Quick Stats
Analytics is now a gamechanger and every organization is investing in Big data for better growth and sustainability
SAS Certification will help us enter into Analytics and build a bright future. R and Python help us adapt to new advancements towards evolution
Be it experienced professional or fresher every one of us must grow with a better vision. Adapt to Analytics R and Python for a healthy growth
Benefits
Analytics on SAS Certification- Complete programme
Knowledge of Data Science, Predictive Modeling, Machine Learning and Statistical Techniques algorithms with data driven approach
Real time data driven projects
Development of analytical and decision-making abilities by examining real-life case studies and coming up with strategies and decisions
Certification
Certification on SAS Analytics-Regression and Modeling is a great value-add for the student’s resume, which can help an individual pursue a promising career or a career growth
SAS Analytics Certification
Industry recognized SAS Analytics-Regression and Modeling certification from SAS after completion of the program.
Career Rise
Looking for switch, career growth, enhancement, upskill. This is the perfect module designed for the same. Take a step forward and be a part of the future drive.
Who Should Attend
- Engineering and IT Students – BTech / BE, BCA, MCA, BSc-IT, MSc-IT
- Commerce & Finance Students - BCom / MCom, Economics Graduates, MBA or BBA
- Highly recommended for people aspiring for jobs that required data handling – Research, Marketing, IT Services, Big Data & more
- People who are already employed, but want to upskill themselves in the domain of Analytics
- As a prerequisite, its just your passion towards data and hard work that is the only requirement, rest is just a cake-walk.
Course Outcome
- Understanding of basic concepts and types of data
- Understanding of sampling techniques
- Dat Science and Machine Learnig concepts with application
- Understanding of frequency distributions and measures of central tendency, dispersion and shape
- In Depth Knowledge of the Hypothests testing T-Test ANOVA
- In depth knowledge on Correlation and Regression
- In depth Knowledge of Predictive modeling using Logistic Regression
- Two live projects which is full hands on real time industrial data
Curriculum
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Basic ConceptsEnroll NowIntroduction to SAS toolSAS Libraries /Temporary Library/ Permanent LibraryCreating LibrariesStart with a Basic SAS programsData Step / Proc Step / Statements/ Global statementsVariables / Datatypes / properties of Variables
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Access DataEnroll NowINFILE statement options to read raw data filesCreating a file refrence with filename statementDATALINES statement with an INPUT statement
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Starting With Raw Data(Basics)Enroll NowStyles of InputReading Unaligned Data / Understanding List InputUnderstanding Column Input / Reading Data Aligned in Columns
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Formats and InformatsEnroll NowStandard Data/ Non Standard DataHow Informats and Format worksWorking with Date/Time/Datetime informatHow and when to use Yearcutoff
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Starting With Raw Data( Beyond Basics)Enroll NowFormatted Input styleUsing Modifiers
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Mixing Styles of InputEnroll NowTesting a Condition before Creating an ObservationCreating Multiple Observations from a Single RecordReading Multiple Records to Create a Single Observation
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PDV: How the DATA Step WorksEnroll NowWriting Basic Data StepHow SAS Processes ProgramsCompilation phaseExecution PhaseDebugging a Data StepTesting SAS Programs
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Manipulating SAS DatasetsEnroll NowCreating & Modifying VariablesAssigning Values ConditionallySpecifying Lengths for VariablesSubsetting DataAssigning Permanent Labels and Formats
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Grouping Statements Using DO GroupsEnroll NowAssigning Values Conditionally Using SELECT GroupsReading a Single Data SetManipulating DataUsing BY-Group ProcessingReading Observations Using Direct Access (Point= option)Detecting the End of a Data Set(end= option)Understanding How Data Sets Are Read through PDVRenaming VariablesSelecting Variables
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Combining SAS Data SetsEnroll NowOne-to-One ReadingConcatenatingInterleavingMatch-MergingMatch-Merge ProcessingExcluding Unmatched Observations
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Transforming Data with SAS FunctionsEnroll NowGeneral Form of SAS FunctionsConverting Data with FunctionsRestriction for WHERE ExpressionsManipulating SAS Date Values with FunctionsSAS Date and Time ValuesSAS Date FunctionsModifying Character Values with FunctionsModifying Numeric Values with FunctionsNesting SAS Functions
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Relevant base SAS proceduresEnroll NowAppend procedureSort procedureDatasets procedurePrintto procedureFormat procedureTranspose procedureImport procedureExport procedurePrint procedureTabulate procedureReport procedureMeans procedureSummary procedureFreq procedure
