B.Tech Data Science

Curriculum Structure

Mewar University, located in Chittorgarh, Rajasthan, offers academic pathways aligned with Data Science and emerging technologies through its School of Engineering & Technology and related Computer Science / IT departments. While Data Science is primarily integrated within core degree programs, the university provides strong exposure to Analytics, Artificial Intelligence (AI), Machine Learning, and Big Data across multiple levels of study.

What to Expect from Data Science–Related Programs at Mewar University

Program Structure:
Data Science concepts are embedded within programs such as B.Tech (Computer Science Engineering), M.Tech, MCA, and select diploma or certification courses, offering students a balanced foundation in computer science alongside specialized analytical skills.

Curriculum Highlights:
The curriculum blends core computer science subjects with statistical analysis, data handling, and programming, emphasizing tools and languages such as Python, R, SQL, and machine learning frameworks. Students engage in hands-on projects, case studies, and real-world data applications to strengthen practical understanding.

Departmental Access:
Prospective students should explore offerings under the School of Engineering & Technology and associated IT/Computer Science departments for Data Science–focused electives, modules, or specialization tracks.

Practical Learning & Placements:
Mewar University places strong emphasis on experiential learning, personalized academic support, and industry-oriented training. The institution actively promotes placement opportunities, with recent placement outcomes reflecting competitive salary packages in technology-driven roles.

Admission Process

The admission to B.Tech Computer Science program is based on entrance exam scores followed by counseling. Here's the step-by-step process:

Career Opportunities

Career Opportunities in Data Science

Data Science offers a wide spectrum of high-growth career opportunities, ranging from foundational analytical roles to advanced positions in Artificial Intelligence, Machine Learning, and Data Engineering. With applications across nearly every industry—including technology, finance, healthcare, retail, manufacturing, and government—data professionals play a critical role in transforming raw data into strategic business decisions.

Core Data Science Roles

Data Scientist
Focuses on analyzing complex datasets, building predictive and prescriptive models, and applying machine learning techniques to generate deep business insights.

Data Analyst
Responsible for cleaning, visualizing, and interpreting data to support decision-making. Commonly uses SQL, Excel, Python, and BI tools to identify trends and patterns.

Data Engineer
Designs, builds, and maintains scalable data pipelines, databases, and data infrastructure that support analytics and machine learning workloads.

Machine Learning Engineer
Develops, deploys, and optimizes machine learning models and algorithms, ensuring performance, scalability, and reliability in production environments.

Specialized & Emerging Roles

AI / ML Research Scientist
Works on developing new algorithms, improving existing models, and advancing the field of artificial intelligence and machine learning.

Data Architect
Designs the overall data strategy, including data models, storage solutions, and integration frameworks aligned with business goals.

Business Intelligence (BI) Analyst / Developer
Creates dashboards, reports, and visualization tools that enable leadership to make data-driven strategic decisions.

Quantitative Analyst / Statistician
Applies advanced statistical and mathematical models, particularly in finance, risk analysis, and research-driven domains.

MLOps Engineer
Bridges data science and IT operations by managing model deployment, monitoring, automation, and lifecycle management.

Career Progression Pathways

• Data Analyst → Senior Analyst → Analytics Manager

• Data Engineer → Senior Data Engineer → Data Engineering Manager / Chief Data Architect

• Machine Learning Engineer → Senior ML Engineer → Head of Machine Learning

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