Learn Data Science From Scratch


Ultimate Data Science course

What you will learn

learn about arificial neural network

using anti-malware

Learn basics of Data science

More of advance data science

Get certification

Description

What is data science?

Data science is the study of data to extract meaningful insights for business. It is a multidisciplinary approach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze large amounts of data. This analysis helps data scientists to ask and answer questions like what happened, why it happened, what will happen, and what can be done with the results.

Why is data science important?


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Data science is important because it combines tools, methods, and technology to generate meaning from data. Modern organizations are inundated with data; there is a proliferation of devices that can automatically collect and store information. Online systems and payment portals capture more data in the fields of e-commerce, medicine, finance, and every other aspect of human life. We have text, audio, video, and image data available in vast quantities.

This course is designed for both complete beginners with no programming experience or experienced developers looking to make the jump to Data Science!.In this course you WILL experience firsthand all of the PAIN a Data Scientist goes through on a daily basis. Corrupt data, anomalies, irregularities – you name it!

This course will give you a full overview of the Data Science journey. Upon completing this course you will know:

  • How to clean and prepare your data for analysis
  • How to perform basic visualisation of your data
  • How to model your data
  • How to curve-fit your data
  • And finally, how to present your findings and wow the audience
English
language

Content

Complete Data Science Masterclass

Basics
Supervised Learning and Bayesian Decision Theory
Linear Discrimination (10 Linear Discrimination
Kernel Machines and Machine Learning Probability
Hidden Markov Models