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data analytics certification

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data analytics certification

Data Analytics Training

People who want to do become data analysts can take up the Data Analyst Training provided by Qtsinfo. The data analytics courses will train you and help you to understand all the concepts which will help you to handle the position perfectly in your job. The job of a data analyst is to analyze the data of a large dataset statistically. This data can later be used to answer the questions asked by clients and customers. Besides data analyst, you can get other data analytics jobs

Course Overview

The data analytics certification will help you understand various concepts of data analysis. You will be taught about terminology and techniques that a data analyst uses to analyze data. You will also learn programming languages like R, Python, databases, and many others. These data analytics skills will be developed after completing the course.

Data Analytics Certification Key features

  • Compare data science vs data analytics
  • Learn the usage of different data analytics tools
  • Know about data analytics software
  • Choose any schedule from different data analytics programs
  • Learn about data analytics in healthcare
  • You can also go for data analytics masters programs
  • Compare business analytics vs data analytics
  • Get data analytics interview questions
  • The course will start with data analytics definition.

Who should take Data Analytics Courses?

People who can take up the course to boost their careers are listed below.

  • Supply Chain Network Managers
  • Banking Professionals
  • Marketing Managers
  • Sales Professionals
  • Data Analytics Professionals
  • IT Professionals

Data Analytics Online Training Important Facts

  • Customer experience can be personalized.
  • Decision-making becomes easy after analyzing data.
  • Operations can be easily streamlined.
  • Risk handling can be done easily through data analytics.
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Course curriculum / Syllabus

Exploratory Data Analysis with R
  • Use are for querying loading, and manipulating data
  • Raw data cleaning for modeling
  • Using Principal Component Analysis  in the reduction of dimensions
  • Using user-defined packages to extend R
Facilitating good analytical thinking with data visualization
  • Data set  characteristics investigation through visualization
  • Use boxplots, histograms and density plots to make charts for data distribution
  • Identifying outliers in data
Working with Unstructured and Large Data Sets

  Mining unstructured data for business applications

  • Unstructured data Preprocessing to prepare deeper analysis
  • Making a corpus of documents using term-document matrix
Managing additional complexities of Big Data
  • Examining the MapReduce and Hadoop architectures
  • Integrating R and Hadoop with RHadoop
Predicting Outcomes with Regression Techniques

  Future values estimation through logistic and linear regression

  • Relationship Modeling between several input variables  and an output variable
  • Interpretation of coefficients of categorical and continuous data

  Regression techniques for dealing with Big Data

  • Overcoming issues of volume with RHadoop
  • Creating regression modules for RHadoop
Categorizing Data with Classification Techniques

  Automating the labeling of new data items

  • Predicting target values using Decision Trees
  • Model building for future predictions from existing data
  • Combination of tree predictors and random forests in RHadoop

  Assessing model performance

  • Visualizing model performance with a ROC curve
  • Evaluating classifiers with confusion matrices
Patterns Detection in Complex Data using Link Analysis and Clustering

  Identification of unknown groupings within a data set

  • Customer market segmentation using the K-Means algorithm
  • What are appropriate distance measures?
  • Tree-like clusters building with the help of hierarchical clustering
  • Text documents and tweets clustering to aid understanding

  Discovering connections with Link Analysis

  • Using Social Network Analysis  to capture important connections
  • Usage of social networks results in marketing
Usage of Transaction Data in order to get the results regarding Association and Recommendations Rules

  Building and evaluating association rules

  • Knowledge about customer preferences in transaction data to enhance customer experience
  • Support, confidence and lift calculation to distinguish “good” rules from “bad” rules
  • Differentiating actionable, trivial and inexplicable rules
  • Searching large data sets for rules with RHadoop

  Constructing recommendation engines

  • Cross-selling, up-selling and substitution as motivations
  • Leveraging recommendations based on collaborative filtering
Implementing Analytics within Your Organization

  Expanding analytic capabilities

  • Use manageable steps for Big Data Analytics
  • Integrating analytics into current business processes
  • Spark, MLib and Mahout review for machine learning

  Dissemination and Big Data policies

  • Examining ethical questions of privacy in Big Data
  • Disseminating results to different types of stakeholders

data analytics certification FAQ’s:

1.Can the fee for data analytics training be paid in installment?

Yes! You can pay the fee in installments. The course is affordable so you can pay full fee at once and get the benefit of the course.

2.Which mode of payment can I use to pay the fee?

You can use credit cards, debit cards, bank transfer and other modes of payment.

3.How can I practice the code written in R and Python?

We will provide you all the facilities for practicing codes of R and Python Language.

4.Will I get any certificate after completing data analyst training

Yes! You will get a certificate after completing the course of data analyst training.

5.In what format will we get the certificate?

You will get an online data analytics certificate and we will also provide physical copies of the certificate.

6.What is a data analytics manager’s salary?

The data analytics manager salary is $112K.

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