Data Science Full Course for Beginners | Data Science Tutorial | Big Data | Machine Learning

Here is Data Science full course to help you understand the DS in depth. This session will help you understand the concepts around Data Science and how to go about writing a research paper. Check out our FREE masterclasses by Industry Leading experts now: https://www.scaler.com/events?utm_sou...

What is Data Science?

Data science is a field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured Data, and apply insights from data across a broad range of application domains. Data science combines the scientific method, math and statistics, specialised programming, and advanced analytics, to uncover and explain the insights buried in data.

What is Machine Learning?
Machine learning (ML) is the study of computer algorithms that can improve automatically through experience and by the use of data .It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so.

Busting Data Science Myths:

It’s easier now than ever before for ideas to spread around the world, including through fact-based communities like the one inhabited by data scientists. However, that doesn’t necessarily mean that every data science “fact” we hear is actually truthful.

In fact, some commonly known “facts” are little more than hearsay, misinterpretations, or, at worst, outright myths.

Python Programming Language:
Python is the most widely used data science programming language in the world today. It is an open-source, easy-to-use language that has been around since the year 1991. This general-purpose and dynamic language is inherently object-oriented. It also supports multiple paradigms, from functional to structured and procedural programming. Therefore, it is one of the most popular languages for data science as well. With less than 1000 iterations, it is faster and a better option for data manipulations.

What is A/B testing?
A/B testing, also known as split testing, refers to a randomised experimentation process wherein two or more versions of a variable (web page, page element, etc.) are shown to different segments of website visitors at the same time to determine which version leaves the maximum impact and drive business metrics. Essentially, A/B testing eliminates all the guesswork out of website optimization and enables experience optimisers to make data-backed decisions.

What is the Confusion Matrix?
A confusion matrix is a tool for predictive analysis. It’s a table that compares predicted values with actual values. In the machine learning context, a confusion matrix is a metric used to quantify the performance of a machine learning classifier. The confusion matrix is used when there are two or more classes as the output of the classifier.


0:00 - Introduction
1:25 - Highest Paying Data Job Roles
26:15 - Data Science Myths Busted
40:12 - Data Scientist vs ML Engineer
49:20 - What is Data Science?
1:43:43 - Data Science & AI for beginners
2:06:22 - Python for Data Science
2:57:54 - Data Science with Python and R
3:52:22 - A/B Testing Basics Explained
4:11:20 - Confusion Matrix
4:29:48 - Principle Component Analysis
4:45:07 - Data Science Interview Questions
7:13:03 - Research Papers on Data Science & Machine Learning

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