Data Science with Python and Jupyter Notebooks

Data science enables organizations to turn raw figures into strategic insights. Learning Python and core data analysis tools gives you a strong foundation to explore datasets and discover hidden patterns effectively. This text-based course guides you step-by-step through fundamental data science concepts. You will read clear explanations, study practical Python code snippets, and build your confidence working with structured data, exploratory analysis, and introductory machine learning algorithms. What you'll learn: - Understand key data science terminology, foundational statistics, and essential Python syntax - Explore data manipulation and cleaning techniques using Pandas and NumPy - Create informative data visualizations by writing Matplotlib code - Build foundational machine learning models with Scikit-learn for classification and regression - Apply modern prompt engineering principles to enhance data exploration workflows - Document and structure your data analysis workflows using Jupyter Notebook scripts. The learning journey begins with core terminology and foundational definitions before moving into practical code walkthroughs and written exercises. Designed specifically for complete beginners in data science, this course requires no prior coding experience or advanced math background. Start reading today to build your practical skills in Python data analysis.