
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
The students will able to understand the types of data analysis and its process
Uncover the knowledge domain and scope of data analysis, including computer fundamentals, programming basics, data structures, databases and sql, version control, and core mathematical and statistical foundations.
Master arithmetic and logic operators, matrix product, and linear algebra basics essential for data analysis, including data cleaning, preprocessing, and model training in Excel workflows.
Explore how increment and decrement operators work in Python for data analysis, and harness NumPy universal functions for fast, vectorized data processing.
Master indexing, slicing, and iteration techniques to access and filter specific rows and columns in data frames, using position-based and label-based methods for data analysis and feature selection.
Master data preparation by handling common file formats, csv, Excel, json, html tables, hdf5, and sql databases, focusing on import, export, cleaning, transformation, and compatibility across tools and platforms.
Learn foundational data visualization with line charts, bar charts, and histograms to reveal trends, distributions, and insights for data-driven decisions.
Explore data visualization types used for data analysis, including pie charts for proportions, contour plots for multivariate relations, and polar charts for circular directional data.
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.