Course description

Data analysis and visualization using Python involve processing, analyzing, and representing data in meaningful ways to extract insights. Python libraries like Pandas, NumPy, and SciPy help clean, manipulate, and analyze datasets efficiently. Visualization tools such as Matplotlib, Seaborn, and Plotly enable the creation of graphs, charts, and interactive dashboards for better data understanding. Exploratory Data Analysis (EDA) techniques help identify patterns, correlations, and trends in data. Machine learning integration with libraries like Scikit-learn enhances predictive analytics and decision-making. Python’s versatility allows automation of data processing and reporting. Interactive visualization tools aid in storytelling and effective communication of insights. Real-time data visualization is possible with frameworks like Dash and Streamlit. Businesses, researchers, and analysts use Python for data-driven strategies. Overall, Python simplifies data analysis and visualization, making it a powerful tool for informed decision-making.

What will i learn?

• CO1 Able to gain knowledge on visualization with good story line and perform job of a data analyst
• CO2 Able to analyze and visualize the dataset
• Ability to design dashboard