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Updated in [June 30th, 2023]

Computing in Python III: Data Structures is a course designed to build on existing knowledge of conditionals, loops, and functions by introducing complex Python data structures. This course is organized into five chapters, each covering a different data structure. These include strings, lists, dictionaries, and file input and output. By the end of the course, students will be able to write complex programs in Python that process and persist complex data structures.

The course is comprised of several parts. Instruction is delivered via a series of short (2-3 minute) videos. In between those videos, students will complete both multiple choice questions and coding problems to demonstrate their knowledge of the material that was just covered.

This course is ideal for students who are looking to expand their knowledge of Python and learn more about data structures. With the skills acquired in this course, students will be able to write programs that can process and persist complex data structures.

[Applications]
Upon completion of this course, students will be able to apply their knowledge of data structures to create more complex programs in Python. These programs can include gradebook applications that track and update averages over time, programs to calculate net force based on several force magnitudes and directions, and programs that can manipulate strings.

[Career Path]
The recommended career path for learners of Computing in Python III: Data Structures is a Data Scientist. Data Scientists are responsible for analyzing large amounts of data and using it to make informed decisions. They use a variety of tools and techniques to extract insights from data, such as machine learning, statistical analysis, and data visualization. Data Scientists must have a strong understanding of data structures and algorithms, as well as the ability to communicate their findings to stakeholders.

The development trend for Data Scientists is to become more specialized in their field. As data becomes more complex and the demand for data-driven decisions increases, Data Scientists must be able to understand and interpret data from a variety of sources. They must also be able to use advanced techniques such as deep learning and natural language processing to extract insights from data. Additionally, Data Scientists must be able to communicate their findings to stakeholders in a clear and concise manner.

[Education Path]
The recommended educational path for learners of this course is to pursue a degree in Computer Science. This degree will provide learners with a comprehensive understanding of the fundamentals of computing, including data structures, algorithms, programming languages, software engineering, and computer architecture. Learners will also gain an understanding of the development of computer systems, including hardware, software, and networks.

The development trend of this degree is to focus on the application of computing technology to solve real-world problems. This includes the development of artificial intelligence, machine learning, and data science. Additionally, the degree will focus on the development of new technologies, such as cloud computing, mobile computing, and the Internet of Things. Finally, the degree will focus on the ethical implications of computing technology, such as privacy, security, and data protection.