NJIT MS in Data Science Eligibility Requirements

The admission requirements for the NJIT MS in Data Science :

Requirements Details
Bachelor's Degree Background in mathematics, computer science, or a related field is preferred, highlighting the program's focus on data science
Academic Performance Strong academic performance with a competitive grade point average (GPA) that meets the program's minimum requirements.
Prerequisite Courses Having prior coursework in mathematics, statistics, or programming can provide an advantageous starting point.
Standardized Tests NJIT MS in Data Science does not explicitly require applicants to submit standardized test scores such as the GRE or GMAT
English Proficiency Non-native English speakers applying to the New Jersey Institute of technology ms in data science need to demonstrate their English language proficiency.
Letter of Recommendation The application typically requires two to three letters of recommendation from professors, employers, or professionals familiar with the applicant's qualifications.
Statement of Purpose Applicants must submit a well-crafted statement of purpose that outlines their motivation, showcases their relevant experiences, and articulates their career aspirations within the field of data science. 

 

3/4

Bachelor's GPA Requirement

4 years Engineering degree

UG Requirement

7

Maximum Backlogs Accepted

min 0 years (no max limit)

Work Experience Required

Test Scores Requirement

ExamRequirementMinimum Section Scores
-
305-
6.5reading: 6 | writing: 6 | speaking: 6 | listening: 6
79-
120-

Program Eligibility URL:https://catalog.njit.edu/graduate/admissions-financial-support/admissions/

About New Jersey Institute of Technology

New Jersey Institute of Technology (NJIT) is an esteemed public research university located in Newark, New Jersey, USA. With a rich history dating back to its establishment in 1881, NJIT MS in Data Science has earned a stellar reputation for providing high-quality education and conducting ground breaking research across various disciplines.

At NJIT, students have access to a diverse range of undergraduate and graduate programs encompassing fields such as engineering, computer science, architecture, business, science, and healthcare. The university is renowned for its rigorous curriculum, experiential learning opportunities, and integration of cutting-edge technologies. Whether you're passionate about designing innovative structures, exploring the depths of data science, or leading advancements in healthcare, NJIT MS in Data Science suits your interests and prepares you for a successful career in your chosen field.

As a leading research institution, NJIT is dedicated to pushing the boundaries of knowledge and driving innovation. The university houses several prestigious research centers and institutes, specializing in areas like cybersecurity, sustainable systems, healthcare technologies, materials science, data science, and urban planning. Through these centers, NJIT's faculty and students actively engage in ground breaking research projects, contributing to advancements that shape our future. By studying at NJIT, you'll have the opportunity to collaborate with experts, work on cutting-edge projects, and make significant contributions to your field of study, such as in the field of data science through the renowned new jersey institute of technology ms in data science program.

NJIT's sprawling campus spans over 45 acres and is equipped with state-of-the-art facilities and modern laboratories. This vibrant learning environment provides an optimal setting for academic growth and research exploration. From well-equipped academic buildings and research centers to comfortable student residences, libraries filled with vast knowledge resources, and sports facilities that encourage a healthy lifestyle, NJIT's campus offers everything you need to thrive both academically and socially.

NJIT MS in Data Science Program

Data scientists with computational abilities are in high demand in today's AI-driven economy because they can create, construct, and use models and tools for data-driven decision-making. Businesses employ data science and AI to make marketing judgments, promote products to specific customers, identify profitable insurance coverage, and offer individualized financial advice.

A high-performing data scientist needs to be proficient in both fundamental and advanced techniques in statistical inference, machine learning, data visualization, data mining, and big data. These topics are all covered in the NJIT MS in Data Science. We demand a fundamental understanding of mathematics (calculus, linear algebra), statistics (probability and basic stats), and software development to admit students to the program (programming, data structures, and algorithms).


Program URL:https://catalog.njit.edu/graduate/computing-sciences/computer-science/data-science-ms/

Curriculum of NJIT MS in Data Science Program

When pursuing the NJIT MS in Data Science then students have the opportunity to select elective courses that align with their specific interests and career goals. Electives play a crucial role in enhancing students' knowledge and skills in specialized areas of data science. 

