Data Science Course

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.

Overview

Section 1: Introduction

Lecture 1 Downloading Anaconda and Installing Python

Lecture 2 Installing Anaconda and Opening Jupyter Notebook

Lecture 3 Anaconda Navigator

Lecture 4 Google Colab

Section 2: Data Science Introduction

Lecture 5 Datasets

Lecture 6 What is Data Science–––––Data?

Lecture 7 Data Representation

Lecture 8 Pandas Data Science Library with Python

Lecture 9 Numpy Data Science Library with Python

Lecture 10 Matplotlib Data Science Library with Python

Lecture 11 Scipy Data Science Library with Python

Lecture 12 Seaborn Data Science Library with Python

Lecture 13 Functions

Lecture 14 Data Cleaning

Section 3: Mathematics Functions for Data Scientist

Lecture 15 Linear Functions

Lecture 16 Linear Programming

Lecture 17 Plotting Linear Graph

Lecture 18 Gradient and the intercept

Section 4: Statistical Analysis Tools

Lecture 19 Introduction

Lecture 20 Statistical Data Analystic Summary Interpretation

Lecture 21 Standard Deviation

Lecture 22 Variance

Lecture 23 Correlation

Section 5: Data Science Advanced Tools

Lecture 24 Linear Regression Intro

Lecture 25 Linear Regression Part 1

Lecture 26 Linear Regression Part 2

Lecture 27 Linear Regression Table

Lecture 28 Linear Regression Table Summary

Data Science and Data Analysis students who finds it difficult to grasp the concept,Python developer who wishes to add more knowledge