DATA SCIENCE ASSOCIATE

DATA SCIENCE ASSOCIATE Training provided by DataMites Institute Training Institute in Bangalore,Bommanahalli

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Created by DataMites Institute Training Institute staff Last updated Tue, 17-May-2022 English


DATA SCIENCE ASSOCIATE free videos and free material uploaded by DataMites Institute Training Institute staff .

Syllabus / What will i learn?

Introduction to Data Science

What Is Data Science?

Evolution Of Data Science

Data Science Terminologies

Data Science Vs Business Analytics Vs Big Data

Comparing Various Related Domains With Data Science

Classification Of Business Analytics

Descriptive Analytics

Predictive Analytics

Discovery Analytics And Prescriptive Analytics

Data Science Project Workflow

Crips – Dm Framework

Data Science Project Workflow

Roles In Data Science

Industry Roles And Responsibilities

Application Of Data Science In Various Industries

Health Care

Finance & Banking

Manufacturing

Retail

 Logistics

Human Resource

Python Installation And Setup

Descriptive And Inferential Statistics

Definitions

Terms

Types Of Data

Harnessing Data

Types Of Sampling Data

Simple Random Sampling

Stratified

Cluster Sampling

Sampling Error

Exploratory Analysis

Mean

Median And Mode

Data Variability

Standard Deviation

Z-Score

Outliers

Distributions

Normal Distribution

Central Limit Theorem

Histogram

Normalization

Normality Tests

Skewness

Kurtosis

R Introduction

R Installation And Setup

R Studio – R Development Environment

R Language Basics

R Data Science

R Data Structures

R Control Statements

R Data Science Packages Exploration

Project In R

Introduction To Statistics

Descriptive  And Inferential Statistics. Definitions

Terms

Types Of Data

Harnessing Data

Types Of Sampling Data. Simple Random Sampling

Stratified

Exploratory Analysis

Mean

Median And Mode

Data Variability

Standard Deviation

Z-Score

Outliers

Distributions

Normal Distribution

Central Limit Theorem

Histogram

Normalization

Normality Tests

Skewness

Kurtosis

Correlation & Regression

Direct And Indirect Correlation

Correlation With Strong And Weak Colleration

Calculating Correlation With Python

Regression Theory

Simple Linear Regression With Python

Numpy Numerical Python Package

Introduction

Numpy Basics

Creating Numpy Arrays

Structure And Content Of Arrays

Subset

Slice

Index And Iterate Through Arrays

Multidimensional Arrays

Python Lists Vs Numpy Arrays

Operations On Numpy Arrays

Basic Operations

Operations On Arrays

Basic Linear Algebra Operations

Pandas Panel Data Package

Pandas Basics

Indexing And Selecting Data

Merge And Append

Grouping And Summarizing Dataframe

Lambda Function & Pivot Tables

Data Cleaning Data Munging With Pandas

Pandas Basics

Indexing And Selecting Data

Merge And Append

Grouping And Summarizing Dataframe

Lambda Function & Pivot Tables

Basics Of Visualization

Components Of A Plot

Data Visualization Toolkit

Functionalities Of Plots

Sub-Plots

Plotting Categorical And Time Series Data

Introduction

Plotting Aggregate Values Across Categories

Plotting Distributions Across Categories

Bivariate Distributions - Plotting Pairwise Relationships

Vector Spaces

Vectors: The Basics

Plotting Data Distributions

Introduction

Univariate Distributions

Univariate Distributions - Rug Plots

Machine Learning Introduction

What is Ml? Ml Vs AI

Ml Workflow

Statistical Modeling Of Ml

Application Of Ml

Machine Learning Algorithms

Popular Ml Algorithms

Clustering

Classification And Regression

Supervised Vs Unsupervised

Choice Of Ml Algorithms

Simple Linear Regression

Regression Line

Best Fit Line

Linear Regression In Python

Assumptions Of Simple Linear Regression

Reading And Understanding The Data

Hypothesis Testing In Linear Regression

Building A Linear Model

Residual Analysis And Predictions

Linear Regression Using Sklearn

Multiple Linear Regression

Simple Linear Reg Vs Multiple Linear Reg

Multicollinearity

Dealing With Categorical Variables

Model Assessment And Comparison

Feature Selection

Logistic Regression Binary Classifier

Introduction: Univariate Logistic Regression

Binary Classification

Sigmoid Curve

Finding The Best Fit Sigmoid Curve Summary

Logistic Regression Model Building

Multivariate Logistic Regression

Data Cleaning And Preparation

Building Your First Model

Feature Elimination Using Rfe

Confusion Matrix And Accuracy

Manual Feature Elimination

Install Sql Packages And Connecting To DB

Sqlalchemy

Pymysql

Rdbms (Relational Database Management) Basics

Basics Of Sql Db

Primary Key

Foreign Key

Select Sql Command, Where Condition

Retrieving Data With Select Sql Command

Where Condition To Pandas Data Frame.

Advanced SQL

Order By Clause

Aggregate Functions

Group By Clause

Having Clause

Nested Queries

Inner Join, Outer Joins, Multi Join

Data Science: Project Structure

Crisp Dm Framework

6-Phase Project Execution

Business Aspects

Ml Use Case Development

Project Management Methodology

Challenges And Pitfalls



Curriculum for this course
0 Lessons 00:00:00 Hours
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Description

Data Science skills are in big demand, every present-day organization seeks individuals who can leverage the potential of data, for making important decisions. The Data Science for Managers course mainly concentrates on the tools and techniques needed to analyze the data of a business and derive insights from them and use them to make further business decisions. 

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