  • Data Structures and Algorithms  
  • Data Management System Design             
  • Advanced Database System Design           
  • Data Mining        
  • Data Analytics with R Program (only available to students in the Mathcore)             
  • Elec. Medical Records: Med Terminologies and Comp. Imp.            
  • Cloud Computing              
  • Security and Privacy in Computer Systems             
  • Internet and Higher-Layer Protocols         
  • Image Processing and Analysis    
  • Systems Simulation          
  • Artificial Intelligence        
  • Cognitive Computing       
  • Software Project Management   
  • Software Testing and Quality Assurance  
  • Computer Vision               
  • Advanced-Data Security and Privacy         
  • Applications of Database Systems              
  • Advanced Machine Learning        
  • High-Performance Analytics Dat 
  • Data Mining and Management in Bioinformatics 
  • Pattern Recognition and Applications       
  • Graduate Capstone Project (Counting towards the elective credits requires the program director’s prior approval.

In addition, it needs to be completed with an external partner (industry, lab, or government), or with a faculty only if the same faculty is not the student’s MS project or MS thesis advisor.)                              

Other Electives for new jersey institute of technology ms in data science :

  • Computational Ecology  
  • Selected Topics  
  • Data Mining and Analysis              
  • Decision Analysis              
  • Corporate Finance I                         
  • Derivatives Markets         
  • Derivatives and Structured Finance

Electives

When pursuing the NJIT MS in Data Science then students have the opportunity to select elective courses that align with their specific interests and career goals. Electives play a crucial role in enhancing students' knowledge and skills in specialized areas of data science. 

  • Data Structures and Algorithms  
  • Data Management System Design             
  • Advanced Database System Design           
  • Data Mining        
  • Data Analytics with R Program (only available to students in the Mathcore)             
  • Elec. Medical Records: Med Terminologies and Comp. Imp.            
  • Cloud Computing              
  • Security and Privacy in Computer Systems             
  • Internet and Higher-Layer Protocols         
  • Image Processing and Analysis    
  • Systems Simulation          
  • Artificial Intelligence        
  • Cognitive Computing       
  • Software Project Management   
  • Software Testing and Quality Assurance  
  • Computer Vision               
  • Advanced-Data Security and Privacy         
  • Applications of Database Systems              
  • Advanced Machine Learning        
  • High-Performance Analytics Dat 
  • Data Mining and Management in Bioinformatics 
  • Pattern Recognition and Applications       
  • Graduate Capstone Project (Counting towards the elective credits requires the program director’s prior approval.

In addition, it needs to be completed with an external partner (industry, lab, or government), or with a faculty only if the same faculty is not the student’s MS project or MS thesis advisor.)                              

Other Electives for new jersey institute of technology ms in data science :

  • Computational Ecology  
  • Selected Topics  
  • Data Mining and Analysis              
  • Decision Analysis              
  • Corporate Finance I                         
  • Derivatives Markets         
  • Derivatives and Structured Finance

Students are required to take (4) core courses from the following list:

  • Machine Learning (DS 675)
  • Introduction to Big Data (DS 644)
  • Data Analytics with R Program (DS 636)
  • Deep Learning (DS 677)
  • Applied Statistics (MATH 661)

The university offers opportunities for students to specialize for new jersey institute of technology ms in data science Specialization options may include cybersecurity analytics, financial data analysis, healthcare analytics, or social media analytics. These specializations allow students to tailor their education to match their career aspirations and deepen their expertise in a particular domain.

  • Machine Learning and Artificial Intelligence
  • Big Data Analytics
  • Business Analytics
  • Computational Biology and Bioinformatics
  • Data Engineering
  • Cybersecurity Analytics

New Jersey Institute of Technology clubs and associations are more than just extracurricular activities; they are vital components of the NJIT experience, fostering innovation, teamwork, leadership, and personal growth.

