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Working in a hands-on learning environment, guided by our expert team, attendees will learn to:

• Understand how data analysts and scientists gather and analyze data
• Perform data analysis and data wrangling using Python
• Combine, group, and aggregate data from multiple sources
• Create data visualizations with pandas, matplotlib, and seaborn
• Apply machine learning (ML) algorithms to identify patterns and make predictions
• Use Python data science libraries to analyze real-world datasets
• Use pandas to solve common data representation and analysis problems
• Build Python scripts, modules, and packages for reusable analysis code
• Perform efficient data analysis and manipulation tasks using pandas
• Apply pandas to different real-world domains with the help of demonstrations
• Get accustomed to using pandas as an effective data exploration tool.

Labs for this course are available at path shared below.

1. Introduction to Data Analysis
2. Working with Pandas DataFrames
3. Data Wrangling with Pandas
4. Aggregating Pandas DataFrames
5. Visualizing Data with Pandas and Matplotlib
6. Plotting with Seaborn and Customization Techniques
7. Financial Analysis: Bitcoin and the Stock Market
8. Rule-Based Anomaly Detection
9. Getting Started with Machine Learning in Python
10. Making Better Predictions -- Optimizing Models
11. Machine Learning Anomaly Detection