Introduction to Data Analytics: Understand the fundamentals of data analytics and its role in extracting meaningful insights from data.
Advanced Excel for Data Analytics: Learn advanced Excel techniques to manipulate, analyze, and visualize data effectively.
Introduction to Python for Data Analytics: Get started with Python programming and its applications in data analysis and manipulation.
Data Manipulation in Python: Learn to clean, transform, and organize data using Python libraries like Pandas and NumPy.
Introduction to SQL for Data Analytics: Discover the basics of SQL to query and manage databases for data analysis.
Advanced SQL for Data Analytics: Master complex SQL queries, joins, and functions for advanced data analysis tasks.
Introduction to Tableau: Learn to use Tableau for creating interactive and insightful data visualizations.
Advanced Tableau: Dive deeper into Tableau’s advanced features, including complex calculations and dashboard design.
Introduction to Power BI: Explore Power BI to create visually appealing reports and dashboards from data.
Advanced Power BI: Learn advanced Power BI techniques like DAX, custom visualizations, and data modeling for complex analysis.
Data Visualization Best Practices: Understand the principles and best practices for creating clear, effective, and impactful data visualizations.
Capstone Project and Presentation: Apply your learning in a real-world project and present your findings using data analytics tools.
Introduction to Data Science: Get an overview of data science concepts, tools, and techniques used in data-driven decision-making.
Data Cleaning and Preprocessing: Learn the techniques for cleaning and preparing data for analysis, ensuring accuracy and consistency.
Data Modeling and Analysis: Understand how to build and evaluate data models to predict outcomes and derive insights.