Can Engineering Graduates Apply for a Master’s in Data Science?

By / September 27, 2026

Can engineering graduates apply for a Master’s in Data Science? Explore the eligibility criteria, quantitative background, programming expectations and pathway structure for the MAS in Data Science Global Pathway. 
 
Engineering graduates often consider Data Science as a way to build careers in analytics, Machine Learning, Artificial Intelligence, and related technical fields. A common question is whether an engineering degree is accepted for a master’s in Data Science. Yes. Engineering is explicitly listed among the bachelor’s backgrounds accepted for edept’s Master of Applied Science in Data Science in partnership with Illinois Tech and Mahindra University. The Global Pathway Program follows a 6+12 structure, with six months of foundational and applied learning in India before 12 months of advanced study at Illinois Tech in Chicago. This blog explains the Data Science master’s eligibility for engineers, the importance of a quantitative background, programming expectations, academic evaluation, and how the Data Science pathway India USA structure works.

Can Engineering Graduates Apply for an MAS in Data Science?

Yes, engineering graduates for master’s in Data Science can apply to edept’s MAS in Data Science Global Pathway Program. Engineering is listed alongside Computer Science, Mathematics, Statistics, and related fields within the accepted bachelor’s backgrounds for the program. However, meeting the broad academic-background requirement does not mean automatic admission. Each application undergoes academic evaluation to assess alignment with Illinois Tech MAS in Data Science prerequisites.

Engineering Is an Eligible Academic Background

An engineering degree can provide the academic starting point for a Data Science master’s after engineering. Applicants are assessed based on their academic record, quantitative preparation, and fit with the program prerequisites. This means an engineering graduate can be eligible, but the final decision depends on the academic evaluation rather than the degree title alone.

Engineering and the Quantitative Foundation of Data Science

The program requires a strong quantitative background because Data Science involves statistics, analytics, Machine Learning, and data-driven problem-solving. Engineering education may include quantitative and technical learning that can support preparation for subjects such as Statistics & Probability for Analytics, Machine Learning, Big Data Analytics, and Data Engineering & High-Performance Computing. Preparation can vary by academic background, so applicants are reviewed individually.

What Engineering Backgrounds Are Suitable for a Master’s in Data Science?

The program lists Engineering as an accepted academic background but does not name individual engineering branches. Therefore, applicants should not assume that a specific branch is officially guaranteed admission. Instead, an applicant’s bachelor’s background is reviewed against the MAS in Data Science eligibility requirements and Illinois Tech prerequisites.

Engineering Graduates With Strong Quantitative Preparation

A strong quantitative background is an explicit requirement. Engineering applicants may benefit from prior exposure to mathematics, statistics, analytical problem-solving, or other quantitative subjects. This preparation can support the transition into a curriculum that includes statistics, analytics, Machine Learning, and data-focused project work.

Engineering Graduates With Technical or Computing Exposure

Programming exposure can also be useful for engineering to Data Science transitions. The program notes that exposure to Python, C++, or Java is preferred. However, prior programming exposure is not required. Applicants without formal coding experience should still be assessed through the academic evaluation process.

Do Engineering Graduates Need a Background in Computer Science?

No. A Computer Science bachelor’s degree is not stated as the only route into the program. Engineering is explicitly included among the accepted bachelor’s backgrounds for the MAS Data Science for engineering graduates. A strong quantitative background remains important, while prior exposure to Python, C++, or Java is preferred but not mandatory.

Engineering vs. Computer Science Background

Engineering and Computer Science are both accepted backgrounds for the MAS in Data Science, and both require strong quantitative preparation. The main difference lies in how closely each background may already align with programming, analytics, and Data Science fundamentals.  
Background Mentioned in brochure? Key consideration
Engineering Yes Strong quantitative background
Computer Science Yes Strong quantitative background
Mathematics Yes Strong quantitative background
Statistics Yes Strong quantitative background
Related fields Yes Subject to academic evaluation
The program does not state that one of these academic backgrounds is preferred over another. Final eligibility is determined through evaluation against the Illinois Tech MAS in Data Science prerequisites.
Engineering Application Document Hierarchy
Engineering Application Document Hierarchy
 

 

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What Skills Should Engineering Graduates Have Before Applying?

Applicants should focus on the program’s stated criteria and the academic demands of the curriculum, rather than assuming that an engineering degree alone meets every requirement.

Quantitative Skills

A strong quantitative background is explicitly required for this Data Science master’s in USA pathway. This matters because the curriculum covers statistics, analytics, Machine Learning, and data-intensive study.

Programming Exposure

Exposure to Python, C++, or Java is preferred but not required. Engineering graduates do not need to have a programming certification before applying. Prior coding familiarity may be helpful, but the formal academic review remains the key eligibility stage.