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Generating Data with DO LoopsEnroll NowConstructing DO LoopsIntroduction to Constructing DO LoopsDO Loop ExecutionCounting Iterations of DO LoopsDecrementing DO LoopsNesting DO LoopsIteratively Processing Data That Is Read from a Data SetConditionally Executing DO LoopsUsing Conditional Clauses with the Iterative DO StatementCreating Samples
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Processing Variables with ArraysEnroll NowCreating One-Dimensional ArraysUnderstanding SAS ArraysDefining an ArrayVariable Lists as Array ElementsReferencing Elements of an ArrayCompilation and ExecutionUsing the DIM Function in an Iterative DO StatementCreating Variables in an ARRAY StatementCreating Temporary Array Elements
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Analytics-An IntroductionEnroll NowWhat is Business AnalyticsDifference between Analytics and AnalysisImportance of Analytics in IndustryApplication of Analytics in IndustryLearning and the growth curve of AnalyticsPuzzleInterview Preparation
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Data and Variables-An introductionEnroll NowWhat is StatististicsWhat is an Average- Mean Median ModeDifferent types of Data and variablesBasic Statistical MeasuresPuzzleQuizCoding-An IntroductionDependent and Independent Variable
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Population and Sample-Sampling techniquesEnroll NowWhy do we need sample over a populationDifference between population and sampleSampling TechniquesSimple Random SamplingStratified Random SamplingSampling with and without replacementPuzzleAssignment
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Normal Distribution & Central Limit TheoremEnroll NowIntroduction to Bell CurveDeviation Vs Standard DeviationVariance and Standard deviationOutliers and their effects on basic statistical measuresSymmetric and Asymmetric curveBell Curve-Emperical Rule--Grading processQuiz
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Exploratory data AnalysisEnroll NowUnivariate anlysis vs Bivariate analysis Vs Multivariate analysisDecile, Percentile,Vintile,Quartile,QuantileProc Univarite- DetailsMoments , Basis Statistical Measures, Test for Location, Quantiles , Extreme ObservationAssignmentPuzzle
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Data VisualizationEnroll NowBox and whiskers plotRanking Algorithm-Proc Rank in detailOutlier- Detection Removal TreatmentMissing values- How critical are they to a dataMissing value Removal and imputationProc for missing value Treatment
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Hypothesis TestingEnroll NowHypothests testing - What does that meanWhat is Hypothesis and what we do we testNull Hypothesis and Alternate HypothesisSignificanace level and Confidence level- P value and α valueDecision making- Reject/Fail to Reject Null HypothesisConfidence IntervalAccuracy and ErrorType I Error and Type II Error
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Campaign ManagementEnroll NowTest and Control groupSolicit and Non SolicitResponder and Non ResponderTargets and Non TargetsMeasuring Cost/Revenue/Profit of a campaign2*2 profit/revenue contingency matrixActual Vs predicted conflictsAccuracy Error Sensitivity SpecificityPuzzleInterview preparation
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One Sample T-TestEnroll NowOne Sample T-test- What is the hypothsis for this testOne Sample T Test using proc ttestOne Sample T Test using proc univariateSides of a test- One sample- two sided, Upper tail, lower tailHow to apply T-test to the dataHow will this help in making a decisionGraphical interpretation of T testPuzzleAssignmentAssumptions to a 1 sample T Test
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Two sample T-test & Sides of a testEnroll NowDifference between a one sample and a two sample T-TestHypothesis for a T TestProc T Test for 2 sample T TestUnderstanding the results from the statistical point of viewPlotting the graph for visulizing T-TestSides of 2 sample T Test-2 sided, Lower tail and upper tailApplication of 2 Sample T TestPuzzleQuizAssumptions to 2 sample T-TEst
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Anova-Analysis of VarianceEnroll NowWhy do we need AnovaWhy cant we use a 3 Sample T TEstHypothesis Testing for AnovaAssumptions to Anova1 way Anova vs N Way AnovaPerforming 2 sample T test using AnovaCoefficient of determinationDegree of FreedomLevenes Test and F testInteraction - Type 1 and Type III SSBalanced Vs Unbalanced designProc AnovaProc GLMPuzzleInterview Preparation
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Anova-Post Hoc Analysis TestEnroll NowWhy apply Post-hoc Test when applying AnovaControlled Design experimentExperimental Error RateMultiple Comparison TestReferential comparisonTukey and Dunnett Test- Sides of a testDiffogram and Control PlotMeans Vs LS MeansPuzzleMock Test
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Correlation-Different typesEnroll NowWhat is CorrelationWhy do need correlation analysis in any other analysisHow to measure correlationPearson and Spearman CorrelationCorrelation-Hypothesis TestProc CorrCorrelation MatrixCorrelation-graphical representation and InterpretationPuzzleCase Study
