BiteSize Python for Absolute Beginners: Data Structures from Coursera

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Syllabus

The List Data Structure

This module introduces the list as a built-in data structure in Python. It covers the basics of what a list is, how to create lists, including heterogeneous lists (lists containing different data types), and how to access, slice, and manipulate them. Additionally, learners will explore list comprehension, a powerful Pythonic way to work efficiently with lists.

The Tuple Data Structure

This module explores the tuple, a built-in data structure in Python. It covers what a tuple is, how to create one, and how to work with heterogeneous tuples (containing elements of different types). Learners will learn how to access elements by index and through iteration, slice tuples, and understand the concept of tuple comprehension for efficient data handling.

The Set Data Structure

This module introduces the set, a built-in data structure in Python that stores unique, unordered elements. It covers what a set is, how to create one, and how to manage elements within a set. The module also explores set operations (such as union, intersection, and difference), common set methods, and set comprehension for efficient data manipulation.

The Dictionary Data Structure

This module focuses on the dictionary (dict), a built-in Python data structure that stores key-value pairs. It covers what a dictionary is, how to create one, and how to access its elements using keys. Learners will explore common dictionary methods to manipulate data, and the module concludes with an introduction to dictionary comprehension for efficient data creation and processing.

Data Structure Case Studies

In this module, students will apply their knowledge of Python’s built-in data structures—list, tuple, set, and dictionary—by working on a real-life case study involving a grade book for students. They will use each of the data structures to store and manipulate the grade data, allowing them to practice and improve their understanding while comparing the advantages and limitations of each structure.

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Provides a practical case study involving a grade book, allowing learners to apply their knowledge of data structures to a relatable real-world scenario

Explores list comprehension, a powerful and Pythonic way to work efficiently with lists, which is a valuable skill for any aspiring Python programmer

Focuses on creating, accessing, and manipulating Python's built-in data structures, which are fundamental skills for any aspiring Python programmer

University of Colorado Boulder publishes this course, which may give learners assurance that the material is accurate and up-to-date

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 BiteSize Python for Absolute Beginners: Data Structures with these activities:

Review Basic Python Syntax

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Reinforce your understanding of fundamental Python syntax, including variable assignment, loops, and conditional statements, to prepare for working with data structures.

Browse courses on Python Syntax

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Review online Python tutorials.
Practice writing simple Python scripts.
Complete basic Python exercises.

Review 'Python Crash Course'

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Solidify your understanding of Python fundamentals by working through the exercises and projects in 'Python Crash Course'.

View Python Crash Course, 2nd Edition: A Hands-On,... on Amazon

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Read the chapters on basic Python syntax and data types.
Complete the exercises at the end of each chapter.
Work through one of the project-based tutorials.

Implement Data Structure Operations

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Practice implementing common operations on lists, tuples, sets, and dictionaries to reinforce your understanding of their unique characteristics.

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Implement functions to add, remove, and search elements in lists.
Create and manipulate tuples with different data types.
Perform set operations like union, intersection, and difference.
Create and access dictionaries with various key-value pairs.

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Create a Cheat Sheet for Python Data Structures

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Synthesize your knowledge by creating a concise cheat sheet summarizing the key features, methods, and use cases of each data structure.

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Summarize the key characteristics of lists, tuples, sets, and dictionaries.
List common methods for each data structure with examples.
Include examples of list, set, and dictionary comprehensions.

Build a Simple Inventory Management System

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Apply your knowledge of data structures by building a project that utilizes lists, tuples, sets, and dictionaries to manage inventory data.

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Design the data structures to store inventory items and their attributes.
Implement functions to add, update, and remove items from the inventory.
Create a user interface to interact with the inventory system.

Dive into Python 3

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Deepen your understanding of Python's capabilities and best practices by reading 'Dive into Python 3'.

View Dive Into Python 3 on Amazon

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Read the chapters on data structures and algorithms.
Experiment with the code examples provided in the book.
Try to implement some of the advanced techniques in your own projects.

Tutor other students

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Reinforce your understanding of data structures by helping other students who are struggling with the material.

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Offer assistance to classmates who are having difficulty with assignments.
Explain concepts in your own words to solidify your understanding.
Answer questions in online forums related to Python data structures.

Career center

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

Data Scientist

Data scientists analyze large amounts of data to discover trends and build predictive models. They often use Python for their work, and this course helps build a foundation in core data structures which is useful for them. Specifically, the course covers Python lists, tuples, sets, and dictionaries, which are crucial data structures for any data scientist. The course also includes a real-world case study, where learners will improve their skills by applying these data structures in a concrete scenario. This course is a great place to begin learning to be a data scientist.

See salaries and explore the career path for Data Scientist

Data Analyst

A data analyst uses programming to examine and interpret data to provide insights and solutions to business problems, and this course may be useful for that goal. This course focuses on the Python programming language and its core data structures which are integral in the life of a data analyst. Specifically, a data analyst needs to be able to create, access, and manipulate data using lists, tuples, sets, and dictionaries, all areas that this course covers. The case study that learners complete using these structures will help build a foundation for the kinds of challenges a data analyst faces on the job.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine learning engineers build and deploy machine learning models. These models require large datasets, and this course helps build a foundation in data manipulation using Python, which may be useful for this role. Working with lists, tuples, sets, and dictionaries is integral to data processing for machine learning models. This course offers in-depth coverage of these data structures as well as a case study where they can be used in a real-world application. The emphasis on practical application makes this course a good place to start for any machine learning engineer.