Analytical Readiness

Engineering courses often involve structured problem-solving and analytical thinking. These skills can support preparation for Data Science study, although applicants still need to demonstrate academic readiness for the program.

Is Programming Required for Engineering Graduates?

No. Prior programming exposure is preferred, not required, for applicants to edept’s Master of Applied Science in Data Science. The program specifically refers to Python, C++, and Java as useful forms of prior exposure. This can reassure engineering graduates who have limited coding experience but meet the wider academic and quantitative expectations.

Why Programming Exposure Is Still Useful

The India Track includes Programming for Data Science using Python. Programming becomes part of the structured curriculum, even though prior experience is not mandatory. This allows students to build relevant programming foundations before progressing to advanced Data Science coursework.

What If You Have Never Used Python?

The admission criteria do not make prior Python experience mandatory. However, applicants should not assume admission is guaranteed without programming exposure. Academic evaluation against Illinois Tech prerequisites remains the determining stage.

What Will Engineering Graduates Study in the MAS in Data Science?

The Data Science pathway India USA structure is designed to build subject knowledge progressively. Students begin with foundational and applied study in India before moving to advanced master’s coursework in Chicago.

Foundation During the India Track

The India Track at Mahindra University includes:
  • Programming for Data Science using Python
  • Statistics & Probability for Analytics
  • Data Management & SQL
  • Data Visualisation & Business
  • Introduction to Machine Learning
  • Cloud & Data Infrastructure Fundamentals
  • Applied Projects & Assessments
These subjects establish foundations for students preparing to study Data Science in USA.

Advanced Study at Illinois Tech

The Illinois Tech phase includes advanced coursework in:
  • Advanced Machine Learning
  • Artificial Intelligence Foundations
  • Big Data Analytics
  • Data Engineering & High-Performance Computing
  • Data Strategy & Governance
  • Capstone Project or Master’s Thesis
  • Industry-Oriented Project Work
The program’s curriculum covers programming, statistics, data management, visualisation, Machine Learning, cloud infrastructure, AI, Big Data, data engineering, and strategy across the India and USA tracks.

How the Curriculum Builds on Existing Engineering Knowledge

Engineering graduates may already have technical or quantitative academic experience. The program adds dedicated Data Science knowledge, tools, and applications through structured coursework and projects. It does not automatically convert an engineering graduate into a Data Scientist. Instead, it can prepare students with relevant academic foundations for Data Science-related work.

How Does the 6+12 Pathway Work for Engineering Graduates?

The Global Pathway Program includes six months at Mahindra University in India and 12 months at Illinois Tech in Chicago. Students build foundational knowledge before entering the advanced U.S. phase. The program states that India-earned credits align with the U.S. curriculum, supporting academic continuity across both tracks.

Six Months of Foundational Learning in India

The India phase focuses on building fundamentals through coursework, academic monitoring, mentoring, applied projects, and assessments. For engineering graduates study Data Science in USA preparation, this phase creates a structured bridge between prior academic experience and advanced master’s-level learning.

Twelve Months of Advanced Learning in Chicago

The USA phase takes place at Illinois Tech in Chicago and includes advanced MAS coursework, projects, and capstone or thesis work. Students complete the full program with a PGP certificate from Mahindra University and a STEM Master of Applied Science in Data Science from Illinois Tech, subject to meeting the relevant requirements.

How Is an Engineering Graduate’s Eligibility Evaluated?

Broad eligibility does not mean automatic admission. The program uses a joint academic evaluation to assess an applicant’s alignment with Illinois Tech’s MAS Data Science prerequisites.

Academic Review

The review considers the bachelor’s background, quantitative preparation, and alignment with academic prerequisites. This process helps determine whether an engineering applicant is academically prepared for the program.

Bridging Courses, If Required

Bridging courses may be assigned where required following academic evaluation. The specific subjects and duration depend on the applicant’s academic background and assessment outcome.

Conditional Offer

Eligible students may receive a conditional offer. This confirms admission to the India phase while setting out requirements for progression and U.S. transfer.  
Build global-ready skills with edept’s Master’s in Data Science program
Begin Your Journey!
 

What Career Paths Can an Engineering Graduate Explore After an MAS in Data Science?

The program can prepare students for Data Science, Machine Learning, data engineering, analytics, and business-focused data roles. Career outcomes depend on academic performance, technical skill development, work experience, and job-market conditions.

Data Science and Machine Learning Roles

Potential roles include:
  • Data Scientist
  • Machine Learning Engineer
These roles connect with the program’s Machine Learning and Artificial Intelligence components.

Data Engineering and Analytics Roles

Potential roles include:
  • Data Engineer
  • Senior Data Analyst
These roles connect with Data Engineering, Big Data, statistics, analytics, and data-management learning.

Business and Product Analytics Roles

Potential roles include:
  • Product & Growth Analyst
  • Business Analytics Manager
These roles connect with Data Visualisation & Business and Data Strategy & Governance.

