This course will prepare you to: Explain the architecture of the Datascience Certification component Configure and use new functionalities in Datascience Certification Use the standard Datascience Certification Sub Modules. Explain the Datascience Certification Controlling Configuration and Customization option.

Statistics & Plotting Seabourn & Matplotlib - Introduction Univariate Analysis on a Data Plot the Data - Histogram plot Find the distribution Find mean, median and mode of the Data Take multiple data with same mean but different sd, same mean and sd but different kurtosis: find mean, sd, plot Multiple data with different distributions Bootstrapping and sub-setting Making samples from the Data Making stratified samples - covered in bivariate analysis Find the mean of sample Central limit theorem Plotting Hypothesis testing + DOE Bivariate analysis Correlation Scatter plots Making stratified samples Categorical variables Class variable

File I/O Series: Data Types in series, Index Data Frame Series to Data Frame Re-indexing Operations on Data Frame: Slicing, Splicing (also Alternate), Sub-setting Pandas Stat operations on Data Frame Reading from different sources Missing data treatment Merge, join Options for look and feel of data frame Writing to file db operations

Regression - Introduction Linear Regression: Lasso, Ridge Variable Selection Forward & Backward Regression Logistic Regression Logistic Regression: Lasso, Ridge Naive Bayes

Decision trees Cart C4.5 Random Forest Boosted Trees Gradient Boosting

SVM - Introduction Hyper-plane Hyper-plane to segregate to classes Gamma

Data science Certification Training

Sapphire Global Datascience Certification Training makes you an expert in using Datascience Certification concepts. Enroll now for Datascience Certification online training and get through the concepts of data, by utilizing the internal memory for storing a working set. Sapphire Global introduces all the key concepts in Datascience Certification to help the learner gain more knowledge. Enroll & Become a Datascience Certification Consultant.

Overview

Training Options

INSTRUCTOR LEAD LIVE TRAINING

Live Instructor Online training by Certified & industry expert Trainers
24/7 One Demand Dedicated Server for Hands on Practice.
Flexibility to attend the class at your convenient time.
Earn a Skill Certificate
Professional Resume Preparation end of the trading period.
Plus 45 Days of flexible access e- learning.

CORPORATE TRAINING

Customized Learning delivery model.
Our training practice are perfectly blended with options for effective live instructor lead hands on training.
Training need analysis.
Our Corporate training services are easy accessibility of LMS ( learning Management System ) online or offline – anytime, anywhere, on any of your devices.
24/7 learner assistance and Support

Course Curriculum

Key features

This course will prepare you to:

Explain the architecture of the Datascience Certification component
Configure and use new functionalities in Datascience Certification
Use the standard Datascience Certification Sub Modules.
Explain the Datascience Certification Controlling Configuration and Customization option.

Introduction to Python Programming

Introduction to Data Science
Introduction to Python
Basic Operations in Python
Variable Assignment
Functions: in-built functions, user defined functions
Condition: if, if-else, nested if-else, else-if

Data Structure - Introduction

List: Different Data Types in a List, List in a List
Operations on a list: Slicing, Splicing, Sub-setting
Condition(true/false) on a List
Applying functions on a List
Dictionary: Index, Value
Operation on a Dictionary: Slicing, Splicing, Sub-setting
Condition(true/false) on a Dictionary
Applying functions on a Dictionary
Numpy Array: Data Types in an Array, Dimensions of an Array
Operations on Array: Slicing, Splicing, Sub-setting
Conditional(T/F) on an Array
Loops: For, While
Shorthand for For
Conditions in shorthand for For

Basics of Statistics

Statistics & Plotting
Seabourn & Matplotlib - Introduction
Univariate Analysis on a Data
Plot the Data - Histogram plot
Find the distribution
Find mean, median and mode of the Data
Take multiple data with same mean but different sd, same mean and sd but different kurtosis: find mean, sd, plot
Multiple data with different distributions
Bootstrapping and sub-setting
Making samples from the Data
Making stratified samples - covered in bivariate analysis
Find the mean of sample
Central limit theorem
Plotting
Hypothesis testing + DOE
Bivariate analysis
Correlation
Scatter plots
Making stratified samples
Categorical variables
Class variable

Use of Pandas

File I/O
Series: Data Types in series, Index
Data Frame
Series to Data Frame
Re-indexing
Operations on Data Frame: Slicing, Splicing (also Alternate), Sub-setting
Pandas
Stat operations on Data Frame
Reading from different sources
Missing data treatment
Merge, join
Options for look and feel of data frame
Writing to file
db operations

Data Manipulation & Visualization

Data Aggregation, Filtering and Transforming
Lamda Functions
Apply, Group-by
Map, Filter and Reduce
Visualization
Matplotlib, pyplot
Seaborn
Scatter plot, histogram, density, heat-map, bar charts

Linear Regression

Regression - Introduction
Linear Regression: Lasso, Ridge
Variable Selection
Forward & Backward Regression
Logistic Regression
Logistic Regression: Lasso, Ridge
Naive Bayes

Unsupervised Learning

Unsupervised Learning - Introduction
Distance Concepts
Classification
k nearest
Clustering
k means
Multidimensional Scaling
PCA

Random Forest

Decision trees
Cart C4.5
Random Forest
Boosted Trees
Gradient Boosting

SVM

SVM - Introduction
Hyper-plane
Hyper-plane to segregate to classes
Gamma

Practice Test and Interview Questions

Course Advisor

Course Advisor

R. Sreenatha Reddy

SAP FICO / FSCM / TRM / FM / S4HANA Functional Consultant

Professional Experience:

15+ years of Industry experience as Accountant, Consultant, Module Lead, worked on various IT Organizations like IBM/TCS/ITC infotech/SAP Labs across the globe.

Specialized in SAP