Data Science Club The NJIT Analytics Club is your gateway to the world of analytics. In an era where data-driven decision-making is paramount, this club focuses on exploring and applying analytics techniques across various industries and domains.
Analytics Club Artificial intelligence, machine learning, and deep learning are revolutionizing technology and shaping the future. If you're passionate about these cutting-edge fields, NJIT's AI and Machine Learning Club is the perfect place for you. 
AI and Machine Learning Club Artificial intelligence, machine learning, and deep learning are revolutionizing technology and shaping the future. If you're passionate about these cutting-edge fields, NJIT's AI and Machine Learning Club is the perfect place for you. 
Women in Data Science (WiDS) A Diversity and inclusion are at the heart of innovation, and the Women in Data Science (WiDS) club at NJIT is committed to promoting these values within the data science community. While the field of data science has traditionally been male-dominated, WiDS empowers women to excel.
Coding and Programming Clubs In the realm of data science, coding and programming skills are essential. NJIT offers several coding and programming clubs that cater to different languages and technologies

 

The new jersey institute of technology ms in data science offers a variety of extra activities to enrich the learning experience and provide students with valuable opportunities for growth and engagement. Here are some of the extra activities available to students in the program:

  • Industry Speaker Series: NJIT invites industry professionals and experts in the field of data science to deliver talks and share their insights. These speaker series provide students with valuable industry perspectives, current trends, and real-world applications of data science. 
  • Hackathons and Data Competitions: NJIT actively participates in hackathons and data competitions, both on-campus and off-campus. These events allow students to work on real-world data problems, collaborate with peers, and apply their data science skills in a competitive environment. 
  • Research Opportunities: NJIT encourages students to engage in research projects related to data science. Through collaborations with faculty members and research centers, students can contribute to cutting-edge research and gain hands-on experience in advanced data science methodologies. 
  • Professional Development Workshops: NJIT provides professional development workshops tailored to the needs of data science students. These workshops cover topics such as resume building, interview skills, job search strategies, and networking. 
  • Data Science Conferences and Events: NJIT encourages students to attend data science conferences, seminars, and symposiums. These events offer opportunities to learn from leading researchers and practitioners, stay updated with the latest advancements in data science, and network with professionals in the field. 

Acceptance Rate of NJIT MS in Data Science

While specific acceptance rates may vary from year to year, NJIT maintains high academic standards, admitting motivated and talented individuals who demonstrate a strong aptitude for the new jersey institute of technology ms in data science.

Acceptance rate of 66%

NJIT MS in Data Science Fee Structure

The graduate cost of attendance for the 2023-2024 academic year, considering two semesters of full-time enrollment, encompasses tuition fees, accommodation, books and supplies, personal expenses this comprehensive estimate is crucial for prospective students to plan their finances effectively, ensuring they are prepared for the monetary commitment required for their advanced studies abroad.

Expenses Amount
Tuition Fee $35,262
living on campus $15,000
Books & Supplies $1,700

For students opting to reside on campus, regardless of being New Jersey residents or not, the estimated room and board cost stands at $15,000. Additionally, they should anticipate indirect costs amounting to $4,664. For those preferring off-campus living, the expected room and board expenses increase to $17,200, with indirect costs also rising to $6,764.

Moreover, it's important for students to account for their academic materials. Specifically, first-time freshmen and transfer students enrolled in non-architecture programs are estimated to incur a cost of $2,100 for books and supplies, a figure that applies to those in architecture programs as well. This information aims to aid students in preparing financially for their upcoming academic year.

Application Documents for New Jersey Institute of Technology MS in Data Science

Mandatory Application Documents

  • Passport

  • 10th Marksheet

  • 12th Marksheet

  • College Transcript

  • Semester Marksheets

  • Consolidated Marksheets

  • Graduation/Provisional Certificate

  • Backlog/No Backlog Certificate

  • IELTS/TOEFL/DTE/PTE

  • GRE

  • WES Evaluation

    Masters in data science Deadlines

    NJIT MS in Data Science Admission Process

    NJIT MS in Data Science Dates & Deadlines operates on a rolling admissions basis, meaning your application will be reviewed as soon as it is fully submitted. You have set the following deadlines for application submissions for the upcoming enrollment periods:

    APPLICATION TYPE FALL SPRING
    Master's - International May 1 November 15

    The admission process at the New Jersey Institute of Technology (NJIT) generally involves several steps. Here is an overview of the typical admission process for undergraduate programs at NJIT:

    Application Submission

    Begin by completing the online application form provided by NJIT. This form will require you to provide personal information, academic history, extracurricular activities, and other relevant details. Make sure to submit the application before the specified deadline.