Is a Master’s in Data Science a Good Next Step After Engineering?

A master’s in Data Science may align with the goals of engineering graduates who are interested in analytics, Machine Learning, AI, Big Data, Data Engineering, or data-driven business roles.

When Data Science May Align With Your Goals

Consider this pathway if you are interested in understanding data, building analytical models, working with Machine Learning systems, or applying technical skills to business and operational decisions.

What to Consider Before Applying

Before applying, assess:
  • Quantitative readiness
  • Academic prerequisites
  • Programming exposure
  • Interest in advanced Data Science
  • Cost and duration
  • The 6+12 study structure
This helps you decide whether the program fits your academic preparation and longer-term goals.

Engineering Graduate to MAS in Data Science: Eligibility at a Glance

The following overview brings together the key academic and pathway-related eligibility points for engineering graduates considering edept’s Master of Applied Science in Data Science in partnership with Illinois Tech and Mahindra University.  
Eligibility factor What the brochure says
Bachelor’s degree Engineering is accepted
Quantitative background Strong quantitative background
Programming Python, C++, or Java exposure preferred, not required
Academic evaluation Alignment with Illinois Tech MAS prerequisites
Bridging courses May be assigned if required
Pathway 6 months in India + 12 months in Chicago

Frequently Asked Questions

Can engineering graduates apply for a Master’s in Data Science?

Yes. Engineering is listed among the accepted bachelor’s backgrounds for edept’s Master of Applied Science in Data Science. Applicants are still assessed against program prerequisites.

Can engineers study Data Science in the USA?

Yes. Engineering graduates can apply for the Data Science master’s in USA pathway, which includes study in India followed by advanced study at Illinois Tech in Chicago.

Is an engineering degree accepted for the MAS in Data Science?

Yes. Engineering is explicitly listed as an accepted bachelor’s background, alongside Computer Science, Mathematics, Statistics, and related fields.

Do engineering graduates need a Computer Science background?

No. Computer Science is not the only accepted background. Engineering is also listed, subject to academic evaluation and quantitative preparation.

Is programming knowledge required for the MAS in Data Science?

No. Programming exposure is preferred but not required. The program identifies Python, C++, and Java as useful prior exposure.

Do I need to know Python before applying?

No. Prior Python experience is not mandatory. The India Track includes Programming for Data Science using Python, although final eligibility depends on academic evaluation.

What if my engineering background is not in Computer Science?

The program does not limit eligibility to Computer Science engineering. Engineering applicants are evaluated individually against the Illinois Tech MAS prerequisites.

Do engineering graduates need strong mathematics skills?

A strong quantitative background is required. This supports readiness for statistics, analytics, Machine Learning, and other Data Science subjects.

Can I be asked to take bridging courses?

Yes. Bridging courses may be assigned if required after academic evaluation.

Where will I study during the 6+12 Global Pathway?

Students study for six months at Mahindra University in India and 12 months at Illinois Tech in Chicago.

Take the Next Step From Engineering to Data Science

Engineering graduates are explicitly included among the bachelor’s backgrounds eligible to apply for edept’s Master of Applied Science in Data Science. A strong quantitative background is important, while programming exposure is helpful but not mandatory. Applicants are assessed against Illinois Tech’s MAS Data Science prerequisites. The 6+12 Global Pathway Program provides foundational study at Mahindra University before advanced MAS study at Illinois Tech in Chicago. Explore edept’s Master of Applied Science in Data Science Global Pathway Program and assess your academic fit with edept and Mahindra University.  

 

Build global-ready skills with edept’s Master’s in Data Science program
Begin Your Journey!

 

Frequently Asked Questions

Yes. Engineering is listed among the accepted bachelor’s backgrounds for edept’s Master of Applied Science in Data Science. Applicants are still assessed against program prerequisites.

Yes. Engineering graduates can apply for the Data Science master’s in USA pathway, which includes study in India followed by advanced study at Illinois Tech in Chicago.

Yes. Engineering is explicitly listed as an accepted bachelor’s background, alongside Computer Science, Mathematics, Statistics, and related fields.

No. Computer Science is not the only accepted background. Engineering is also listed, subject to academic evaluation and quantitative preparation.

No. Programming exposure is preferred but not required. The program identifies Python, C++, and Java as useful prior exposure.

No. Prior Python experience is not mandatory. The India Track includes Programming for Data Science using Python, although final eligibility depends on academic evaluation.

The program does not limit eligibility to Computer Science engineering. Engineering applicants are evaluated individually against the Illinois Tech MAS prerequisites.

A strong quantitative background is required. This supports readiness for statistics, analytics, Machine Learning, and other Data Science subjects.

Yes. Bridging courses may be assigned if required after academic evaluation.

Students study for six months at Mahindra University in India and 12 months at Illinois Tech in Chicago.

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