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Quantitative Analyst

Quantitative analysts, often working in the financial sector, use mathematical models and statistical methods to analyze complex data. The analyst creates and uses advanced algorithms to inform business decisions and strategic planning. This course helps build a foundation in Python's data structures, which are relevant to the work of a quantitative analyst. Specifically, the course teaches how to create, access, and manipulate lists, tuples, sets, and dictionaries. These skills, practiced in this course's case study, should prove very valuable in a quantitative analyst role.

See salaries and explore the career path for Quantitative Analyst

Research Engineer

Research engineers design and conduct experiments, develop prototypes, and analyze results, often using programming tools like Python. This course helps build a foundation in data structures that any research engineer may find helpful. The course explains Python lists, tuples, sets, and dictionaries in depth, which are very useful for the kind of work a research engineer does. The course's practical case study provides helpful experience for any research engineer looking to improve their technical skills.

See salaries and explore the career path for Research Engineer

Software Developer

Software developers design, create, and test software systems and this course may be useful for that goal. The course's in-depth exploration of Python's data structures provides valuable practical skills for any aspiring software developer. A key aspect of software development is the use of lists, tuples, sets, and dictionaries to organize and manage data. A software developer who takes this course will learn how to manipulate them effectively. This course's exploration of a case study, using each of the data structures, helps build a foundation for more complex software projects.

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Operations Research Analyst

Operations research analysts use analytical and mathematical techniques to improve efficiency and effectiveness in organizations and this course helps build a foundation in programming and data manipulation using Python which is useful for the job. The course focuses on core data structures such as lists, tuples, sets, and dictionaries, all of which are necessary to model complex systems and datasets. Operations research analysts will find this especially helpful when formulating and testing the effectiveness of different algorithms. This course includes a case study which may improve relevant skills.

See salaries and explore the career path for Operations Research Analyst

Database Administrator

A database administrator is responsible for organizing, storing and securing data. The role also involves developing and maintaining databases of varying complexity. This course helps build a foundation in organizing data using Python data structures such as lists, tuples, sets, and dictionaries. This course teaches database fundamentals including creating, accessing, and manipulating data sets, all of which will be valuable to a database administrator. The case study portion will also help hone the applied skills of any database administrator.

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Bioinformatician

Bioinformaticians analyze biological data using computational tools and techniques. This course may be useful for them, as they frequently rely on Python to perform data analysis. Bioinformaticians often work with lists, tuples, sets, and dictionaries when processing DNA sequences or other biological data. Any person who wishes to be a bioinformatician should try this course, as they provide a good introduction to the data structures used in these sorts of applications. The course's real-world case study using these data structures will be particularly valuable.

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Statistician

Statisticians collect, analyze, and interpret data to provide insights and solutions to problems. Often, statisticians use programming tools, and this course in Python may be useful for them. The course covers Python's core data structures, including lists, tuples, sets, and dictionaries, which are necessary to prepare any data for analysis. The case study provided helps statisticians improve their practical skills, and is particularly relevant to this role. A statistician who has taken this course will be able to more effectively manipulate datasets using Python.

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Information Architect

Information architects organize and structure information in ways that make it accessible and usable. This course may be useful for them, as learning to work with lists, tuples, sets, and dictionaries helps build a foundation in structuring data. The information architect relies on an understanding of how data is structured, stored, and accessed, and this course explores exactly that topic. The case study, with its emphasis on practical application, will be particularly valuable to any person who wishes to become an information architect, as it gives them real-world experience.

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Research Scientist

Research scientists perform experiments, analyze data, and publish findings. This course may be useful for this career, as many scientists need to be able to manipulate data and create experiments using tools such as Python. This course focuses on lists, tuples, sets, and dictionaries, all of which are critical tools for any research scientist with computational needs. The practical case study, using these data structures, helps any research scientist improve their data manipulation skills.

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Financial Analyst

Financial analysts analyze financial data, provide recommendations, and help in strategic planning. Many financial analysts rely on data manipulation skills, and this course will be useful for them. This course introduces Python and its built-in data structures including lists, tuples, sets, and dictionaries. These data structures are very relevant for organizing financial data to perform analyses, an area that this course prepares learners for. The case study will also allow financial analysts to improve their real-world data manipulation skills.

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Web Developer

Web developers create and maintain websites. This course's in-depth look at Python and its built-in data structures are relevant to this kind of work. While most web developers do not use Python for front-end development, there is significant use of Python for back-end development, and these skills may be very helpful. The lists, tuples, sets, and dictionaries covered in the course often form the foundation of databases, and the case study will allow the web developer to hone relevant skills.

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Technical Writer

Technical writers create documentation for technical products, including software and hardware. This course, though not directly related to writing, may be useful to a technical writer who wishes to document Python code. A deeper understanding of Python, its data structures including lists, tuples, sets, and dictionaries, and its use will help a technical writer better describe the code being documented. This course also includes a case study that allows technical writers to better understand how Python code works.

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BiteSize Python for Absolute Beginners

Data Structures

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