Applied Data Science

Module 1: Python for Data Science, AI & Development

• Describe Python basics and data structures
• Apply Python programming logic and libraries like Pandas and Numpy
• Access web data using APIs and web scraping from Python in Jupyter Notebooks

Module 2: Python Project for Data Science

• Demonstrate skills in Python for data science and analysis
• Build a dashboard using Python and libraries like Pandas, Beautiful Soup, and Plotly

Module 3: Data Analysis with Python

• Develop Python code for cleaning and preparing data for analysis
• Perform exploratory data analysis and apply analytical techniques using libraries like Pandas and Numpy
• Build and evaluate regression models using machine learning scikit-learn library

Module 4: Data Visualization with Python

• Implement data visualization techniques and plots using Python libraries like Matplotlib, Seaborn, and Folium
• Create different types of charts and advanced visualizations
• Generate interactive dashboards using the Dash framework and Plotly library

Module 5: Applied Data Science Capstone

• Demonstrate proficiency in data science and machine learning techniques using a real-world data set
• Apply skills to perform data collection, data wrangling, exploratory data analysis, data visualization, and model development
• Write Python code to create machine learning models and evaluate their results for predictive analysis