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Regression -Exploring the algorithmEnroll NowSimple Linear Regression and Multiple Linear RegressionRegression-Hypothesis TestingDegree of FreedomAnova table for RegressionWhat is Ordinary least squareParameter Estimate and InterceptSignificant and Non Significant VariablesRemoving RedundancyCollinearity- VIFPuzzleAssignment-Discussion
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Regression - Model BuildingEnroll NowRegression- Model BuildingR square and adjusted R square2 way honest assessment3 way honest assessmentHow to split Training validation TestOversampling Undersampling Overfitting UnderfittingModel Selection techniquesvariable selection techniquesModel building Vs Model FittingModel fit statisticsPuzzleMock Test
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Logistic Regression-IntroductionEnroll NowLogistic Regression-An IntroductionLogistic Regression-Need and the necessityWhy cant we apply regression everywhereAlgorithm to Logistic RegressionAsssumption to Logistic RegressionChecking the linearity amongst variablesChecking for collinearityRemoving Non LinearityRemoving Non LinearityLogistic Regression- Hypothesis testing
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What are odds ratioOdds ratio vs probabilityLog oddslog Vs natural LogComplete seperation Vs Quasi Complete SeperationData ConvergenceFischers TechniqueCreating and identifying the dependent variableData preparation for model building process
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Logistic Regression-Model BuildingEnroll NowSampling data for Training Validation TestFine tuning Assessment and final assessmentOut of sample validationOut of time validationVariable transformationVariable reduction techniquesVariable clusting techniquesIdentifying Collinearity amongst variablesInterpretation of Results
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Cumulative Lift ChartCumulative Gain ChartRelative operating characteristicsArea under the curveModel fit statisticsvalidation statisticsVariable selection techniquesSignificant and non significant variablesIdentifying the best variables for a model
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Model selection techniquesParameter estimate and Intercept% Concordant, %Discordant, %ties pairsCalculatig C value from the statisticsPuzzleInterview PreparationCase studyComparing training and validation statistics
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SAS SQL 1: EssentialsEnroll NowIntroducing the Structured Query LanguageOverview of the SQL procedureSpecifying columnsSpecifying rows
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Displaying Query ResultsEnroll NowPresenting dataSummarizing data
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SQL JoinsEnroll NowIntroduction to SQL joinsInner joinsOuter joinsComplex SQL joins
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SubqueriesEnroll NowNoncorrelated subqueriesIn-line views
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Set OperatorsEnroll NowIntroduction to set operatorsUnion operatorOuter Union operatorExcept operatorIntersect operator
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Creating Tables and ViewsEnroll NowCreating tables with the SQL procedureCreating views with the SQL procedure
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Advanced PROC SQL FeaturesEnroll NowDictionary tables and viewsUsing SQL procedure optionsInterfacing PROC SQL with the macro language
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SAS Macro LanguageEnroll NowIntroductionGetting Familiar to the macro facility
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Macro VariablesEnroll NowIntroduction to macro variablesAutomatic macro variablesMacro variable referencesUser-defined macro variablesDelimiting macro variable referencesMacro functions
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Macro DefinitionsEnroll NowDefining and calling a macroMacro parameters
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DATA Step and SQL InterfacesEnroll NowCreating macro variables in the DATA stepIndirect references to macro variablesCreating macro variables in SQL
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Macro ProgramsEnroll NowConditional processingParameter validationIterative processingGlobal and local symbol tables
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Advanced SAS Programming TechniquesEnroll NowMeasuring Efficiencies
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Controlling I/O Processing and MemoryEnroll NowSAS Data step processingControlling I/OUsing SAS viewsReducing the length of numeric variablesCompressing SAS data sets
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Accessing ObservationsEnroll NowCreating a sample data setCreating an indexUsing an index
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Using DATA Step ArraysEnroll NowIntroduction to lookup techniquesUsing one-dimensional arraysUsing multidimensional arraysLoading a multidimensional array from a SAS data set
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Using DATA Step Hash and Hiter ObjectsEnroll NowIntroductionUsing hash object methodsLoading a hash object with data from a SAS data setUsing the DATA step hiter object
