CHRIST CUx

Skills

Our curriculum matches modern standard practices to provide exceptional training milestones.

Learning Outcomes

Our curriculum matches modern standard practices to provide exceptional training milestones.

Quantitative Research Fundamentals

Understand the core principles of quantitative research and statistical methods used to collect, analyze, and interpret numerical data effectively.

CORE KNOWLEDGE

Statistical Concepts

Learn essential statistical concepts, including data types, measures, distributions, and probability, to support accurate quantitative analysis and interpretation.

STATISTICAL FOUNDATIONS

Data Analysis Techniques

Apply quantitative data analysis techniques to organize datasets, identify patterns, and generate meaningful insights for informed decision-making.

ANALYTICAL SKILLS

Interpreting Numerical Results

Develop the ability to interpret statistical outputs, evaluate findings, and communicate numerical results with clarity and confidence.

DATA INTERPRETATION

Evidence-Based Decision Making

Use quantitative evidence and statistical reasoning to evaluate alternatives, solve problems, and support informed business and research decisions.

DECISION MAKING

Practical Data Applications

Apply quantitative analysis methods to real-world datasets, strengthening analytical thinking and practical problem-solving across diverse disciplines.

PRACTICAL LEARNING

ELIGIBILITY CRITERIA

UG - 2nd and 3rd years and First Year PG

Course Instructor

Expert guidance from acclaimed industry professional leaders.

Dr. M. Martha Sucharitha

Associate Professor

Dr. M. Martha Sucharitha is an Associate Professor specializing in Finance, Predictive Analytics, Machine Learning, and Quantitative Research Methods. With extensive teaching and research experience, she is passionate about simplifying data analysis through practical learning. Her work empowers learners with analytical skills for research, business, and evidence-based decision-making.

Program Overview

Academic Curriculum

A meticulous, guided learning path engineered to transform your cloud engineering expertise.

Module 1

Introduction to Quantitative Data

Module 2

Methods of Data Visualization

Module 3

Descriptive Statistics

Module 4

Probability & Probability Distribution

Module 5

Inferential Statistics & Hypothesis Testing

Module 6

Correlation & Regression Analysis

“

Sania Fathima

MBA

“The course provided useful knowledge and insights related to the subject. The content was informative and relevant, and it helped me gain a better understanding of the concepts covered.”

“

Kaushik Vallioor Sankaran

MBA

“I thoroughly enjoyed the Micro Credential course. It was direct and very informative.”

“

Adrija Roy

MBA

“The modules were structured in a simple and accessible way, making the concepts easy to understand even without prior knowledge of the topic. The workbooks provided valuable hands-on practice, and the course was an enriching learning experience that helped me build practical skills and confidence.”

“

Xavier Amith J

MCA

“The hands-on demonstrations and coding sessions were my favourite part. Overall, it was a valuable learning experience that helped me learn beyond the classroom, explore a new area, and become more curious about what AI can do.”

“

M A Lekshmi Narayanan

BCom

“It was interesting to learn about a new topic which was predominant in the world. The videos were short and kept me engaged throughout the course.”

Foundations of Quantitative Data Analysis

Overview

Credentials and Certification

Students exploring industry-relevent skills

Professionals planning to upskill and reskill

Faculty building digital deployment literacy

Course Menu

COURSE DELIVERY