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Mateo Prigl

Mastering Python’s containers is key to tackling complex data structures efficiently. This course will teach you how to utilize Python's built-in and specialized container types for optimal data management and manipulation.

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Mastering Python’s containers is key to tackling complex data structures efficiently. This course will teach you how to utilize Python's built-in and specialized container types for optimal data management and manipulation.

In today's fast-paced world of programming, handling and organizing data efficiently is a challenge that every developer faces. In this course, Python Collections, you’ll learn how to optimize and enhance your data handling skills in Python. First, you’ll explore the foundational aspects of Python's built-in container types: lists, dictionaries, tuples, and sets, understanding their unique characteristics and best use cases. Next, you’ll discover advanced dictionary types such as defaultdict, OrderedDict, and Counter, diving into their specialized functionalities that streamline common programming tasks. Finally, you’ll learn how to leverage specialized collection classes like namedtuple, ChainMap, and deque, enhancing the efficiency and readability of your code. When you’re finished with this course, you’ll have the skills and knowledge of Python's container data types needed to create elegant, efficient solutions in your programming projects.

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What's inside

Syllabus

Course Overview
Utilizing Built-in Containers
Improving Efficiency with Advanced Dictionaries
Using Specialized Collection Classes
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Customizing Built-in Data Types

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores fundamental data structures, which underpins most of computer science
Taught by experts who are widely recognized within the developer community
Builds a solid foundation for developers seeking to enhance their data structures skills
Provides comprehensive coverage of Python's built-in and specialized container types

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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 Collections with these activities:
Attend Python community meetups
Connect with other Python enthusiasts to exchange knowledge and learn about trends in Python containers.
Show steps
  • Find local Python community meetups.
  • Attend meetups and participate in discussions.
  • Network with other Python developers.
Show all one activities

Career center

Learners who complete Python Collections will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers are responsible for developing and deploying machine learning models. Python is used throughout this process, and this course in Python Collections provides a strong foundation necessary to succeed in this role.
Data Scientist
Data Scientists use a variety of programming languages, including Python, to build models and solve complex problems. This course provides the Python skills for organizing and manipulating data, essential for building machine learning models.
Data Architect
Data Architects design and manage data systems. Python is increasingly used in this role for tasks such as data modeling, data quality management, and data governance. This course in Python Collections provides a solid foundation for Python programming, with particular relevance to data management tasks.
Web Developer
Web Developers use Python for server-side programming and data analysis. This course, Python Collections, provides a strong foundation for the Python programming skills required for this role.
Data Engineer
Data Engineers use Python in the preparation of data for analysis, as well as for building and maintaining data pipelines and infrastructure. This course, with its emphasis on organizing and manipulating data, could prove to be a valuable stepping stone into this role.
Computer Programmer
Computer Programmers use Python for a wide range of tasks, including data analysis, web development, and machine learning. This course, Python Collections, provides a solid foundation for Python programming, with particular relevance to data-related tasks.
Data Analyst
Data Analysts use Python skills like data cleansing, manipulation, and analysis to help organizations gain insights from data. This course, Python Collections, can help build a foundation for the specialized programming skills required for this role.
Software Engineer
Software Engineers use Python for many purposes, including web development, data analysis, and machine learning. This course helps build a foundation in data structures, preparing one to use Python for a variety of tasks.
Database Administrator
Database Administrators use Python for database management tasks, such as data import and export, schema management, and performance tuning. While this course does not focus on databases, it provides a solid foundation for Python programming, which is widely used in this role.
Statistician
Statisticians use Python for data analysis, modeling, and forecasting. This course in Python Collections may be useful for building a foundation in Python programming, but it does not focus on the statistics and probability that is central to this role.
Quantitative Analyst
Quantitative Analysts use Python for data analysis, modeling, and risk management. This course, Python Collections, may be useful for building a foundation in Python programming, though it does not focus on the finance or statistics that is central to this role.
Financial Analyst
Financial Analysts use Python for data analysis and financial modeling. This course, Python Collections, may be useful for building a foundation in Python programming, but it does not cover the finance or accounting that is central to this role.
Business Analyst
Business Analysts use Python for data analysis and visualization. This course, Python Collections, may be useful for building a foundation in Python programming, but it does not cover the business analysis skills required for this role.
Actuary
Actuaries use Python for data analysis, modeling, and risk management. This course, Python Collections, may be useful for building a foundation in Python programming, but it does not focus on the actuarial science that is central to this role.
Product Manager
Product Managers use Python for data analysis and user research. This course, Python Collections, may be useful for building a foundation in Python programming, but it does not cover the product management skills required for this role.

Reading list

We've selected 11 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 Python Collections.
Provides a comprehensive overview of data structures and algorithms in Python. It valuable resource for both beginners and experienced programmers who want to learn more about data management and manipulation in Python.
Practical guide to Python collections. It good choice for programmers who want to learn more about the different types of collections available in Python and how to use them effectively.
Guide to writing clean and maintainable code. It valuable resource for programmers of all levels who want to learn more about how to write code that is easy to read, understand, and maintain.
Classic guide to design patterns in object-oriented programming. It valuable resource for programmers who want to learn more about how to design and implement reusable and maintainable code.
Guide to web development with Django. It valuable resource for programmers who want to learn more about how to design and implement web applications with Django.
Guide to web development with Flask. It valuable resource for programmers who want to learn more about how to design and implement web applications with Flask.
Guide to machine learning with Python. It valuable resource for programmers who want to learn more about how to use machine learning to solve real-world problems.
Guide to natural language processing with Python. It valuable resource for programmers who want to learn more about how to use natural language processing to analyze text data.
Classic guide to design patterns in object-oriented programming. It valuable resource for programmers who want to learn more about how to design and implement reusable and maintainable code.

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