Designed for individuals new to programming, this comprehensive course provides a structured foundation for developing complex programs in computer science and data science. Through hands-on exercises and examples, you will gain a thorough understanding of Python programming and utilize various common Python packages such as numpy, scipy, and pandas.
The course covers foundational concepts of computer science, including natural language processing and data analytics. You will learn how to write programs to solve problems and gain confidence in your ability to verify the accuracy of your solutions. Upon completion, you will be equipped to tackle real-world programming challenges effectively.
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This course is divided into five modules, covering essential topics such as Python fundamentals, control statements, loops, program development, functions, and data science concepts. Each module includes hands-on exercises and live coding sessions to reinforce learning.
Welcome to the course! This module provides an introduction to programming and the Python language. You will learn about variables, arithmetic, decision making, built-in functions, and how to write code in Jupyter Notebook.
This module focuses on control statements, loops, and program development. You will delve into algorithms, if statements, while and for statements, boolean operators, and an introduction to data science concepts such as mean, median, and mode.
The third module introduces functions, covering topics such as defining, calling, and using functions with multiple parameters. You will also explore variable scope, random number generation, and the Python Standard Library.
Building on the previous module, this module reviews functions, methods, scope rules, and provides a deeper look at import. You will also delve into measures of dispersion and apply the concepts through live coding sessions.
The final module serves as a conclusion to the course, reinforcing the key concepts covered and providing a comprehensive overview of the skills and knowledge gained throughout the modules.
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