    Application Fee

    Pay the required application fee as indicated by NJIT. The fee is typically non-refundable and covers the administrative costs of processing your application. Follow the instructions provided for payment and provide proof of payment, if required.

    Transcripts

    Request official transcripts from your high school and any other educational institutions you have attended. These transcripts should include your grades, courses taken, and any degrees or diplomas earned. NJIT may have specific instructions on how to submit official transcripts.

    Standardized Test Scores

    Submit your standardized test scores, such as the SAT or ACT, directly to NJIT. Check NJIT's admissions website for specific requirements and minimum score expectations. Some programs may have additional test requirements, so be sure to review the program's specific guidelines.

    Letters of Recommendation (LORs)

    Some programs at NJIT may require letters of recommendation. These letters typically come from teachers, counselors, or other individuals who can speak to your academic abilities, character, and potential for success. Follow the instructions provided by NJIT for submitting these letters.

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    Career Opportunities at New Jersey Institute of Technology MS in CS

    94,997

    Average Starting Salary

    Companies Recruiting NJIT MS in Data Science Graduates

    Technology Finance Consulting
    Google JPMorgan Chase McKinsey
    Microsoft Goldman Sachs Deloitte
    Amazon BlackRock Accenture

     


    Success Stories of NJIT MS in Data Science

    The new jersey institute of technology equips students with the knowledge and skills necessary to excel in the field of data science. Graduates of this program have gone on to achieve remarkable success in their careers, making significant contributions to the industry. In this article, we will explore the accomplishments and experiences of NJIT MS in Data Science alumni.

    Michael Noll Michael Noll is an American engineer, and professor emeritus at the Annenberg School at the University of Southern California
    John Pelesko Pelesko is an American mathematician. He is currently a Professor of the Department of Mathematical Sciences and Dean of the College of Arts and Sciences at the University of Delaware.
    Funsho Williams Anthony Olufunsho Williams was an influential politician from Lagos State and former Commissioner under Colonel Olagunsoye Oyinlola's Military Administration in Lagos.
    Gerard J. Foschini Gerard Joseph Foschini, is an American telecommunications engineer who has worked for Bell Laboratories since 1961

    These alumni exemplify the diverse range of career paths available to NJIT in Data Science Graduates. Their accomplishments highlight the program's ability to nurture talented individuals who have gone on to thrive in various positions and industries.

    Letter of Recommendation for NJIT MS in Data Science

    A letter of recommendation is a document written by a person who knows you well academically, professionally, or personally and can vouch for your abilities, achievements, and character. It is often required as part of the application process for academic programs or job opportunities. For admission into the new jersey institute of technology ms in data science program, letters of recommendation play a crucial role in assessing an applicant's suitability for the program.

    Letters of Recommendation: 

    • Objective Assessment: Letters of recommendation provide an external and unbiased evaluation of your capabilities and potential as a data science student. They offer insights that go beyond what you might have mentioned in your application.
    • Academic and Professional Validation: A strong recommendation from a professor, supervisor, or mentor can validate your academic and professional achievements in the field of data science.
    • Character Assessment: Admissions committees look for individuals who will contribute positively to the academic community. Letters of recommendation can shed light on your work ethic, teamwork skills, and other personal qualities.
    • Evidence of Fit with the Program: A well-written letter can highlight how your skills, interests, and aspirations align with the objectives and offerings of the NJIT MS in Data Science program.
    • Enhancement of Application Package: A positive letter of recommendation can strengthen your overall application and set you apart from other candidates with similar academic backgrounds.

