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Oracle SCM Discrete Manufacturing Online Training in Hyderabad India

Oracle SCM Discrete Manufacturing Online Training in Hyderabad India

Oracle Discrete Manufacturing (ODM)


Oracle Discrete manufacturing helps Organizations better manage production operations to achieve fulfillment excellence. Factories of all sizes and in all industries can benefit from improving the management of information in the entire production cycle, from R&D to design through work-in-process to cost and quality management.


Duration:25hrs

Discrete Manufacturing Course Content:

  • · Oracle Bill of Material
  • · Oracle Work in Process
  • · Oracle Cost Management
  • · Oracle Quality
  • · Oracle Manufacturing Execution system
  • · Production Scheduling
  • · Material requisition planning
  • · Advance supply chain Planning
  • · Oracle MPS/ MRP/DRP planning

Guidewire Claim Center Training in Hyderabad India

Guidewire Claim Center  


This course offers students with the knowledge and skills needed to with success set up the application-specific features of ClaimCenter. The course assumes students recognize the basics of configuration for any Guidewire product. The course focuses on the options specific to ClaimCenter that are configured in nearly all implementations. By the conclusion of the course, students consider to have an understanding of Claim Center adequate enough that they will use the product documentation to find out the way to accomplish more advanced configuration.

Guidewire training


Duration: 25hrs

Course Content:

The Claim File
  • The ClaimCenter data model 
  • The claim file 
Claims Process and Intro to Intake
  • Claims processing – business perspective 
  • Claims processing – functional perspective 
  • The claim intake process 
  • Automated claim setup 
  • New claim validation 
ClaimCenter Demo
  • Demonstration of ClaimCenter functionality 
Introduction to ClaimCenter Configuration
  • ClaimCenter data model 
  • ClaimCenter user interface 
  • ClaimCenter rules 
  • Importing data into ClaimCenter 
Configuring Location Groups
  • Location group basics 
  • Location group configuration 
  • Page configuration 
Configuring Wizards
  • Wizard basics 
  • Wizard configuration 
  • Wizard step configuration 
Configuring Claim Setup
  • Claim setup basics 
  • Presetup rules 
  • Segmentation rules 
  • Workplan rules 
  • Exposure and activity setup 
Configuring LOB Typelists
  • Line of business model 
  • The LOB typelists 
  • The LOB editor 
  • LOB model configuration 
Configuring LOB User Interface
  • LOB model and the user interface 
  • Configuring exposure types 
  • Configuring new exposure menu behavior 
Configuring Validation Rules
  • Types of validation 
  • Validation rule basics 
  • Validation rules in the user interface 
  • Warnings and errors 
  • Identifying invalid fields 
Configuring Permissions
  • ClaimCenter security functionality 
  • Checking system permissions in Gosu 
  • Creating system permissions 
  • Application permission keys 
Contact Roles
  • Contact roles 
  • Categorizing contact 
  • Contact role configuration 
  • Contact role type constraints 
  • Entity role constraints 
ClaimContact Widgets
  • ClaimContact widget basics 
  • Configuring ClaimContact widgets 
Intro to Transaction Rules
  • Transaction basics 
  • Transaction data model 
  • Transactions and Gosu 
  • The Financial Calculations Library 
Configuring Transaction Validation Rules
  • Transaction and check life cycles 
  • Transaction validation basics 
  • Transaction validation rules 
Configuring Transaction Approval Rules
  • Transaction approval basics 
  • Authority limits 
  • Transaction approval rules 
  • Approval routing rules
If you want to know more about Guidewire Claim Center Online Training
Contact +91-8143111555


Data Science Course in Hyderabad | Data Science Training in Hyderabad

Data Science Course In Hyderabad 


Data science course in Hyderabad is in search on large basis. Ecorp Trainings being a prominent provider of IT courses and training in Hyderabad, Chennai,chicago, california, canada, usa uk, bangalore, india has been Data science training in Hyderabad.
Data Science training in Hyderabad

Data Science is considered as the new arena, which is the most emerging technology that can easily enhance the Organizational growth. Data Administration and Management is being the biggest challenges that can face real time challenges in the explosion of happening these days.


