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Reveal the world of data science and gain proficiency in Python's essential data manipulation and visualisation libraries. In our "Python Data Science with Numpy, Pandas, and Matplotlib" course, you'll embark on a journey of discovery, learning the tools and techniques that empower you to analyse, interpret, and visualise data effectively.
Course Highlights:
Introduction to Data Science with Python
Gain an understanding of the course and its significance in the realm of data science.
Explore why Python is preferred for data analysis and visualization.
Configure your data science environment, ensuring a smooth learning experience.
Master the use of Jupyter Notebooks, a popular tool for interactive data analysis.
Numpy - The Numerical Powerhouse
Delve into the fundamentals of NumPy, a critical library for scientific computing.
Learn about array creation, manipulation, and mathematical operations in NumPy.
Apply NumPy to analyse and manipulate data efficiently.
Tackle practical data analysis projects using NumP
Data Handling with Pandas
Discover the pivotal role of Pandas in data analysis and how to create data frames and Series.
Learn data cleaning and preprocessing techniques with Pandas.
Explore data, conduct statistical analysis, and derive insights using Pandas.
Apply Pandas skills to analyse real-world datasets.
Data Visualisation with Matplotlib
Unlock the power of Matplotlib, a versatile data visualisation library.
Create various plots, including line plots, bar charts, and scatter plots, to represent data visually.
Dive into advanced data visualisation techniques like subplots, 3D plots, and customising visualisations.
Master the art of data storytelling through visualisation.
Real-world Applications and Case Studies
Work with actual datasets to gain hands-on experience.
Collaborate with peers on data analysis projects, applying your knowledge from the course.
Tackle a comprehensive data analysis project, integrating Numpy, Pandas, and Matplotlib to extract meaningful insights.
