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Data Science Course (2023)
« em: 26 de Maio de 2023, 13:37 »


Data Science Course (2023)
Published 5/2023
Created by Fanuel Mapuwei
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 28 Lectures ( 2h 7m ) | Size: 933 MB
Learn Mathematics Functions, Statistics and Linear Regression model concept in Data Science with Python

What you'll learn
Data Cleaning and Preparation
Linear Functions and other Data Science Mathematics
Statistics
Data Representation and Interpretation
Requirements
Python basic knowledge
Computer with Jupyter notebook or any IDE
Description
Hello, guys welcome to the Data Science course. In this course, I have summarized the essential concept necessary to be a master in Data Science. I have tried my best to give a detailed explanation and a clear demonstration of how well data is represented. Data Science has become more prevalent in all significant areas like the Health sector, financial market, marketing teams, accounting and manufacturing industries. Data science gives accurate predictions on analyzed data and gives clear outcomes for the organization to make decision-based on the analysis which has been made. In this course, I have demonstrated how to gather data from various sources then clean the data and make analysis for decision-making. In this course there are Mathematical Analysis functions, Statistical Analysis tools and Advanced Data Science tools which I combined in demonstrating how powerful and effective Data Science is when analysing data. These tools and functions are used in various sectors across the globe when analysing the data pattern.I have presented this course content clearly with the inclusion of all Beginner level in Python Programming and Data Science students who are still fresh, I did so to make sure that we all understand the lectures well.
Who this course is for
Data Science and Data Analysis students who finds it difficult to grasp the concept
Python developer who wishes to add more knowledge

Download link

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