Duration: 40hrs

Course Content:

Introduction to Data Science
What is Data Science?
Role of Data Science 
Scope of Data Science
1. Descriptive and Inferential Statistics
Samples and Populations
Sample Statistics
Estimations of Population Parameters
Random and Non-random Sampling
Sampling Distributions
The Central limit Theorem
Degree of Freedom
Percentiles and Quartiles
Measures of Central Tendency
Mean
Median
Mode 
Measures of Variability/Dispersions
Range
IQR
Variance
Standard Deviation
Distributions
Normal Distributions
Binomial Distribution
Probability Distribution
Events, Sample Space and Probabilities
Conditional Probabilities
Independence of Events
Bayes’ Theorem
Random Variable
Confidence Intervals
Hypothesis Testing
Null Hypothesis
The Significance Level
p-value
Type I and Type II Errors
Inferential Test Metrics
t test
f test
Z test
Chi square test
Student test
The Comparison of Two Populations
Analysis of Variance
ANOVA Computations
Two-way ANOVA
Similarity Metrics
Euclidean Distance
Jaccard Distance
Cosine Similarity
Graphical Representation and summaries
2. Data Exploration
Variable Identification
Uni-variate Analysis
Bi-variate Analysis
Missing Values Treatment
Imputation
Deletion
Prediction
Outlier Detection
Deletion
Binning and Transformation
Feature Engineering
Variable transformation
Variable / Feature creation
Dimensionality Reduction
Missing Values
Low Variance
High Collinearity
PCA
Factor Analysis
Principal Component Analysis
Data Summaries Using Stats and plots
Covariance, Correlation, and Distances
Correlation vs Causation
3. Machine Learning: Introduction and Concepts
Differentiating algorithmic and model based frameworks
Supervised Learning with Regression and Classification
Model Validation Approaches
Training Set
Validation Set
Test Set
Cross-Validation
Regression Algorithms
Linear Regression
Ordinary Least Squares
Ridge Regression
Lasso Regression 
Unsupervised Learning
Clustering
Hierarchical (Agglomerative) Clustering
Non-Hierarchical Clustering: The k-Means Algorithm
Recommender Engines:
Collaborative Filtering Recommenders
Content Based Recommenders
4. R-Analytical Tool (Data Mining / Machine Learning)
Basic Data Types
R Data Structures
Vectors
Matrix
Data Frames
List
R Functions
Predictive Modeling Project based on R
Classification Model Attention:ing Project based on R
Clustering Project based on R
Association Mining Project based on R
R Visualization Packages
Machine Learning Packages in R
5. Python Scientific Libraries for Machine Learning
Scikit-Learn
Numpy
Scipy
Pandas
Matplotlib
Rmsc
R/Square
K Nearest Neighbors Regression & Classification
Classification
Logistic Regression
Naive Bayes
Classifier Threshold And Interpretation
Confusion Matrix-Error Measurement
Roc Curve
Accuracy, Precision, Recall
Measuring Sensitivity And Specificity
Regression And Classification Trees
Decision Trees
Recursive Portioning
Impurity Measures (Entropy And Gini Index)
Pruning The Tree
Support Vector Machines
Ensemble Methods
Bagging (Parallel Ensemble) – Random Forest
Boosting (Sequential Ensemble) – Gradient Boosting
Neural Networks
Structure Of Neural Network
Hidden Layers And Neurons
Weights And Transfer Function
Deep Learning
Forecasting (Time-Series Modeling )
Trend And Seasonal Analysis
Different Smoothing Techniques
Arima Modeling
6. Spark Mllib (Scalable Machine Learning) 
Spark Vs Hadoop 
Spark Architecture 
Distributed Computing Advantages 
Rdd Concept 
Spark Mllib: Data Types, Algorithms, And Utilities




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