M.Tech in Data Science

About Course

The Master of Technology (M.Tech) in Data Science at G H Raisoni University (GHRU), Amravati, is an intensive post-graduate journey designed for those who seek to master the art of turning raw, chaotic data into strategic foresight. This isn't a standard analytics course; it is a deep dive into the mathematical scaffolding and algorithmic rigor required to build autonomous systems. The curriculum pushes beyond surface-level visualization, immersing students in high-dimensional statistics, deep learning architectures, reinforcement learning, and the ethics of algorithmic bias. We train our scholars to architect the engines of the modern economy—systems that don't just process information, but learn, adapt, and predict at a global scale.

Objectives of the Program

Mathematical Mastery: Build an uncompromising foundation in multivariable calculus, linear algebra, and Bayesian statistics—the bedrock of all machine learning models.
Predictive Engineering: Develop the expertise to design, train, and deploy sophisticated neural networks and deep learning models tailored for computer vision and natural language processing.
Big Data Orchestration: Provide hands-on command over distributed computing frameworks capable of managing and querying petabyte-scale datasets in real-time.

Algorithmic Innovation: Cultivate the ability to not just use existing libraries, but to innovate, optimize, and write custom algorithms for niche industrial constraints.
Data Governance & Ethics: Instill a rigorous framework for data privacy, ensuring that innovation remains compliant with evolving global regulations and ethical standards.

Study at Raisoni for a successful future & drive your career in the right direction with our M.Tech in Data Science

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Future data science

₹18,00,000/Year*

In the current landscape, specialized Data Scientists and Machine Learning Engineers command the highest entry-level premiums in the tech sector. With an M.Tech, starting packages frequently average ₹18 Lakhs. Senior AI Architects and Lead Data Scientists in specialized sectors like Fintech or Biotech often see compensation packages ranging from ₹35 Lakhs to ₹65 Lakhs.

28% Market Growth

Data is the new electricity. The global demand for advanced analytics is projected to grow at a CAGR of 28% through 2030. As industries move from descriptive to prescriptive analytics, the need for individuals who can build self-learning systems is outpacing the available talent pool.

THE INTELLIGENCE ECONOMY

We are transitioning from a digital economy to an "Intelligence Economy." Organizations are no longer looking for people to build databases; they are looking for architects who can extract competitive advantages from those databases. This shift ensures that M.Tech graduates are the most sought-after assets in the global workforce.

Eligibility

Academic Requirement: Bachelor’s Degree (B.E. / B.Tech) in CS, IT, Statistics, Mathematics, Electronics, or an equivalent quantitative discipline from a recognized institution.
Minimum Marks: At least 50% aggregate (45% for reserved categories).
Selection: Admission is granted based on a valid GATE score or the GHRU Entrance Test, followed by a rigorous technical interview focusing on mathematical aptitude and logical reasoning.
Skillset: Proficiency in Python or R is mandatory, along with a high level of comfort in probability theory and structured query languages (SQL).

Key Details

Applied AI Research Lab: A specialized facility at the Amravati campus where students experiment with generative models, synthetic data creation, and edge computing.
NVIDIA-Powered Computational Cluster: Access to high-end GPU environments and TPU nodes, essential for training large-scale deep learning models and processing complex image datasets.
Data Incubation Wing: A dedicated space for students to transform predictive models into viable business products, supported by mentorship from veteran data scientists and industry consultants.
Live Industry Datasets: Collaboration with corporate partners provides students with access to anonymized, real-world enterprise data for capstone projects, moving beyond "clean" classroom examples.

Admission Procedure

Notification: The University formally announces the postgraduate admission cycle via its official portal.
Application Submission: Candidates must submit a comprehensive application dossier, detailing academic transcripts and relevant technical portfolios or research publications.
Shortlisting: A curated list of candidates is invited for a technical and academic interview to assess research aptitude and computational readiness.
Provisional Admission: Final-year engineering students may apply. If selected, provisional admission is granted with the following stipulations: l marks within one month from the day of admission. Failure to do this will lead to cancellation of your provisional admission.
- Submission of transcripts up to the pre-final semester.
- Provision of the final degree certificate and consolidated mark sheet within one month of the academic commencement.

Application Rejection Scenarios

Applications may be respectfully declined if academic prerequisites are unmet, technical interviews fall below threshold, or documentation is incomplete.

Enrolment: Upon rigorous verification of all credentials and fee remittance, scholars are inducted and assigned a University registration cipher.

Scholars are required to present original documents alongside FOUR sets of attested photocopies upon admission.

Required Documents:

B.E. / B.Tech Degree Certificate & Consolidated Marksheets
Valid GATE Scorecard (if applicable)
10th and 12th (SSC & HSC) Marksheets
Nationality & Domicile Certificate
College Leaving / Transfer Certificate
Valid Government Identification (e.g., Aadhaar - Masked Photocopy)

If Applicable:

Caste / Non-Creamy Layer Certificates
Migration Certificate
Income / Gap Certificates
Published Research Papers or Patents

Core Skills

Deep Learning & Neural Network Architecture
Probabilistic Graphical Models & Advanced Statistics
Big Data Engineering (Spark, Hadoop, NoSQL)
Natural Language Processing (NLP) & Computer Vision
Generative AI & Large Language Models (LLMs)
Data Visualization & Strategic Storytelling
MLOps (Deploying & Monitoring Models at Scale)
Reinforcement Learning & Autonomous Systems
Cloud Data Warehousing (AWS Redshift, Google BigQuery)

Career Opportunities

Depending on prior industry experience and domain expertise, graduates typically align with the following trajectories:

Entry Level

Machine Learning Engineer
Junior Data Scientist
Business Intelligence Developer
Data Analyst (Predictive)

Mid Level

Data Architect
AI Research Scientist
Senior MLOps Engineer
Lead Data Engineer

Senior Level

Chief Data Officer (CDO)
Principal AI Consultant
VP of Analytics
AI Startup Founder

Future Studies Options

There are several postgraduate programs and degrees you can pursue after completing Mtech Data Science , which are as follows:

Ph.D. in Data Science / AI

For scholars aiming to push the boundaries of algorithmic research, deep learning paradigms, or quantum machine learning.

Post-Doctoral Fellowships:

Specializing in niche sectors like Computational Biology, Algorithmic Trading, or Autonomous Robotics.

Advanced Industry Certifications

Earning elite credentials such as the AWS Certified Data Analytics – Specialty, or Google Cloud Professional Machine Learning Engineer.

Top Recruiters

FAQ

How much math is actually involved?

A significant amount. Data Science at the M.Tech level is essentially applied mathematics. If you aren't comfortable with statistics and linear algebra, this program will be challenging. We don't just teach you how to use tools; we teach you how the tools work.

Yes. Real-world data is messy, incomplete, and biased. Our laboratory exercises focus heavily on data cleaning, feature engineering, and handling imbalanced datasets to mirror actual industry conditions.

Absolutely. The elective structure and your final-year capstone project allow you to apply data science frameworks to a specific vertical of your choice.

Yes. Building a model is only half the battle. We place heavy emphasis on MLOps—the process of taking a model out of a notebook and into a production environment where it can serve millions of users.

High. We expect our M.Tech scholars to contribute to the field. Whether it’s improving an existing algorithm or finding a new application for AI, research is a core component of the second year.

Applications of admission are now
open for academic year 2026-2027

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