    Tips for Getting a Good Letter of Recommendation:

    • Choose the Right Recommender: Select individuals who know you well and can speak positively about your abilities and character. This may include professors, supervisors, or mentors in data science-related fields.
    • Ask Early and Politely: Request a letter of recommendation well in advance of the application deadline, and ask politely, respecting the recommender's time and commitments.
    • Provide Relevant Information: Provide your recommender with relevant details about the program and your achievements in data science. Include your resume, academic transcript, and any relevant projects you have worked on.
    • Remind Your Recommender: A gentle reminder closer to the deadline can be helpful, but avoid being pushy or demanding.
    • Discuss Your Goals: Speak with your recommender about your career aspirations and why you are interested in the NJIT MS in Data Science program. This will help them tailor the letter to align with your goals.
    • Be Thankful: After the letter has been submitted, express your gratitude to your recommender for taking the time to support your application.

    Remember that strong letters of recommendation can significantly enhance your application. Choose recommenders who can provide valuable insights into your abilities, and be proactive in facilitating the process while being respectful of their time.

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    Statement of Purpose for NJIT MS in Data Science

    A Statement of Purpose (SOP) is a crucial component of the application process for various academic programs, including MS (Master of Science) programs. It is a written essay where applicants describe their academic background, professional experiences, career goals, and reasons for applying to a specific program or institution. The SOP provides an opportunity for applicants to showcase their motivations, aspirations, and their fit with the chosen program.

    Importance of the SOP

    • Personal Insight:

      The SOP allows the applicant to provide a personal touch to their application. It helps the admissions committee to understand the applicant's personality, passion for the field, and their potential as a future student.
    • Academic and Professional Background:

      Applicants can use the SOP to highlight their academic achievements, relevant coursework, and any research or projects related to data science. They can also discuss their work experience in the field, if applicable, to demonstrate their preparedness for the program.
    • Alignment with Program:

      The SOP gives applicants the chance to explain why they are specifically interested in NJIT's MS in Data Science program. They can mention unique aspects of the program, such as specific courses, faculty expertise, or research opportunities that align with their career goals.
    • Career Goals:

      The SOP allows applicants to articulate their short-term and long-term career goals in the field of data science. Admissions committees look for candidates whose aspirations align with what the program can offer.
    • Communication and Writing Skills:

      The quality of the SOP reflects an applicant's ability to communicate effectively and showcase their writing skills. A well-written and articulate SOP can leave a positive impression on the admissions committee.
    • Demonstrates Seriousness:

      Writing a strong SOP indicates that the applicant is serious about their application and has taken the time to research the program and put thought into their reasons for applying.

    Statement of Purpose is a critical part of the application process for the new jersey institute of technology ms in data science. It allows applicants to present their motivations, qualifications, and career aspirations, helping the admissions committee make informed decisions about who would be the best fit for the program. 

    Tips to write a compelling Statement of Purpose

    Here are some tips to help you craft a strong SOP:

    https://mentr-me-prod.s3.ap-south-1.amazonaws.com/uploads/images/65004f5fe34241694519135.jpg

    • Start with a Strong Introduction:

      Begin your SOP with an engaging and attention-grabbing introduction. You can start with a personal anecdote, a relevant quote, or a brief overview of your passion for data science.
    • Explain Your Motivation:

      Clearly state your motivations for pursuing a Master's in Data Science at NJIT. Explain what sparked your interest in this field, and how your past experiences have led you to choose this program.
    • Highlight Relevant Academic and Professional Background:

      Showcase your academic achievements and any relevant coursework or projects related to data science. If you have prior work experience in the field, emphasize how it has prepared you for advanced studies in data science.
    • Emphasize Fit with NJIT:

      Research NJIT's Data Science program thoroughly and mention specific reasons why it aligns with your career goals and academic interests. Highlight unique courses, faculty members, research opportunities, or facilities that attract you to the program.
    • Discuss Your Career Goals:

      Clearly outline your short-term and long-term career goals in the field of data science. Explain how obtaining an MS from NJIT will help you achieve these goals and contribute to your chosen field.

    It is essential for applicants to craft a well-written, thoughtful, and persuasive SOP to increase their chances of admission to their desired program.

     

    Scholarships for International Students: Master's in Data Science at NJIT

    • NJIT Graduate Scholarships
    • Graduate Teaching Assistantships (GTAs)
    • Graduate Research Assistantships (GRAs)
    • External Scholarships and Grants

    Unique Aspects of NJIT MS in Data Science Program

    Look no further than the New Jersey Institute of technology ms in data science. With its unique combination of interdisciplinary education, industry relevance, and experiential learning, NJIT's program stands out as a top choice for aspiring data scientists. Let's explore what sets the M.S. in Data Science at NJIT apart from the rest.

