a foundational text for developing good programming habits. It highly recommended practical guide for students and professionals alike.
Provides a comprehensive overview of variables in JavaScript. It covers topics such as data types, scope, and memory management. It valuable resource for students and professionals who want to gain a deeper understanding of variables in JavaScript.
Provides a comprehensive overview of variables in Ruby. It covers topics such as data types, scope, and memory management. It valuable resource for students and professionals who want to gain a deeper understanding of variables in Ruby.
Offers a comprehensive treatment of data structures and algorithms, suitable for academic settings. It covers various data types and algorithms for sorting, searching, and processing. The book is known for its detailed explanations and includes an online portal with source code, making it a strong resource for solidifying understanding.
Unpacks professional testing methodologies using pytest, explaining fixture management, parameterized tests, coverage tracking, and automated CI test execution.
Delves into the complexities of data systems, covering various data models and their underlying principles. It's highly relevant for professionals and graduate students dealing with large-scale data, offering insights into how data types and structures impact system design, reliability, and scalability.
Offers practical advice on writing better code and becoming a more effective programmer. It emphasizes thinking critically about program design and structure, which directly involves the thoughtful use of control structures for clarity and maintainability. It's a highly recommended book for developers at all stages looking to improve their craft.
This textbook is suitable for advanced data structures or introductory graduate-level algorithm analysis courses. It bridges the gap between foundational data structures and more advanced analysis techniques. The book provides a rigorous and in-depth analysis of algorithms and their implementation in C++.
An excellent resource for understanding design patterns in a more accessible and engaging way. uses a visually rich format to explain complex concepts, making it suitable for undergraduate students and those new to design patterns. It complements 'Design Patterns' by providing a gentler introduction with practical examples.
Investigates advanced software craft, detailing packaging distribution, bytecode internals, scaling architectures, and maintainability across large distributed systems.
Is crucial for understanding how to improve the design of existing object-oriented code without changing its external behavior. It provides a catalog of refactorings and explains when and why to apply them. This practical guide for developers looking to maintain and evolve object-oriented systems.
Bridges volumetric point cloud analysis with Python, teaching LiDAR processing, spatial meshing, and 3D machine vision using modern scientific computing toolchains.
Presents a welcoming, foundational ramp into computational logic and programming, establishing syntax literacy, object modeling, and error handling for total beginners.
Affectionately known as the 'Dragon Book,' this comprehensive text on compiler design. Understanding data types is crucial in compiler construction for type checking and code generation. provides in-depth coverage of how data types are handled within the compilation process, making it essential for graduate students and professionals in programming languages and compilers. (Consider the latest edition).
While Java-specific, this book offers invaluable insights into object-oriented best practices and common pitfalls. It presents a collection of programming guidelines and rules of thumb that are broadly applicable to other object-oriented languages. This must-read for Java developers and highly recommended for anyone looking to write robust and efficient object-oriented code.
Provides 50 focused exercise routines and guided breakdowns designed to build instinctive muscle memory across collections, functional pipelines, algorithms, and file I/O.
An excellent introductory book to algorithms and data structures using clear illustrations and a friendly approach. It effectively demonstrates how control structures like loops and conditional statements are used within fundamental algorithms. is ideal for beginners looking for an accessible way to understand the practical application of control flow.
Another popular project-based introduction to Python programming. It quickly introduces fundamental concepts like variables, lists, classes, and loops and if statements (control structures). The hands-on approach helps beginners quickly gain a working understanding of how to use control flow in practical programming scenarios.
Tackles the full lifecycle of shipping models into production, covering feature store development, container packaging, drift detection, and continuous retraining.
Using Ruby as the examples language, this book provides a practical and accessible introduction to object-oriented design principles from an agile perspective. It focuses on creating clean, maintainable, and flexible code. is great for those learning OOP through Ruby or looking for a practical take on design.
This comprehensive book explores the design, implementation, and يَusages of programming languages. It includes detailed discussions on various control flow mechanisms found in different language paradigms and the trade-offs involved in their design. It is suitable for advanced students and professionals interested in the theoretical and practical aspects of language design.
Known as 'The Book' in the Rust community, this is the official guide to learning Rust. It extensively covers Rust's unique ownership and borrowing system, which core aspect of its approach to memory safety without a garbage collector. Understanding this is crucial for working with data effectively and safely in Rust, making it highly relevant for those interested in modern systems programming.
Serves as an introduction to designing algorithms and includes a comprehensive catalog of algorithms and data structures. It's a valuable reference for understanding different algorithmic techniques and when to apply them. It is suitable for both students and practitioners.
This comprehensive book widely respected introduction to modern C++. It covers the core language features, including fundamental and user-defined data types, classes, templates, and the Standard Library. It's an excellent resource for gaining a solid understanding of the C++ type system and is suitable for serious students and professionals. (Consider the latest edition).
This textbook offers a rigorous introduction to data structures and algorithms with implementations in C++. It covers a wide range of topics and is suitable for undergraduate computer science programs.
A foundational text covering the principles of object-oriented analysis and design. It introduces the Unified Modeling Language (UML) and provides a comprehensive approach to developing complex software systems using OOP. is valuable for students and professionals involved in the design phase of software development.
A classic and concise book that introduced the C programming language. It clearly explains fundamental programming concepts, including control flow statements. While not a recent publication, the principles of structured programming and the usage of control structures described are foundational and highly relevant to understanding many modern languages.
Practical guide to variables in programming. It covers topics such as variable types, scope, and memory management. It also provides numerous examples and exercises to help readers learn how to use variables effectively.
Provides a theoretical yet accessible introduction to database design based on the relational model. It explains the importance of normal forms in structuring data correctly, which is fundamental to working with databases. It's valuable for students and professionals who need a deeper understanding of the theory behind relational databases.
Explores object-oriented design principles and design patterns within the context of agile software development using C#. It provides practical guidance on how to apply these concepts to build robust and maintainable applications. It's a valuable resource for C# developers interested in clean design and agile methodologies.

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