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Binary Talk Data Science Expert


INTRODUCTION

Data science specialization will give you complete knowledge of analytics. It will cover end to end skillset of data science profile for small as well as large level organization. 

Course contain below robust tool for Data Science and Analytics
  • Excel: Complete understanding of excel analytics and advance features

 

  • SQL: Introduction to SQL, SQL Course overview, Installing the test environment, What is SQL?, Editors and Platforms to learn SQL, Complete SQL in a Class, Quick-start introduction, Using the basic SELECT statement, Selecting rows, Selecting columns, Counting rows, Inserting data, Updating data, Deleting data Fundamentals of SQL : Databases and tables, SQL syntax overview, Creating tables, Deleting a table, Inserting rows into a table, Deleting rows from a table, What is NULL?, Controlling column behaviors with constraints, Changing a schema with ALTER, Creating an column with ID, Filtering data with WHERE, LIKE, and IN, Removing duplicates with SELECT DISTINCT, Sorting with ORDER BY

 

  • SAS: Introduction to SAS Programming Working in the SAS Environment,Introduction, Working with the windows,Program editor window, Log window, Output window, Result window, Explorer window

 

  • R and R Studio: Fundamentals of R, Installation of R & R Studio, Getting started with R , Basic & advanced data types in R , Variable operators in R, Working with R data frames, Reading and writing data files to R, R functions and loops, Special utility functions, Merging and sorting data

 

  • Modeling Techniques : Predictive modelling in SAS & R, Correlation, Simple linear regression, Multiple linear regression, Model assumptions, Model diagnostics and validation, Moving from linear to logistic, Logistic regression, Odds ratio, Model assessment and gains table, ROC curve and KS statistic, Techniques of customer segmentation, Need for segmentation, Criterion of segmentation, Types of distances, Clustering algorithms, Hierarchical clustering, K-means clustering, Deciding number of clusters

 

  • TABLEAU : Install Tableau Desktop, Connect Tableau to various Datasets: Excel and CSV files, Create Barcharts, Create Area Charts, Create Maps, Create Scatterplots, Create Piecharts, Create Treemaps, Create Interactive Dashboards, Create Storylines, Understand Types of Joins and how they work, Work with Data Blending in Tableau, Create Table Calculations, Work with Parameters, Create Dual Axis Charts, Create Calculated Fields, Create Calculated Fields in a Blend, Export Results from, Tableau into Powerpoint, Word, and other software, Work with Timeseries Data (two methods), Creating Data Extracts in Tableau. Understand Aggregation, Granularity, and Level of Detail, Adding Filters and Quick Filters, Create Data Hierarchies, Adding Actions to Dashboards (filters & highlighting)
Solving an actual business problem through analytics. Simulating an analytics project
  • Case study on Healthcare

 

  • Case study on E-commerce

 

  • Case study on Financial services

 

  • Case Study on call center analytics

 

  • Case study on Twitter analytics

Course Duration :- 120 Hours

KEY FEATURES

Accredited Training Partner

To teach real programming skills

Build a solid understanding

Educated Staff

Timesheets

Video Lessons

Modules / Levels

Advance Excel

Mathematical Functions

Date & Time Function

Text Functions & Data Validation

Statistical Function & Other Functions

Logical Functions

Lookup & Reference Functions

Pivot Table and Charts

Data Collection Method

Analysis - Single/Multidimensional Analysis

Advanced Chart Technique

Advanced Dashboard

Report Development

SQL

Introduction to SQL

SQL Queries

JOINs

Strings

Functions

Triggers & views

SAS

Introduction to SAS

libraries

Understanding Data step Processing Program data vector(PDV)

Importing

Formats & Informats

Functions

Conditional Statements

Joins

Procedures

Combining SAS Datasets

R and R Studio

Introduction to R and R Studio

Fundamentals

Visualization

Data Preperation

Decision Making

Modeling Techniques

Time series forecasting

Techniques of customer segmentation

Model assessment

Model diagnostics and validation

Predictive modelling in SAS & R

Correlation

Simple linear regression

Multiple linear regression

Model assumptions

Moving from linear to logistic

Logistic regression

Odds ratio

Model assessment and gains table

ROC curve and KS statistic

Techniques of customer segmentation

Need for segmentation

Criterion of segmentation

Types of distances

Clustering algorithms

Hierarchical clustering

K-means clustering

Deciding number of clusters

Time series forecasting techniques

Need for forecasting

What are time series?

Smoothing techniques

ARIMA

Decision trees

What are decision trees

Entropy and Gini impurity index

Decision tree algorithms

CART & CHAID

Machine Learning Algorithms Random forest

Support Vector Machine

Knn classification

Text Analytics

Sentimental Analysis

predictive modelling on Text Data

Social Media analysis (Twitter, linkedIn, facebook)

Tableau

Install Tableau Desktop

Connect Tableau to various Datasets: Excel and CSV files

Create Barcharts

Create Area Charts

Create Maps

Create Scatterplots

Create Piecharts

Create Treemaps

Create Interactive Dashboards

Create Storylines

Understand Types of Joins and how they work

Work with Data Blending in Tableau

Create Table Calculations

Work with Parameters

Create Dual Axis Charts

Create Calculated Fields

Create Calculated Fields in a Blend

Export Results from

Tableau into Powerpoint/Word and and other software

Work with Timeseries Data (two methods)

Creating Data Extracts in Tableau

Understand Aggregation

Granularity and Level of Detail

Adding Filters and Quick Filters

Create Data Hierarchies

Adding Actions to Dashboards (filters & highlighting)

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What You Get

  • 24/7 e-Learning Access
  • Certified & Industry Experts Trainers
  • Assessments and Mock Tests