Great Learning via Great Learning Academy
To keep pace with the ever-changing landscape of data and its related fields, the handling and analysis of data have become increasingly important. That's why data science has become such a rapidly growing field, attracting millions of people who want to learn and master the subject.
Data Science is the study of information, its origins, meaning, and how it can be transformed into valuable resources and inputs to inform business and IT strategies. In this course, you will learn what data science is and why it's crucial in today's technology-driven world.
You will be introduced to the life cycle of data, the basics of statistics and time series analysis, as well as databases like SQL and NoSQL. After gaining an understanding of data, you will learn how to handle large amounts of data using Big Data techniques. This course provides a comprehensive introduction to the world of Data Science and its related topics.
Dr. Abhinanda Sarkar, Ph.D. from Stanford University and former MIT faculty, teach the course. He is the Academic Director at Great Learning for the Data Science and Machine Learning programs.
This module introduces the domain of Data Science, defining its purpose and explaining why it has become a critical field in the modern technological world.
This module covers the complete lifecycle of data, from collection and processing to analysis and communication of insights.
This module focuses on the basic idea of statistical distributions, teaching you how to understand and interpret data patterns and variability.
This module explores A/B testing, demonstrating how to design and execute experiments to compare two versions and determine which performs better.
This module teaches the fundamentals of time series analysis, covering techniques for analyzing data points collected over a sequence of time.
This section gives you various examples to help you understand Data Science. It explains how you decide on a place for the vacation, how the weather is predicted, and sales during a particular time in a year using data science.
This module covers the concept of big data, focusing on the three key characteristics: volume, velocity, and variety.
This module introduces database technologies, explaining the fundamental differences and use cases for both SQL and NoSQL databases in data science.
This module clarifies the distinction between SQL and NoSQL, detailing the pros and cons of each for various data storage and retrieval needs.
Some points apply to every course of this kind; see how we rank.
Great Learning is in Tier 4: commercial training companies and platform-made courses of our institution ranking (58/100).
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