This data analysis course provides students with a comprehensive understanding of the fundamental concepts and techniques used in analyzing and interpreting data. The course covers a wide range of topics, including data collection, data cleaning and preprocessing, exploratory data analysis, statistical modeling, and data visualization.

Students will learn how to apply various statistical methods and tools to extract meaningful insights from data, identify patterns and trends, and make informed decisions. They will also gain practical experience in working with real-world datasets through hands-on exercises and projects.

Throughout the course, students will use popular data analysis software and programming language such as Python to manipulate and analyze data. They will learn how to write code to perform data manipulation, statistical calculations, and create visualizations to effectively communicate their findings.

By the end of the course, students will have developed a solid foundation in data analysis and will be equipped with the necessary skills to tackle data-driven problems in various domains, such as business, finance, healthcare, and social sciences.

Prerequisites: Basic understanding of statistics and proficiency in a programming language (such as Python) would be beneficial but not mandatory. Familiarity with data manipulation concepts and basic mathematical operations is recommended.

Course Duration: This course is designed to be completed in 3-4 months and consists of 2-3 hours of hands-on practice.

Course Fee: 24,000/-

Installments - 2

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