Course Description: Python in Data Science
What is Needed:
- Basic understanding of Python programming.
- Familiarity with statistics and data analysis concepts.
What is Included:
- Introduction to Python’s role in data science.
- Hands-on projects covering data manipulation, analysis, and visualization.
- Practical skills in using Python libraries like pandas, NumPy, Matplotlib, and scikit-learn.
What is Required:
- Laptop/PC with Python and essential libraries installed.
- Basic programming knowledge is recommended.
5 Key Points:
- Data handling with pandas for effective data manipulation.
- Statistical analysis and data modeling with NumPy and SciPy.
- Data visualization techniques using Matplotlib and Seaborn.
- Building machine learning models with scikit-learn.
- Integrating Python workflows for complete data science projects.
