MCA Data Science
Education goes beyond textbooks and classrooms. We believe in empowering students to explore their passions challenge conventions.
Our university offers a comprehensive range of academic programs designed to inspire learning, innovation and real-world impact Each program is carefully crafted to blend theoretical knowledge with practical experience ensuring students gain the skills needed to excel in today’s competitive global environment From foundational undergraduate courses to advanced postgraduate and professional degrees our curriculum emphasizes critical thinking hands-on learning, and industry relevance With guidance from experienced faculty access to modern laboratories and opportunities for research and internships students are empowered.
Faculty
Engineering
Duration
2 Years
Language
English
About Programs
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Master of Computer Applications (24 Months)
Session: 2025 - 2026
Typical Program Structure
A 24-month M.S. Statistics program usually follows a structure split across three or four academic terms (e.g., two semesters plus a summer term, or three quarters plus a summer term).
- Duration: 24 Months (Full-Time)
- Structure: Heavily focused on taught coursework and often culminates in a capstone project or dissertation completed over the summer.
- Duration: 24 Months (Full-Time)
| Core Curriculum Topics | |
|---|---|
|
Statistical Theory |
Theory of Statistical Inference, Advanced Probability Theory, Foundations of Statistics |
|
Statistical Modeling |
Linear Models and Regression Generalized Linear Models, Multivariate Analysis. |
|
Computational Statistics |
Statistical Programming (e.g., R and Python), Statistical Computing, Data Management |
|
Applied Methods |
Time Series Analysis, Design and Analysis of Experiments, Sampling Theory |
|
Modern Techniques |
Statistical Machine Learning, Advanced Statistical Learning, Data Science Methods |
Curriculum Overview
Our university curriculum is designed to deliver a balanced future-focused learning experience that empowers students with both academic knowledge and practical competencies Each program is structured to combine foundational coursework specialized major subjects hands-on learning and interdisciplinary opportunities By integrating theory research and real-world applications we prepare students to excel in a rapidly evolving global environment Students begin with core courses that build essential skills in communication, critical thinking, digital literacy, and quantitative analysis.
| Core Curriculum Topics | |
|---|---|
|
Statistical Theory |
Theory of Statistical Inference, Advanced Probability Theory, Foundations of Statistics |
|
Statistical Modeling |
Linear Models and Regression Generalized Linear Models, Multivariate Analysis. |
|
Computational Statistics |
Statistical Programming (e.g., R and Python), Statistical Computing, Data Management |
|
Applied Methods |
Time Series Analysis, Design and Analysis of Experiments, Sampling Theory |
|
Modern Techniques |
Statistical Machine Learning, Advanced Statistical Learning, Data Science Methods |
CDLU Campus Introductions
At CDLU, education goes beyond textbooks and classrooms We believe in empowering students to explore their passions challenge conventions and discover their potential through meaningful experiences Our distinguished faculty members are leaders their respective fields dedicated to delivering world-class education that integrates theory with practical.