This course aims to introduce learners to Jupyter Notebook, an essential tool for interactive computing. The course is designed to provide a comprehensive understanding of Jupyter Notebook’s features, focusing on how to use it effectively for various tasks. The course is divided into multiple sections, each containing theoretical content followed by practical exercises.
Welcome to the “Introduction to Python” course. This comprehensive, beginner-friendly course is designed to take approximately 4 hours to complete and provides a solid foundation in Python programming. No prior knowledge of Python or programming is required. This course will help you to: Understand the basic syntax of Python, including how to execute calculations and define and modify variables. Navigate through various control structures such as conditionals and loops to control the flow of your program. Explore and manipulate essential data structures like tuples, lists, and dictionaries. Learn to structure your code effectively by defining and using functions to prevent repetition and improve code clarity. By the end of this course, you will have a strong understanding of Python's core concepts and be well-prepared to advance to more specialized topics such as data analysis and machine learning.
Welcome to the “Introduction to NumPy” course. This free course, designed for beginners, takes approximately 3 hours to complete and provides a foundational understanding of NumPy. No prior knowledge of the subject is required. This course will help you to: Understand what NumPy is and its key features and benefits. Create and manipulate arrays efficiently. Perform element-wise operations on arrays. Use mathematical and statistical functions with NumPy. Execute operations involving arrays of different shapes and sizes. Perform advanced indexing and slicing techniques. Work with arrays in the context of data analysis and scientific computing. By the end of this course, you will be well-prepared to interact with NumPy confidently, setting a strong foundation for more advanced data analysis and machine learning courses.
Welcome to the “Introduction to Pandas” course! This comprehensive course, designed for beginners, takes approximately 3 hours to complete and provides a foundational understanding of Pandas. No prior knowledge of the subject is required. This course will help you to: Understand what Pandas is and its key features and benefits. Work with Series and DataFrames, the core data structures in Pandas. Perform indexing, selecting, and assigning operations in Pandas. Utilize basic functions to manipulate and analyze data. Apply grouping operations to aggregate and summarize data. Combine and merge datasets for comprehensive data analysis. By the end of this course, you will be well-prepared to handle data efficiently using Pandas, setting a strong foundation for more advanced data analysis and manipulation tasks.
Welcome to the “Visualization in Python” course. This free course, designed for beginners, takes approximately 4 hours to complete and provides a foundational understanding of data visualization using various Python libraries. No prior knowledge of the subject is required. This course will help you to: Understand the importance and role of data visualization in data science. Learn how to create and customize a variety of charts and plots using Matplotlib. Explore the capabilities of GGPLOT for creating layered visualizations. Utilize Seaborn for statistical data visualization. Harness the power of Bokeh for interactive visualizations. By the end of this course, you will be well-prepared to create insightful and interactive visualizations, setting a strong foundation for more advanced data analysis and visualization tasks.
This is a free course resource that was developed as a guide for designing your own course on the citizen science-topics discussed: Research & Methodology, Education & Awareness-raising, Support Resources & Infrastructure, and Policy & Assessment. It includes resources such as detailed session/workshop outlines and PowerPoint slides. The enrollment key for the course is TIME4CS
This area of moodle is set for communication and exchange of resources between network members of the network of citizen science educators and trainers.