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Combining Data HorizontallyEnroll NowDATA step merges and SQL procedure joinsUsing an index to combine dataCombining summary and detail dataCombining data conditionally
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Expert Programmer TechniquesEnroll NowCreating user-defined functionsThe experts’ FORMAT procedure
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Understanding the R environment:Enroll NowSetting up the machine and installing RSetting up the R environment for the smooth usage of RUnderstanding the various IDEs for R developmentInstallation/Removal of packages
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Importing raw dataEnroll NowReading csv files into RReading json files into RReading txt files into RReading sas7bdat files into R
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Data structuresEnroll NowUnderstanding homogenous and hetrogenous form atomic vectors in R including Dataframes, List, Vectors, Factors and Matrices in RAtomic vectors in RDataframes, List, VectorsFactors and Matrices in R
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Style GuideEnroll NowCoding standards-Know HowNotation and NamingFilenamesObject namesSyntaxCurly BracesSpacingLine lengthIndentationAssignmentCommenting Guidelines
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Loops and vectorizationEnroll NowWriting For and while loops in RUnderstanding if loops are really a necessary in RUnderstand the apply family in R
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Functions and conditionalsEnroll NowWriting functions in RUnderstanding if...then...else in RUndersanding pure functions in R and understanding the purrr package in R
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summarizationEnroll NowUnderstand the meaning of clusteringHierarchial clustering in RK means clustering in R
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GLM FamilyEnroll NowLinear regression in RMulticollinearity and calcualtion of VIFRoot mean squared error, t statistic, pvalue and confidence intervalLogistic regression in RRoC, TPR, Lift, Gain and KS statistic in RInterpreting the Linear and logistic ModelUnderstanding ridge and lasso in linear and logistic model
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Decision TreesEnroll NowDecision Trees in RUnderstanding Ginni IndexKnowing the difference between CART and CHAIDWorking with Random Forest
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Optimization in REnroll NowWhat is optimization?Working with opimiztion packages in R (e.g Optimx)Constrained optimisation ( Lagrange multipliers )
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Bonus TopicEnroll NowBasics of GGPLOT2Scatterplots in RHistograms and density plots in RUnderstanding basics of "Grammer of Graphics" concept
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Introduction to MLEnroll NowWhat is LearningComponents of learningA simple learning modelTypes of LearningWhat is machine learningApplication of ML
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Getting started with PythonEnroll NowWhat is PythonOrigins and versions of PythonWays to run a Python programSetting up Python environmentBasic file operations with PythonBasic data operations with PythonBasic data visualization with PythonHands on with Python
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Process in any MLEnroll NowBasic process flow of any machine learningTerminologies used in MLEvaluation metrics used in MLComparison of ML and Statistical learning
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RegressionEnroll NowSimple Linear RegressionMultiple Linear RegressionConsideration in RegressionAccessing the accuracy of Coefficient estimatesAccessing the accuracy of ModelFun example and workshop!
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ClassificationEnroll NowAn overview of classificationWhy not linear regressionLogistic ModelLinear discriminant AnalysisComparing classificationFun example and workshop!
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Support Vector machinesEnroll NowIntroductionGeneral conceptsComponents of SVMRelationship with Logistic regressionFun example and workshop!
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Decision TreesEnroll NowIntroductionBasics of a treeClassification with treesAdvantages / disadvantages of tree
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Random ForestEnroll NowIntroductionHow Random forest worksDifferent parameters in RFFun example and workshop!
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Gradient boosting machinesEnroll NowIntroductionHow GBM worksDifferent parameters in GBMFun example and workshop!
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ClusteringEnroll NowIntroductionK- Means clusteringHierarchical ClusteringPractical issues in clustering
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Natural Language processingEnroll NowGeneral text processingTokenizingStop wordStemmingPOS taggingChunking/chinkingLemmatizingCorporaBuilding text only modelsFun example and workshop!
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Neural NetworkEnroll NowIntroductionImportant concepts in NNBuilding NN for classificationFun example and workshop!
