Welcome to our Data Analysis with Python course! This comprehensive program is designed to teach you the essential skills needed to analyze data using Python. Whether you're a beginner or have some experience with programming, this course will help you master the tools and techniques necessary for effective data analysis.
Course Overview
- Duration: 12 weeks
- Format: Online, self-paced
- Prerequisites: Basic understanding of Python or programming experience
- Materials: Access to Python environment, Jupyter Notebook
Course Content
Introduction to Python for Data Analysis
- Setting up your Python environment
- Basic Python syntax and data types
- Introduction to Jupyter Notebook
Data Manipulation and Cleaning
- Importing and exporting data
- Data cleaning techniques
- Handling missing data
Data Visualization
- Introduction to data visualization libraries (Matplotlib, Seaborn)
- Creating basic plots (line charts, bar charts, histograms)
- Advanced visualization techniques
Statistical Analysis
- Descriptive statistics
- Hypothesis testing
- Correlation and regression analysis
Machine Learning
- Introduction to machine learning concepts
- Supervised learning (classification, regression)
- Unsupervised learning (clustering, association)
Case Studies
- Real-world data analysis projects
- Hands-on exercises and assignments
Learning Outcomes
- Understand the fundamentals of Python for data analysis
- Master data manipulation and cleaning techniques
- Create insightful visualizations and reports
- Apply statistical analysis to real-world data
- Develop machine learning models for predictive analytics
Resources
For further reading, check out our Python for Data Science course.
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