MLRIT Logo

B.Tech — Computer Science & Engineering (Data Science)

"Data Science at MLRIT gave me the tools to turn raw numbers into real decisions — Python, Spark, real datasets from day one."
CSE-DS StudentB.Tech — Computer Science & Engineering (Data Science)

Introduction

Dr. P. Subhashini
From the HOD's Desk

Our Data Science department fosters innovation in data analytics, machine learning, and cloud computing. With 22 research papers, 5 patents, and industry projects with Mu Sigma, Fractal Analytics, and Amazon, we equip students with skills to lead in the data-driven economy.

Dr. P. Subhashini, Professor & Head of Department

The Department of Computer Science and Engineering (Data Science) was established in 2020 to address the rapidly growing industry demand for data-literate engineers. Offering B.Tech with an intake of 120 students under the R25 regulation, the department is built around the Python, R and SQL ecosystem. Partnerships with leading analytics organisations provide students with real-world capstone projects that bridge academic knowledge and industry practice.

Vision and Mission

Vision

To be a leading centre for Data Science education, producing analytically skilled engineers who harness data ethically to solve complex societal and industry problems.

Mission

  • Deliver outcome-based education grounded in statistics and programming, equipping students with the analytical foundation required to solve complex data problems.
  • Foster a culture of real-world project work through industry partnerships, enabling students to tackle authentic data challenges across diverse domains.
  • Cultivate ethical data practitioners who understand privacy, governance and responsible use of data in all professional contexts.
  • Strengthen industry readiness through certifications, internships and placement linkages that prepare graduates for high-impact data science careers.
Innovative Teaching Methodology

The department adopts a project-driven pedagogy anchored in real datasets sourced from industry and public repositories. Every semester integrates Kaggle competitions, data journalism exercises and dashboard design workshops. Industry mentors from analytics firms guide capstone projects, while regular seminars on data ethics and emerging tools ensure students remain aligned with evolving professional standards.

Established in 2020, the Department of CSE (Data Science) was created to meet the surging demand for analytics professionals across industry and research. The inaugural batch graduated in 2024, achieving a 100% placement rate with offers from leading data-driven organisations. The department has since built a suite of six specialised laboratories and forged industry partnerships that support real-world capstone projects every semester.

Year-Wise Student IntakeGrowing Stronger Every Year60 STUDENTS201790 STUDENTS2019120 STUDENTS2020150 STUDENTS2021180 STUDENTS2022210 STUDENTS2023240 STUDENTS2024270 STUDENTS2025
Data Engineering Lab
ETL pipelines, Apache Kafka, Apache Airflow, workflow orchestration
Statistical Computing Lab
R, SAS, SPSS, hypothesis testing, regression modelling
Business Intelligence Lab
Tableau, Power BI, Looker, interactive dashboards, executive reporting
Database Systems Lab
PostgreSQL, MongoDB, Snowflake, query optimisation, schema design
Data Science Platforms Lab
Jupyter Notebooks, Databricks, Azure ML, experiment tracking
Cloud Analytics Lab
AWS Redshift, Google BigQuery, dbt, cloud-scale data transformation
Brochure