Training on Sectoral Programs
The following programs are offered through Workshops, Seminars and faculty development programs. Please call +919177573730 or write to academy@sriindia.in or academy.sri.india@gmail.com
I STATISTICAL MODELLING
PROGRAM  1: Basic statistical analysis through Calc & PSPP.
Duration; 5 hours.


Introduction to data science.

Descriptive statistics (Univariate & Bivariate): summary statistics like measures of central tendency, measures of dispersion, measures of shape. Cross tabulation.

Inferential statistics (Univariate & Bivariate): Statistical tests (chisquare test, T test, Z test, F test, other parametric and nonparametric tests)

Exploratory statistics (Bivariate & Multivariate): Correspondence analysis (including MCA, MJCA), Principal components analysis, Factor analysis, Cluster analysis.

PROGRAM  2: Advanced Visualization techniques through R language.
Duration: 5 hours


Creating statistical graphs  2D & 3D: bar charts, histograms, pie charts, box plots, line charts etc.; Scatter diagrams,

linear plots, QQplots, regression plots, contour plots, perspective plots; 3D plots; Animations; Creating flow charts and block diagrams; Image manipulation and editing.

PROGRAM  3: Advanced analytics through R language.
Duration: 5 hours


Structural Equation Modelling (SEM)

(Social) Network Analysis (SNA)

Artificial Neural Networks (ANN)

Text Analytics (Text Mining/TM)

Natural Language Processing (NLP)

Data mining and Web scraping

II HEALTH CARE & MEDICINE
PROGRAM 1: Data analytics for better health care decisions
Duration: 5 hours
Tools: Excel, Calc, PSPP, SPSS, R and SAS.

Summary statistics: central tendency, dispersion and shape.

Statistical tests or diagnosis: parametric & nonparametric and hybrid tests.

Association and linear modelling: bivariate ) canonical correlation, simple regression, logistic, predictive modelling, Cross tabulation and other association techniques.

Effective visualization techniques

Multivariate analytics: Correspondence analysis, PCA, MCA. MJCA, HCPCA, Exploratory and Confirmatory Factor Analysis, Cluster analysis and MDS

Advanced analytics: Artificial neural networks, Text analytics for medical transcription

Structural equation modelling

Social network analysis

Big data analytics
PROGRAM 2: Text Mining for Clinical Data Analysis through R
Duration: 4 hours

Data Import & Export

Inspecting Corpora

Data Transformations

Filtering

Meta data Management

Creating TermDocument Matrices

Operations on TermDocument Matrices

Dictionary operations
PROGRAM 3: Medical Image Analysis through R language
Duration: 5 hours

Magnetic resonance imaging (MRI): diffusion tensor imaging (DTI), Dynamic contrast  enhanced MRI (DCE  MRI), functional connectivity, functional MRI, structural MRI, visualization, simulation of time series and 4D data.

General image processing.

Positron Emission Tomog

Digital imaging and communications in medicine (DIACOM)

raphy (PET)

Electroencephalography (EEG).
III BIOINFORMATICS
PROGRAM 3: Open source tools for bioinformatics
Duration: 5 hours
Tools: Calc, PSPP and R.

Data Display & Discriptive statistics

Probability Distributions

Estimation and Inference

Linear Models

Cluster Analysis & Trees

Classification Methods

DNA Sequence Statistics

Micro Array Analysis
IV FINANCE
PROGRAM 1: Risk Modeling Through R Language
Duration: 5 hours

Probability distributions for returns

Methods and models of valuation

Modeling volatility

Modeling dependence

Robust portfolio optimization techniques

Tactical asset allocation techniques

Testing and reporting portfolio strategies
PROGRAM 2: Fraud Analytics for effective risk modeling
Duration: 5 hours
Tools: R language

Binning

ROC Curves

KS statistics

Logistic Regression & predictive analytics

Tree algorithms

Plotting trees

Assessing complexity of trees

Trees to rules

Conditional inferences

Estimation of trees with Logistic regression

Baysian Networks

Graphical & numerical analysis
V COMPUTER SCIENCE AND ENGINEERING
PROGRAM 1: High Performance and Parallel Computing" (Big data analytics through R Language)
Duration: 5 Hours

Explicit parallelism

Implicit parallelism

Grid computing

Hadoop

Random numbers

GPU computing

Resource (memory) management
For other programs or special training through R language please visit http://sriindia.in/rtraining