Course Description

Introduction to Python Basics for Data Science is a comprehensive course designed to introduce students to the fundamental concepts of Python programming language and how it is applied to data science. Python has become the most popular programming language in the field of data science and is widely used for data analysis, data visualization, and machine learning. The course is suitable for students who have little or no programming experience but are interested in data science. It is also beneficial for those who are familiar with other programming languages and want to learn Python specifically for data science. The course will cover the basics of Python, including variables, data types, conditional statements, loops, functions, and input/output operations. Students will also learn how to use Python libraries such as NumPy, Pandas, and Matplotlib for data analysis, manipulation, and visualization. The first part of the course will focus on the basics of Python programming. Students will learn how to use Python's built-in functions, manipulate data types, and create control structures for decision making and looping. The course will also cover how to read and write data from files using Python. In the second part of the course, students will be introduced to data analysis and manipulation using Python libraries. The course will cover the basics of NumPy for scientific computing, Pandas for data manipulation, and Matplotlib for data visualization. Students will learn how to manipulate data using NumPy arrays and how to use Pandas for data analysis tasks such as filtering, grouping, and aggregating data. They will also learn how to create visualizations using Matplotlib. In the final part of the course, students will apply what they have learned to a real-world dataset. They will learn how to import and clean data, perform exploratory data analysis, and create visualizations to gain insights into the data. Students will also learn how to use machine learning algorithms in Python to create predictive models. In conclusion, the Introduction to Python Basics for Data Science course is an excellent starting point for anyone interested in data science or machine learning using Python. By the end of the course, students will have a solid understanding of the Python programming language and be able to use it to perform data analysis and visualization tasks. They will also be equipped with the skills to apply machine learning algorithms to real-world datasets. Author: (DPhi)