CSC 205: DATA ANALYSIS

CSC 205: Data Analysis   (2 Units; E; L = 30; P = 30)

Course Content

1. Introduction to Data Analysis: Understanding the Data Ecosystem: Explore different types of data structures, file formats, and sources of data. Business Problem Solving: Learn how to identify business questions, analyze data requirements, and understand the importance of data in decision-making. Data Ethics and Governance: Understand the ethical considerations and responsible use of data.

2. Data Manipulation and Cleaning: Working with Data: Learn how to access, organize, clean, prepare, transform, and explore data. Data Wrangling: Master techniques for handling missing values, outliers, and inconsistent data. Data Visualization: Learn to represent data visually to identify patterns and insights. SQL Fundamentals: Gain proficiency in querying and managing data in relational databases. NoSQL Databases: Learn about non-relational databases and their applications.

3. Statistical Analysis: Descriptive Statistics: Understand measures of central tendency, dispersion, and frequency distributions. Inferential Statistics: Learn about hypothesis testing, confidence intervals, and regression analysis. Probability and Distributions: Study probability concepts and common probability distributions. 

4. Programming Languages: Python for Data Science: Learn Python syntax, data structures, and libraries like NumPy, Pandas, and Matplotlib. R Programming: Learn R syntax, data manipulation, and visualization techniques. 

5. Data Visualization: Tableau: Learn to create interactive dashboards and visualizations using Tableau. Power BI: Learn to create compelling visualizations and reports using Power BI. Other Visualization Tools: Explore other visualization tools like Seaborn and Metplotlib. 

6. Business Intelligence and Reporting: Data Modeling: Learn the principles of data modeling for efficient data management and analysis. Creating Reports: Learn to create reports using pivot tables, charts, and other visualization techniques. Dashboard Design: Learn to design effective dashboards to communicate insights. 

Real-world Application: Apply learned skills to solve a real-world data analysis problem.