Long-Term FDPs (4-6 Days)

Our Long-Term Faculty Development Programs deliver extensive, in-depth training on advanced research methodologies and analytical tools. These programs are specifically developed for the faculty members and research scholars who wish to acquire expertise in advanced research methods and techniques. The long tenure is utilized to delve deep into intricate topics, hands-on practice sessions, and cooperative learning opportunities. 

Structural Equation Modeling – AMOS / Smart PLS

This intensive course is an in-depth study of the theoretical background and hands-on applications of Structural Equation Modeling (SEM), a sophisticated statistical method of testing and estimating causal relationships. Students learn how to master both covariance-based SEM with AMOS and variance-based SEM with SmartPLS. The course includes model specification, identification, estimation, assessment, and interpretation, and enables students to use these methods in their research projects. Through interactive sessions, members are trained in building, testing, and iterating measurement and structural models, analyzing direct and indirect effects, and resolving common issues in implementing SEM.

Mixed Method & Multi-Method Research Designs

This course delves into the combination of qualitative and quantitative methods in research design, data gathering, and analysis. Learners are taught to create strong mixed-method research designs that take advantage of both methods' strengths while avoiding their weaknesses. The course discusses several mixed-method typologies, sampling schemes, data gathering methods, analytical practices, and quality indicators. By case studies and hands-on exercises, participants learn to design and conduct mixed-method studies solving challenging research questions and giving rich insights into the phenomena under study.

Python/R for Business Data Analytics

This interactive program trains participants in programming in Python and R for sophisticated data analytics in business research. From rudimentary syntax and data types, the course moves on to sophisticated concepts like data manipulation, statistical analysis, machine learning, and data visualization. Through hands-on exercises, learners acquire skills to apply a wide range of analytical techniques, ranging from descriptive statistics to predictive modeling, against real-world business datasets. The course highlights real-world applications, allowing participants to utilize these powerful programming languages to derive meaningful insights from intricate business data and improve the rigor and relevance of research.

Content & Thematic Analysis using NVivo

This course centers on qualitative data analysis with NVivo, a premier software tool for handling and analyzing unstructured data. Participants acquire systematic methods in content and thematic analysis from data preparation and coding to pattern discovery and theme development. The course addresses several analytical methods such as coding models, matrix coding questions, relationship mapping, and visualization tools in NVivo. By hands-on practice with varied data sources like interviews, focus groups, and documents, participants become skilled in deriving useful insights from qualitative data and communicating them in engaging terms.