Business Analytics and Visualization

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Course Overview

The Business Analytics and Visualization Program is a comprehensive learning journey designed to transform raw data into strategic insights. This meticulously crafted curriculum empowers professionals and aspiring analysts to master the critical skills needed in today’s data-driven business landscape. By combining technical expertise with practical applications, the program provides a holistic approach to understanding and leveraging data for informed decision-making.

At the core of the program lies an intensive focus on developing robust technical capabilities. Participants will dive deep into data manipulation techniques, learning to navigate complex datasets using SQL and Python. The curriculum covers advanced statistical analysis, enabling learners to extract meaningful patterns and insights from diverse data sources. Through hands-on training in visualization tools and techniques, students will learn to transform complex numerical information into compelling, easy-to-understand visual narratives.

This program goes beyond theoretical knowledge, emphasizing real-world application and practical skill development. Participants will engage with industry-relevant case studies, working on projects that simulate actual business challenges. From Excel-based analytics to advanced Python visualization techniques, learners will develop a comprehensive toolkit that bridges the gap between data analysis and strategic business decision-making. The program ensures that graduates can immediately apply their skills to drive organizational performance and create data-driven strategies. Prerequisites Basic understanding of mathematics and statistics Familiarity with Excel and spreadsheets Knowledg of database structures (SQL basics)

Prerequisites
Program Outcomes
Program Coverage

Duration: 7 Hours

Basic Excel Functions
Data Entry
Data Cleaning
Pivot Tables
Visualization Techniques

Duration: 8 Hours

Descriptive Statistics
Probability Distributions
Hypothesis Testing
Sampling Techniques

Duration: 8 Hours

Basic SQL Commands (SELECT, JOIN, WHERE)
Normalization
Data Aggregation
Subqueries

Duration: 19 Hours

Python Syntax
Data Structures
Pandas
Numpy
File Handling
Data Analysis Techniques

Duration: 15 Hours

Data Wrangling
Matplotlib
Seaboarn
Data Visualization
Exploratory Data Analysis (EDA)

Duration: 03 Hours

Review of Excel
SQL
Python
Visualization with Practical Excercises and MCQs

40%

VILT (Virtual Instructor Led)

60%

SDL (Self Directed Learning)

This course includes:
Investment:
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