    The NJIT MS in Data Science offers a distinctive approach to data education, providing students with a comprehensive understanding of the field and preparing them for successful careers. Here are the key elements that make NJIT's program unique:

    • Interdisciplinary Approach: The NJIT MS in Data Science takes an interdisciplinary approach, blending concepts from computer science, mathematics, statistics, and other relevant disciplines. This comprehensive approach ensures that students develop a well-rounded skill set, enabling them to tackle complex data problems from multiple angles.
    • Industry-Relevant Curriculum: The program's curriculum is carefully crafted to align with the latest industry trends and demands. Students delve into a wide range of topics, including data mining, machine learning, statistical analysis, big data analytics, and data visualization. By gaining expertise in these cutting-edge areas, NJIT graduates are well-prepared to meet the evolving needs of the data-driven job market.
    • Experiential Learning Opportunities: New Jersey Institute of technology emphasizes practical application and hands-on experience. Students have the opportunity to engage in real-world projects, internships, and research collaborations with industry partners. These experiences allow students to apply their knowledge in practical settings, develop essential problem-solving skills, and establish valuable connections within the industry.
    • Distinguished Faculty and Research Centers: At NJIT, students learn from a distinguished faculty comprising accomplished researchers and experts in the field of data science. Their guidance and mentorship contribute to a rich learning experience. Moreover, NJIT hosts research centers and institutes focused on data-driven research, providing students with additional resources and opportunities for innovation and collaboration.
    • Industry Partnerships and Top Recruiters: NJIT has cultivated strong relationships with leading companies and organizations that actively recruit data science graduates. Collaborating with industry partners allows NJIT to stay at the forefront of industry needs and ensure program relevance. Graduates benefit from excellent career opportunities and internships with top recruiters across various sectors.
    • Specializations and Electives: The NJIT MS in data science offers specializations in areas such as cybersecurity analytics, financial data analysis, healthcare analytics, and social media analytics. These specializations allow students to tailor their education to match their specific career interests and goals. Additionally, a wide range of elective courses allows students to explore niche areas of data science and further deepen their expertise.

    Key Qualities of NJIT MS in Data Science looks for in Candidates?

    The New Jersey Institute of Technology (NJIT) values various qualities and characteristics in applicants. While the specific criteria may vary across programs, here are some key aspects that NJIT tends to value:

    • Academic Excellence:

      NJIT highly values applicants who have demonstrated strong academic performance in their previous studies. This includes a solid foundation in relevant subjects, such as mathematics, computer science, statistics, and engineering. Good grades, a challenging course load, and academic honors can be advantageous.
    • Relevant Background and Preparation:

      NJIT looks for applicants who have a background or prior coursework in areas related to their chosen field of study. For example, in the MS in Data Science program, a background in mathematics, computer science, statistics, or a related field would be beneficial. Showing a strong foundation and preparation in the field of study demonstrates readiness for advanced coursework.
    • Research and Practical Experience:

      NJIT values applicants who have engaged in research, practical projects, or internships related to their field. Demonstrating hands-on experience and an understanding of real-world applications can be advantageous. Highlighting any research publications, presentations, or relevant work experience will strengthen your application.
    • Passion and Motivation:

      NJIT appreciates applicants who display genuine passion and motivation for their chosen field of study. Clearly expressing your enthusiasm, future goals, and how NJIT's program aligns with your aspirations will demonstrate your commitment and dedication.
    • Problem-Solving and Analytical Skills:

      NJIT seeks applicants who possess strong problem-solving and analytical skills. This is particularly relevant for fields such as engineering, computer science, and data science. Showcasing your ability to analyze complex problems, think critically, and propose innovative solutions will be beneficial.

    Contact NJIT MS Data Science

    Whom should I contact in case of any doubts?

