This course provides a practical introduction to Python for Data Science, designed for beginners and aspiring analysts & AI engineers. Students will learn core Python programming, data handling with libraries like NumPy and Pandas, data cleaning, visualisation, and exploratory analysis needed for Data Science. Each concept is taught through hands-on examples and real datasets to build confidence and problem-solving skills. By the end of the course, learners will be able to write Python scripts, analyse data effectively, and prepare themselves for advanced topics in Machine Learning and AI.
Curriculum Highlights:
• Introduction to Python: syntax, variables, loops, functions
• Working with data: NumPy arrays and operations
• Data analysis with Pandas: loading, cleaning, transforming datasets
• Data visualisation using Matplotlib and Seaborn
• Exploratory Data Analysis (EDA) techniques
• Handling real datasets and common data-science workflows
• Introduction to statistics for data analysis
• Mini-projects and guided assignments to build confidence
By the end of the course, learners will be able to write Python scripts, clean and analyse data, create visual insights, and prepare for advanced topics like Machine Learning and AI.