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.
- Introduction to Data Analysis
- Working with Pandas DataFrames
- Data Wrangling with Pandas
- Aggregating Pandas DataFrames
- Visualizing Data with Pandas and Matplotlib
- Plotting with Seaborn and Customization Techniques
- Financial Analysis: Bitcoin and the Stock Market
- Rule-Based Anomaly Detection
- Getting Started with Machine Learning in Python
- Making Better Predictions -- Optimizing Models
- Machine Learning Anomaly Detection