Advance Diploma in Data and Business Analytics

Course Overview

• Course Duration:10–12 Months (Fast-track and weekend options available).
• Eligibility: aspiring data analysts working professionals learners.
• Aspiring data analysts.

Advanced Data Analytics (Diploma)

• Learn the fundamentals of data analytics, data cleaning, and visualization.
• Understand business analytics principles for decision-making and reporting.
• Work with Python, R, and SQL for data manipulation and analysis.
• Build interactive dashboards using Power BI and Tableau.
• Apply machine learning and predictive analytics for real-world business insights.
• Prepare for Data and Business Analytics credential preparation Exams and analyst career roles.

Overview of Advanced Diploma in Data (Business) Analytics

The Advanced Data Analytics is designed for learners and professionals aiming to master the art of data-driven decision-making. This program blends technical data analysis with strategic business analytics to create professionals who can extract insights and drive growth.

Through hands-on projects and real-world datasets, learners gain hands-on experience in Python, Power BI, and data visualization techniques. By the end of the course, you'll earn your Advanced Data Analytics, opening doors to careers in data science, business analysis, and consulting.

Module 1 – Advanced Excel for Analytics

• MS Office version comparison and interface.
• Cell referencing: absolute, relative, and mixed.
• Keyboard shortcuts, Data entry, Series filling.
• Formatting options, Arithmetic and Logical functions.
• VLOOKUP, HLOOKUP, INDEX, MATCH, INDIRECT, OFFSET.
• Nested functions, Data Validation, Charts & Pivot Tables.
• Basic VBA and Macros for automation.

Module 2 – Basic Programming Concepts

• Programming introduction, variables, data types.
• Functions and arithmetic expressions.
• Conditional statements and lists.
• Basics of Object-Oriented Programming (OOPs).

Module 3 – SQL & Database Management

• Introduction to MySQL and SQL commands.
• DDL, DML, TCL commands.
• Data types, constraints, joins, subqueries, unions.
• Stored procedures, functions, exception handling.
• Indexes, views, and case handling.

Module 4 – Python for Data Analysis

• Introduction to Python and Anaconda installation.
• Data types, slicing, inbuilt functions.
• Regular expressions, sets, decision-making.
• Loops, lambda functions, PANDAS data analysis.
• Real-world dataset analysis.

Module 5 – Power BI for Business Intelligence

• Power BI overview and installation.
• Connecting data sources and building dashboards.
• Visualizations, animations, and AI visuals.
• Power Query Editor, Data Modeling, DAX expressions.
• Data filtering, sharing, and Power BI Service usage.