Course Description:
“Introduction to Python for Data Science” is designed to equip learners with the fundamental skills required to harness the power of Python in the realm of data science. This course caters to beginners with no prior programming experience and aims to build a solid foundation in Python programming, data analysis, and visualization techniques. Through hands-on exercises and real-world examples, participants will learn to manipulate data, perform statistical analyses, and create visual representations of data insights, setting the stage for more advanced studies in data science and machine learning.
Course Objectives:
By the end of this course, you should be able to:
- Understand the basic concepts of Python programming.
- Utilize Python libraries such as NumPy, Pandas, and Matplotlib for data manipulation and visualization.
- Perform data cleaning and preprocessing tasks.
- Conduct exploratory data analysis (EDA) to uncover patterns and insights.
- Apply basic statistical methods to analyze data.
- Create meaningful visualizations to communicate data findings.
- Understand the basics of machine learning and its applications.
- Develop a foundation for further study in data science and machine learning.
Course Structure:
This course is divided into 7 modules with two lessons each.
Module 1: Introduction to Python Programming
Module 2: Data Structures in Python
Module 3: Introduction to NumPy
Module 4: Data Manipulation with Pandas
Module 5: Data Visualization with Matplotlib
Module 6: Exploratory Data Analysis (EDA)
Module 7: Basic Statistics for Data Science and Introduction to Machine Learning
Trainer: Samuel Loga
