• Grasp fundamental concepts such as variables, data types, and control structures (loops and conditionals).
• Develop and run Python scripts to solve simple to moderately complex problems.
• Utilize lists, dictionaries, tuples, and sets effectively.
• Read from and write to files for data processing tasks.
• Create reusable functions and understand scope and lifetime of variables.
• Use exception handling to manage and debug errors.
• Import and use standard and third-party libraries to extend Python’s functionality.
• Understand classes and objects, and implement simple OOP principles.
• Perform basic data analysis using libraries like Pandas and visualize data using Matplotlib.

• Beginners to Programming: Individuals with little to no programming experience who want to learn how to code using Python.
• Aspiring Data Scientists: People interested in data analysis and manipulation, as Python is widely used in data science.
• Software Developers: Those looking to add Python to their skill set to enhance their programming capabilities.
• Automation Enthusiasts: Individuals aiming to automate tasks and processes using Python scripts.
• Students and Researchers: Those needing Python for academic purposes, research, or projects.
• Experienced Programmers: Those already proficient in Python might find this course too basic.
• Non-technical Learners: Individuals not interested in programming or technical fields might not benefit from this course.

• Comfort with basic computer operations such as installing software and navigating file systems.
• Basic understanding of arithmetic and logic.
• A computer with internet access to download and install Python and relevant libraries.
• Willingness to practice coding and solve problems independently.
• Familiarity with another programming language can be helpful but is not required.

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