Data Science Training in BTM Layout - Bangalore

Best Data Science Training in BTM Layout with Placement Assistance


Data Science Training

TecMax is one of the leading Data Science Training Institute in Bangalore. Certified experts at TecMax are real-time consultants at multinational companies and have more than 5+ years of experience in Data Science Training. Our Trainers have conducted more than 200 classes and have extensive experience in teaching Data Science in most simple manner for the benefit of sudents.

We have advanced lab facilities for students to practice Data Science course and get hands-on experience in every topics that are covered under Data Science Training. In the presence of Data Science Trainer, students can execute all the techniques that has been explained by the instructor. Course Material for Data Science is specifically designed to cover all the advanced topics and each of the module will have both theory and practical classes. Data Science Batch Timings at TecMax are flexible and students can choose to join the batch as per their requirements. We have a batch starting every week for Data Science for regular students. Weekend batches and fast track batches for Data Science training can be arranged based on the requirement. 

All our students will get placement assistance in Data Science after successfully completing the Data Science training from our institute. We are committed to provide high-quality training and provide assistance to get you the right job.


Data Science Training Course Content

 Statistical Analysis:

vUnivariate Analysis

vMeasure of Central Tendency

vMean( Arithmetic, Geometrical, Harmonic)

vMedian

vMode( Categorical)

 vQuartiles

v1st, 2nd, 3rd, nth-Quartile

 vMeasures Of Dispersion

vRange

vIQR

vVariance

vStandard Deviation

    vDistributions

v  Frequency Distributions

              Normal Distribution ( Symmetric)

              Asymmetric Distribution

             Skewness

             Kurtosis

vProbability Distributions

   vSampling Techniques

vEstimate Sampling Errors

vDegrees of Freedom

vConfidence Intervals

vProbability

 Multivariate Analysis:                                      

vCorrelation Analysis

vPredictions

vRegression Analysis

vLinear Regression (Simple/Multi)

vNon- Linear Regression

vLogistic Regression

vLasso Models

   vHypothesis Testing Models

vInferential Test Metrics

vr-test

vf-test

vz-test

vChi-square test

vstudent test

Data Mining:

vAll above +

vData Clustering/ Categorizations

vKmeans

vKNN( K Nearest Neighbour)

 

vPredictives

vDecisions Science(Operational Research)

vDecision Tree

vRandom Forest

vForecasting

v       Time Series Analysis(Time Line Estimation)

v       Season Identification

v       Trend Analysis

v       Bend Moment Analysis

v       Different Basket Analysis(Ex- Recommending)

                     Products/Features/Options

 

ARM(Association Role Management):

vApriori  Algoritham

vFP Growth

Machine Learning:

vAll Stat + Mining

vSupervised Learning

vUnsupervised Learning

vData Sets used in ML

vTrain Set

vValidation Set

vTest Set

vGradient Desent Algorithm

vDeployment of Modelfit in to Production

vTesting Accuracy ( Performance ) of Production Modelfits

vRebuilding Models

vModel Selection

 Neural Networks:

vStar + Mining + ML

vPower of Brain

vWhere Brain Bad

vNeuron Architecture

vHow Different Neurons Will Communicate

vStochastic Models

vDeveloping Learning Systems Using Human Brain Models

vFeature Extractions( Feature Engineering)

vRecent Data Buffering

vInfluenced Data Buffering

vForward / Backward Propagation Algorithms

 Deep Learning:

vIntegrated Best Features of Both Machine Learning and Neural Networks

 Text Mining:

vSentiment Analysis

vUser Behavioural Analysis

vGraph Data Processing

vTopic Categorization

vCustomer Review Analysis

vIdentifying User Expectations and Preferences

vTopic Ranking

 Recommender Engineers:

vCollaborative Filtering

vFPGrowth

Technicals:

vImportance of Big Data for Data Science

vData Streaming for live Systems ( Ex-Flume/ Kufka)

vLive Analytics ( Real time-Analytics) (Ex: STORM)

vMicro Batch Process( Ex: Spark Streaming)

vBatch Process(Ex: Hadoop)



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