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Data Science for Everyone - BaDshaH - 09-24-2024
![[Image: 99e27e1692f514af722098137ea47e53.jpg]](https://i124.fastpic.org/big/2024/0924/53/99e27e1692f514af722098137ea47e53.jpg)
Published 9/2024
Created by Takuma Kimura
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 58 Lectures ( 9h 25m ) | Size: 1.75 GB
Data Science Essentials for Beginners
What you'll learn:
Basics of data science
Basics of machine learning
Basics of statistical inference
Basics of data-driven decision making
Requirements:
None
Description:
Welcome to this course, data science for everyone. In this series of lectures, I will provide you with essentials of data science.This course is targeted for managers who are not data scientist but need to manage data analytic projects. It is also targeted for managers who want to introduce data-driven management. So, the knowledge provided in this course is both theoretical and pragmatic, but not includes details of mathematics and coding. However, anyone who are beginners in data science are also welcome because this course can provide you with essentials for learning technical aspects of data science.You will learn: - Essentials concepts and theories for learning technical aspects of data science.- Pragmatic knowledge for interpreting data and results of data analytics.- Not includes mathematics details and coding.Target Audience:- Managers who are not data scientist but need to manage data analytic projects.- Managers who want to introduce data-driven management.- Anyone who are beginners in data scienceThis course covers the following topics. As you can see, the contents include fundamental concepts of data science, and basics of descriptive, diagnostic, and predictive analytics. This course also covers the very basics of deep learning. In the final two chapters, you can gain a basic but essential and robust understanding of artificial neural networks.I hope you enjoy this course.Contents:- Data Literacy and DIKW- Data-Driven Decision Making- Exploratory Data Analysis: Probability theory, Descriptive Statistics- Data Preprocessing- Data Visualization- Diagnostic Analytics: Hypothesis Testing (Theory and Methods)- Predictive Analytics: Machine Learning, Deep Learning
Who this course is for:
Anyone who want to learn data science
Managers who implement data-driven management
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