This course offers a comprehensive introduction to Data Science, covering the process of analyzing, visualizing, and interpreting data to derive insights and support decision-making. Learn essential tools, techniques, and methodologies in data analysis, machine learning, and statistical modeling.
Key Topics:
Data analysis with Python and libraries like Pandas & NumPy
Data visualization with Matplotlib and Seaborn
Statistical analysis and hypothesis testing
Machine learning concepts and model building
Tools and techniques for big data processing
By the end of the course, you'll have the skills to analyze complex data, create visualizations, and apply machine learning techniques to solve real-world problems.