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Building a recommender SystemBuilding a sales prediction modelRetrieving twitter feeds and sentiment analysis
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Basic TableauEnroll NowIntroduction – Why data visualizationArchitecture of TableauWelcome! What is Tableau & Course Overview?Installation
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Data connectivity and navigationEnroll NowConnecting Tableau with different data sourcesWorking with data extractsNavigating tableau
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My first visual - Bar chartEnroll NowBusiness challengeCreating calculated fieldAdding colorsAdding labels and formattingExporting the worksheet
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Other charts in TableauEnroll NowTree mapBubble chartBullet chartPie chartOther visuals
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Time series, aggregation and filtersEnroll NowWorking with time seriesUnderstanding Aggregation, Granularity and level of detailsCreating area chart and learning about highlightingAdding quick filters
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Maps and scatter plotEnroll NowCreating maps and working with hierarchiesCreating scatter plot and applying filters in multiple sheetsLet's create the first dashboardApply action filters
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Joining and Data blendingEnroll NowUnderstand left, right, inner, outer joinsJoins with duplicate valuesJoin data vs Blending data in TableauEditing blending relation
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Advanced TableauEnroll NowGroups and SetsWorking with GroupsCreating dynamic setsCombining setsControlling sets with parameter
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Advanced Table calculationEnroll NowCreating multiple joinsCalculated field vs Table CalculationCreating advanced table calculationSaving quick table calculationSpecifying direction of computationWriting your own table calculationAdding second layer of moving averageQuality assurance of table calculationTrend lines for power insights
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Building box plots in TableauAnalysing box plotsWorking with large data sourcesPivot and splitTrend linesData prep exerciseAdvanced time series blendingForecasting in TableauIntegration of Tableau with R
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Creating animations in TableauEnroll NowAdding animation in the visualization
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Level of details (LOD)Enroll NowLOD Type 1 (Include)Understanding ATTR in TableauLOD Type 2 (Exclude)LOD Type 3 (Fixed)Multiple fields in LOD Calculations
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Tableau ServerEnroll NowUsers and GroupsPublishing Dashboards to the serverDifference between Tableau online and Tableau server
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ProjectEnroll NowReal Time Project
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BigDataEnroll NowIntroduction to BigDataExamples and Categories of BigDataBenefits of BigData Analytics
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HadoopEnroll NowIntroduction to Apache HadoopFeatures of HadoopCore/Common components of HadoopHadoop Architecture/Framework (Clustered)Hadoop Ecosystem
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Hadoop Framework SetupEnroll NowPre-installation SetupInstallation ModesVerifying Hadoop InstallationAccessing Hadoop Cluster
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Hadoop HDFS (Hadoop Distributed File System)Enroll NowHDFS FeaturesHDFS ArchitectureObjectives of HDFSHDFS Operations
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Hadoop MapReduceEnroll NowIntroduction to MapReduce FrameworkMapReduce ArchitectureMapReduce ComponentsMapReduce Programming
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Hadoop YARNEnroll NowIntroduction to YARNYARN MapReduce Application Execution FlowYARN Workflow
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Apache HiveEnroll NowIntroduction to Apache Hive FrameworkHive Framework ArchitectureHive Framework ComponentsHive MetastoreHive Framework SetupHiveserver2 and Beeline InstallationHive QL (Query Language) operations
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Apache FlumeEnroll NowIntroduction to Apache Flume FrameworkApplications and Advantages of Apache FlumeFeatures of Apache FlumeApache Flume StreamingApache Flume SetupApache Flume Operations
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Apache SqoopEnroll NowIntroduction to Apache Sqoop FrameworkFeatures of Apache SqoopApache Sqoop SetupApache Sqoop Operations
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Apache PigEnroll NowIntroduction to Apache Pig FrameworkApplications and Advantages of Apache PigFeatures of Apache PigApache Pig ComponentsApache Pig SetupApache Pig Execution ModesApache Pig Execution MechanismsIntroduction to Apache Pig Latin LanguageApache Pig Latin Operations
Instructors
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Vikhyat
Chief Data Scientist
Vikhyat is a Business Consultant and worked with prestigious companies like TCS, American Express, Mu Sigma in the past 10 years and has been working in the Analytics industry since the beginning of his career.
He has worked for international and domestic markets markets as an expert in Predictive modeling and forecasting role in the field of Business Analytics. He co-founded PSTAn.... Vikhyat is a Business Consultant and worked with prestigious companies like TCS, American Express, Mu Sigma in the past 10 years and has been working in the Analytics industry since the beginning of his career.
