Data Analysis

Course Description: Data Analysis Master the skills needed to transform raw data into meaningful insights and support data-driven decision-making. This comprehensive Data Analysis course is designed for beginners and aspiring professionals who want to build a strong foundation in collecting, cleaning, analyzing, visualizing, and interpreting data. Throughout the course, students will gain hands-on experience with industry-standard tools and real-world datasets while learning the complete data analysis workflow. What You Will Learn Introduction to Data Analysis Microsoft Excel for Data Analysis Advanced Excel (Functions, Pivot Tables, Charts & Dashboards) SQL for Data Querying and Database Management Python Programming for Data Analysis NumPy for Numerical Computing Pandas for Data Cleaning and Manipulation Data Visualization with Matplotlib and Plotly Exploratory Data Analysis (EDA) Statistics for Data Analysis Data Storytelling and Reporting Working with APIs and External Data Sources Data Cleaning and Preprocessing Techniques Business Intelligence Fundamentals Capstone Data Analysis Project Portfolio Development and Best Practices Skills You Will Gain Clean, organize, and transform raw data Analyze datasets using Excel, SQL, and Python Create professional charts, dashboards, and reports Identify trends, patterns, and business insights Build interactive data visualizations Make data-driven recommendations Develop a professional portfolio of data analysis projects Prepare for entry-level Data Analyst roles and freelance opportunities Prerequisites: No prior programming experience is required. Basic computer knowledge is sufficient. Outcome: By the end of this course, students will be able to confidently analyze real-world datasets, communicate insights effectively, and use modern data analysis tools to solve business and organizational problems.