Data Analytics with Python Course Overview

Study Notes

Course on Data Analytics with Python by Prof. Ramesh Anbanandam at IIT Roorkee focuses on practical examples over repetitive software use, aiming to make students comfortable with analytics in their careers and personal lives.
The course emphasizes the importance of choosing the right methodology and understanding the fundamental concepts behind data analytics tools.
Learning objectives include defining data and its importance, understanding data analytics types, explaining the significance of analytics in today's business environment, and clarifying the interrelation between statistics, analytics, and data science.
The course utilizes Python for practical applications and covers the four levels of data: nominal, ordinal, interval, and ratio.
Variables are characteristics of entities capable of taking different values, measurements assign numbers to variable attributes, and data are recorded measurements.
Data can be generated by humans, machines, or their combination, and it adds value to businesses by facilitating the development of data products like recommendation engines and insights.
Data is crucial for making better decisions, identifying reasons for underperformance, benchmarking performance, improving operations, and understanding consumers and markets.- Data analysis involves studying past events to understand why and how they happened, while data analytics focuses on predicting future events based on past data.
Descriptive analytics provides a summary view of facts and figures, while diagnostic analytics examines why certain events happened.
Predictive analytics helps forecast trends based on current events, using techniques like regression analysis.
Prescriptive analytics indicates the best course of action to optimize outcomes, utilizing tools like optimization models and decision analysis.
The demand for data analysts and data scientists is increasing, with many companies looking for qualified individuals in this field.
Skills required to become a data analyst include knowledge of mathematics, technology, and business/strategy acumen.
Data analysts focus on analyzing data within a specific business domain, while data scientists work on advanced algorithms and machine learning to create data products.
Python is chosen for data analysis due to its simplicity, free and open-source nature, extensive library, and usability across various applications including data science, machine learning, and artificial intelligence.
Different levels of data measurement include nominal, ordinal, interval, and ratio scales, each with specific characteristics and usefulness in data analysis.
Understanding the different types of data measurement helps in choosing the appropriate analytical tools for analysis, whether parametric or non-parametric tests.

Description

Learn about the practical examples and fundamental concepts of data analytics with Python in a course by Prof. Ramesh Anbanandam at IIT Roorkee. Understand the importance of data, analytics methodologies, and the interrelation between statistics, analytics, and data science. Explore different levels of data measurement and the role of Python in data analysis.