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Foundation of Data Analysis
Rating: 4.4 out of 5(11 ratings)
46 students

Foundation of Data Analysis

Data, Data analysis, Scope of Data Analysis, Knowledge Domain, Computational Methods, Data Visualization
Last updated 6/2025
English
English [Auto],

What you'll learn

  • Introduce a range of topics to understand the data and data analysis process
  • Explain the knowledge needs for data analysis and give the idea about the scope of data analysis
  • To give the knowledge on basic and advanced Computational Operations of Data Analysis
  • To explore the data preparation process and Visualization methods in Data analysis

Course content

6 sections • 12 lectures • 2h 40m total length
  • Define Data, Data Analysis and It’s importance14:16

    The student will able to understand the basics of data, importance of data, data science, difference between Data analysis and Data analytics and the applications

  • Introduction Quiz
  • Types of Data Analysis, The Process of Data Analysis, Tools for Data Analysis19:00

    The students will able to understand the types of data analysis and its process

Requirements

  • You will learn the basic of data analysis from the scratch . No need of prior knowledge

Description

Foundations of Data Analysis is a comprehensive introductory course designed to equip learners with essential knowledge and practical skills in the field of data analysis. This course guides you through the core concepts, processes, and tools necessary to understand and analyze data effectively.

The journey begins with defining what data and data analysis are, highlighting their growing importance across industries. Learners explore various types of data analysis, step-by-step processes, and commonly used analytical tools. The course then delves into understanding the nature of data, domains of knowledge required for analysis, and the wide scope of applications.

Participants will develop foundational technical skills through lessons on basic computational operations, including arithmetic, logical, and matrix operations, followed by increment/decrement operators and universal functions used in data processing. The course also covers advanced operations like aggregation, indexing, slicing, and iteration—key techniques for efficient data manipulation.

Data preparation is another crucial component, where students learn to handle various data file formats and apply preprocessing techniques, including outlier detection and filtering. Finally, the course emphasizes the power of data visualization, teaching how to interpret and create line charts, bar charts, histograms, pie charts, contour plots, and polar charts.

Quizzes reinforce learning throughout, making this a practical and interactive introduction to the fundamentals of data analysis.

Who this course is for:

  • This Course is mainly for the beginners those who are curious about data analysis process and visualization