150 hours of exhaustive training program, covering the broad spectrum of Analytical and Data Visualization tools like R, SAS, Python, Advanced Excel with VBA, and Tableau on a solid statistical foundation including hands on projects.Module 1: Introduction to analytics and fundamentals of business statisticsModule 2: Working in R environmentModule 3: Theory of advanced business statistics for Data AnalyticsModule 4: Base and Advanced SASModule 5: Advanced Excel and VBAModule 6: Data analytics projects using R and SASModule 7: Data visualization using R and TableauModule 8: Introduction to Machine Learning through PythonModule 9: Industry interfacing programs and final project

100 hours of Data Science Training Program (DSTP) that covers the most in-demand tools like R, Python, Apache, Hive, Spark and implement concepts such as EDA (Exploratory data analysis), predictive modelling, hypothesis testing, machine learning algorithms and Big data.Module 1: Basic and advanced business statistics and machine learning algorithmsModule 2: Getting started with R environmentModule 3: Machine Learning and Data Analytics in RModule 4: Working in Python IDEModule 5: Machine Learning algorithms-IIModule 6: Implementing Machine Learning algorithms using PythonModule 7: Introduction to Big data , HadoopModule 8: Elective Domain Specialization and live projectsModule 9: Industry readiness program and mock interview and self assessment program

60 hours of compact training on Big Data and Hadoopalong with introduction to data analytics, designed by seasoned industry experts, covering Hive, Spark, R and other data mining and data analytics tools.Module 1: Understanding Big Data, Hadoop, HDFSModule 2: Hadoop Architecture, HDFSModule 3: Introduction to Hadoop MapReduce FrameworkModule 4: Advanced Hadoop MapReduceModule 5: Apache Pig & HiveModule 6: Advanced Apache Hive and basic HbaseModule 7: Advanced Apache HbaseModule 8: Processing Distributed Data with Apache SparkModule 9: OozieModule10: Data analytics using RModule11: Industry readiness program, mock interview and self assessmentBHTP includes live projects, assignments and lots of hands on experience

40 hours of training conducted by eminent academicians and senior researchers to facilitate research scholars to explore techniques of primary and secondary research covering research methodologies, sample design, questionnaire preparation and statistical analysis of data using SPSS and R.Module 1: Research methodologyModule 2: Methods of sample design and preparation of questionnaireModule 3: Collection of primary and secondary dataModule 4: Analysis of data using R, SPSS and Excel Module 5: Descriptive statistics, Regression and OLS, Factor analysis, Time series, Cluster analysisModule 6: Use of smart tools and infographics

25 hours of training on R programming and statistical techniques conducted by academicians and industry experts to introduce our participants in the area of data analytics.Module 1: Introduction to R environment and programmingModule 2: Statistics refresherModule 3: Data handling using R Module 4: Data analysis techniques using R packages (Basic descriptive statistics, correlation, Testing of Hypothesis, Regression, Role of R in data analytics: Case study)Module 5: Using graphics in RModule 6: Use of R in predictive modeling in specific domains by expertsIncludes projects, assignments and lots of hands on experience

40 hours of training conducted and designed by industry experts to induct participants in statistical techniques and base and advance SAS programming environment. Module 1: Intro to SAS environment Module 2: Statistics refresherModule 3: Data handling (procedures, sorting, merging & grouping)Module 4: Merging of SAS datasets Module 5: SAS macrosModule 6: SQL and Advanced SAS programming, Report generation Module 7: Analytics using SAS (Predictive modeling, projects)