He has worked for international and domestic markets markets as an expert in Predictive modeling and forecasting role in the field of Business Analytics. He co-founded PSTAnalytics in 2010, and has taken up the initiative to spread quality education
He has worked extensively in domains such as Customer Segmentation , Market benchmarking, Customer profiling, Customer targeting, Credit card life cycle , generating Score card, Phases in clinical cycle,Market Research, Brand positioning, Building Go-to-market strategies, Pricing for clients in various sectors like BFSI, Healthcare,Automotive, Hi-tech, and Telecom. His day to day task include Credit Risk projects, propensity and attrition modeling, Credit risk score cards, Cross sell and Up sell Pre & Post campaign management.
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Lokesh
Business Leader- Data Insights
Lokesh is a Senior SAS consultant and worked with prestigious companies like Genpact, Target, Barclays, MasterCard in the past 10 years and has been working in the Data industry since the beginning of his career
He has worked for international markets as an expert in data preparation and insights in the field of Analytics. He co-founded PSTAnalytics in 2010, and has taken up the.... Lokesh is a Senior SAS consultant and worked with prestigious companies like Genpact, Target, Barclays, MasterCard in the past 10 years and has been working in the Data industry since the beginning of his career
He has worked for international markets as an expert in data preparation and insights in the field of Analytics. He co-founded PSTAnalytics in 2010, and has taken up the initiative to spread quality education
He has worked extensively in domains such as Retail ,Pharma , BFSI ,Healthcare,Automotive, Hi-tech, and Telecom. His day to day task include campaign management, production, Data Warehousing, ETL, and process development for batter insights and rapid delivery with precision
https://www.linkedin.com/in/lokesh-rajput/
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Gaurav
Senior consultant Machine Learning
Gaurav is a Business Consultant and worked with prestigious companies like TCS, American Express, AON in the past 10 years and has been working in the Analytics industry since the beginning of his career.
He has worked for international and domestic markets as an expert in Predictive modeling and forecasting role in the field of Business Analytics
.... Gaurav is a Business Consultant and worked with prestigious companies like TCS, American Express, AON in the past 10 years and has been working in the Analytics industry since the beginning of his career.
He has worked for international and domestic markets as an expert in Predictive modeling and forecasting role in the field of Business Analytics
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FAQS
Is this a module or a complete course?
This is a complete course. Technically the course is Analytics on SAS Certification for which we cover five modules- SAS Base Certification, SAS Analytics Certification, SAS Advance Certification, R and Python
Is this a distance or online program?
This is an instutor led workshop program, available in 2 modes – Instructor-Led and self paced.
What is the difference between instructor led and self paced program?
In the self paced programme learners have to learn about the course on their own using the study materials provided to them after registration.There would be recorded videos which will be throughout this programme.
In the Instructor-led version, learners will be provided assistance of faculty who will take them through the course as a part of classrom/ live webinar mode.
In case if I missed a class?
Every class is recorded and In case you miss a class you can go through the recordings and let us know in case of doubts. You can even sit in other regular classes for the sessions that you missed
Is there any option of face-to-face classes?
Yes, this is a classroom programme. In case you are not able able to make up for the class you can use the link to connect online through a webex link and can attend the same LIVE class without even coming to the class.
What is the duration of Analytics program?
Its a weekend programme comprising 40 Hours. It would take 10 weeks or 2 months to cover the module in full.
You just need to spend not more than 30 minutes a day to become a successful Analyst.
What are the speciality of this module?
Our Analytics module is aligned to current industry requirements, uses latest tools and techniques and the curriculum of the course has been developed in consultation with industry practitioners.
Which certification will I be eligible for?
You would be eligible for SAS certifcation exam conducted by SAS with global recognition.
We will conduct exam prepration classes for the same and this is included as a part of the module
Does the fees also includes the SAS certification fees
The preparation classes are complimentary and the exam needs to be booked. The exam fees is not included as a part of the programme
How is this SAS certification different from the certificates provided by other institute
SAS certification is conducted by SAS and recognized globally. Upon successful completion your name appears on the website and anyone can check that. The certificates provided by institutes ae not recognized by any organizaion and hence not valid
What about the projects
The projects are industrial projects with real time data and not the mocked one. This is not a capstone project where you actually do not get a pretty idea how things work in industry. It will be hands on and live industrial data decision making projects