Programming 101
An Introduction to Python for Educators
Jo Wakefield,
Lauren Hyams,
Laura Sach,
Philip Harney,
Beverley McCormick,
Martin O'Hanlon,
Michael Conterio,
Ross Exton,
Rebecca Franks,
Josh Crossman,
Ben Garside,
Diane Dowling,
and
Allen Heard
Jo Wakefield,
Lauren Hyams,
Laura Sach,
Philip Harney,
Beverley McCormick,
Martin O'Hanlon,
Michael Conterio,
Ross Exton,
Rebecca Franks,
Josh Crossman,
Ben Garside,
Diane Dowling,
and
Allen Heard
Topics Covered
- The core programming concepts of sequence, selection and repetition
- Using variables to store data
- When and how to use a ‘for’ loop, an ‘if’ statement, a ‘while’ loop, and functions
- Creating your own program to solve a simple problem
- The basics of Python syntax
- How to interpret error messages
Register for this course and see more details by visiting:
OpenCourser.com/course/i1rlp0/programming
Activities
Coming soon
We're preparing activities for
Programming 101: An Introduction to Python for Educators.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Programming 101: An Introduction to Python for Educators will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/i1rlp0/programming
Reading list
We haven't picked any books for this reading list yet.
Comprehensive guide to the basics of Python programming, covering data types, control flow, functions, object-oriented programming, and debugging.
Uses a creative and engaging approach to teach Python concepts, with a focus on visual learning and hands-on exercises.
Comprehensive guide to Python's data analysis ecosystem, including NumPy, Pandas, and Matplotlib, with a focus on practical applications.
Comprehensive guide to machine learning using Python, covering supervised and unsupervised learning, model evaluation, and deployment.
Comprehensive guide to deep learning using Python, covering neural networks, convolutional neural networks, and recurrent neural networks.
Concise and comprehensive reference to the Python language, covering syntax, built-in functions and objects, and advanced topics.
Deep dive into Python's advanced features, covering metaprogramming, decorators, generators, and concurrency.
Collection of practical recipes and solutions for common Python programming tasks, covering a wide range of topics.
Is an introductory text to Python programming, with a focus on computational thinking and problem-solving.
Comprehensive guide to the Python Standard Library, covering its vast collection of modules and their applications.
Practical guide to testing Python code using the pytest framework, covering unit testing, integration testing, and end-to-end testing.
Practical guide to using Python for bioinformatics tasks, covering sequence analysis, genome assembly, and data visualization.
Comprehensive guide to using Python for financial analysis and modeling, covering data manipulation, financial calculations, and visualization.
Offers a structured and in-depth approach to programming fundamentals using the C programming language. It covers essential concepts such as data structures, algorithms, and memory management, making it well-suited for both beginners and experienced programmers seeking a deeper understanding of C.
This visually appealing and engaging book presents programming fundamentals in Java in a unique and memorable way. It uses a conversational style and numerous illustrations to make learning enjoyable and accessible, particularly for beginners with no prior programming background.
While not specifically focused on programming fundamentals, this book offers invaluable insights into the principles and practices of professional software development. It covers topics such as code maintainability, testing, and project management, making it a valuable resource for aspiring programmers looking to enhance their skills.
This collection of thought-provoking problems and elegant solutions in various programming languages challenges readers to think critically and develop their problem-solving abilities. It covers a range of topics, including algorithms, data structures, and code optimization, making it a valuable resource for experienced programmers looking to hone their skills.
This comprehensive textbook covers the fundamental concepts of algorithms, data structures, and analysis techniques. It provides a deep understanding of how algorithms work and how to design efficient and effective solutions to programming problems. While not specifically focused on programming fundamentals, it is an essential resource for programmers looking to develop a strong foundation in algorithm design and analysis.
This seminal work introduces the concept of design patterns, which are reusable solutions to common software design problems. It provides a catalog of proven patterns and explains how to apply them effectively in object-oriented programming. While not directly related to programming fundamentals, it valuable resource for programmers looking to improve their software design skills.
Practical guide to using Python for basic automation tasks, providing a gentle introduction to Python's core concepts and its practical applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/i1rlp0/programming
Share
Help others find
this course page
by sharing it with your friends and followers:
Copy
Link