For Appointment Call  +91 9901857466
Follow Us:

Students Training

CARES is committed to supporting academic institutions in their mission to provide high-quality education and foster intellectual growth among students, faculty, and staff. Our academic training programs are designed to enhance teaching and learning methodologies, promote professional development, and improve overall academic excellence.

We offer a wide range of academic training programs tailored to the needs of college institutions, faculty members, and students. Our programs cover areas such as effective teaching strategies, curriculum development, assessment and evaluation methods, data analytics and research skills, and academic leadership.

Through our academic training programs, we aim to empower educators with innovative teaching approaches, pedagogical techniques, and the latest educational technologies. We also provide students with the necessary skills and knowledge to excel in their academic pursuits and prepare them for future careers in the field of data analytics.

List of training offered


Excel - Beginner Level

Excel fundamentals, data entry and manipulation, basic formulas and functions.


Excel - Intermediate Level

Advanced formulas and functions, data analysis tools, pivot tables.


Excel - Advanced Level

Advanced data modeling, automation with macros, advanced functions (e.g., VLOOKUP, INDEX-MATCH).


Power BI - Beginner Level

Introduction to Power BI, data visualization basics, creating interactive reports and dashboards.


Power BI - Intermediate Level

Advanced data modeling, DAX formulas and functions, data transformation and cleansing.


Power BI - Advanced Level

Power Query, Power Pivot, advanced visualization techniques, advanced data analysis.


Tableau - Beginner Level

Introduction to Tableau, data connection and visualization basics, creating basic charts and graphs.


Tableau - Intermediate Level

Advanced chart types, calculations and parameters, interactive dashboards.


Tableau - Advanced Level

Advanced analytics, data blending, scripting and automation, server administration.


SPSS - Beginner Level

Introduction to SPSS, data entry and manipulation, basic statistical analysis.


SPSS - Intermediate Level

Descriptive statistics, inferential statistics, regression analysis.


SPSS - Advanced Level

Multivariate analysis, factor analysis, structural equation modeling.


Jamovi - Beginner Level

Introduction to Jamovi, basic data analysis, simple statistical tests.


Jamovi - Intermediate Level

Advanced statistical tests, data visualization, data cleaning and transformation.


Jamovi - Advanced Level

Complex statistical modeling, ANOVA, advanced data analysis techniques.


R - Beginner Level

Introduction to R, data types and structures, basic data manipulation.


R - Intermediate Level

Data visualization with ggplot2, statistical analysis with base R, programming fundamentals.


R - Advanced Level

Advanced statistical modeling, packages for specific analysis (e.g., machine learning, time series).


Python - Beginner Level

Introduction to Python, data types and structures, basic data manipulation.


Python - Intermediate Level

Data visualization with libraries like Matplotlib and Seaborn, data analysis with Pandas.


Python - Advanced Level

Advanced data manipulation and cleaning, machine learning with libraries like Scikit-learn, deep learning with TensorFlow or PyTorch.

For student level Research and data analytics (dissertation project) we offer the following:

Program Content

The program aims to bridge the gap between traditional research methods and data analytics, providing academics with the skills to integrate data analytics techniques into their research work. Participants will gain a comprehensive understanding of how data analytics can enhance research outcomes.

Program Outcomes

  1. Introduction to Research and Data Analytics
  2. Problem Formulation and Research Design
  3. Data Collection and Management
  4. Exploratory Data Analysis
  5. Statistical Analysis
  6. Advanced Data Analytics Techniques
  7. Integrating Research Findings and Data Analytics
  8. Ethical Considerations in Research and Data Analytics
  9. Research Project Development

Program Benefits

  • Comprehensive understanding of research methodologies and data analytics techniques
  • Enhanced quality and rigor of academic research through data analytics integration
  • Improved research outcomes through data-driven insights
  • Practical skills in data collection, management, analysis, and visualization
  • Enhanced research profile and staying updated with the latest trends

Note: The program can be customized to meet specific needs and requirements.

Key Outcomes

Critical Thinking