    Contact for new jersey institute of technology ms in data science -

    Admissions
    Stephen M. Eck, Executive Director, University Admissions
    973-596-3300 / 973-596-3461 (fax)
    stephen.eck@njit.edu

    Mailing Address
    New Jersey Institute of Technology
    University Heights 
    Newark, New Jersey 07102

    Main phone
    (973) 596-3000

    Useful Links

    Conclusion: Is the MS in Data Science at New Jersey Institute of Technology Right for You?

    If you are passionate about data science and seeking a comprehensive and reputable program, applying to the new jersey institute of technology ms in data science can be a valuable step towards advancing your career in this field. NJIT's program offers a rigorous curriculum, state-of-the-art resources, and a supportive learning environment.

    By pursuing in the new jersey institute of technology ms in data science, you will have the opportunity to learn from experienced faculty members who are experts in the field. The program covers a wide range of topics, including data analysis, machine learning, data visualization, and big data management, ensuring you develop a well-rounded skill set.

    Ask a Question

    Have Queries about New Jersey Institute of Technology?

    Get Answers from Alums

    I want to become a data scientist...what should I choose in my masters...CS or data science?Or Can I do my masters in CS and become a data scientist ?I'm a CS major !?

    Data Science is an important aspect of many industries because it helps people understand big data and how it can be used effectively in businesses or organisations with the scope of communication and programming. Data science works with structured and unstructured data, which subject matter experts sort to form a product or explanatory analysis. Data Science has advanced technology and made it easier to connect and communicate. Masters in Data Science Course Eligibility:

    English Proficiency Test: IELTS or PTE or TOEFL
    Entrance Exam: GRE and GMAT (depends on the specific university)
    Bachelor’s degree from a relevant university
    Resume/CV
    Letter of Recommendation
    Over 90% of individuals working in this field pursue an MS in Data Science abroad because the career requires an explicit understanding of the methods, modules, and processes. The Masters of Data Science programme is popular among Indian students due to the broad scope of learning, growth, and career opportunities. The most common university programme is the MSc Data Science or MS Data Science. If you have any further questions just ask me.

     

    What is the meaning of data science and how is it different from data analytics?

    There are a lot of things that are often considered as same when they are not, such as MiM and MBA, Stock Market and gambling and many more. One of those things is data science and data analytics. Many students still consider these as the same thing and often say that they are going to become a data analyst when they are actually pursuing a data scientist course. 

    In order for you to not do these kinds of blunders, I have mentioned some key differences between a data analyst and a data scientist. So let’s get started with them: 

    In data science, you apply various algorithms, processes., and scientific methods from structured and unstructured data to derive meaningful insights from them. But in data analytics, you process raw data to arrive at the conclusions. 
    Data science is a much more broad scope with many branches and fields. Data analytics has a much narrower scope and is a subset of data analytics. 
    The knowledge and skills needed in data science are much more in-depth than in data analytics.
    Machine learning is used in data science and sometimes it is an essential part of various data science tasks. But data analytics has no relation to machine learning. 
    Some major fields where data science is used are Machine learning, AI, search engine engineering, and corporate analytics. Healthcare, gaming, and travel are some major fields where data analytics is used. 
    So, these were some major differences between data science and data analytics, there are others as well but for the time being, these are sufficient. But no matter what differences are there between the two fields, both data science and data analytics are two sides of the same coin. 

    Would you like to tell me how many of these were you already aware of and how many were new to you?

     

     

    What are the top career options for data analytics and data science?
    Data analytics and data science are often considered as one, but there is a difference. Data science is a vast career, and data analytics is a subset of data science. A large number of people today are inclining toward data analytics and data science careers. Well, there are various reasons for this inclination, such as :

    This is a field where there is a high average salary of individuals. 
    The industry is growing at a fast pace, and there is a huge demand for skilled personnel. 
    There is a lot of room for advancement in a career in this field. 
    So let’s now discuss the various job roles. As I have mentioned that data analytics and data science are two different fields, here are the top two career options for each of them separately. 


    Career options in data analytics: 

    Data analyst: This is the most common job role in the field of data analytics. But it does not mean that this does not have a wide career scope. We have already discussed that this field industry is facing a huge shortage of skilled individuals. The role of a data analyst is to analyze huge chunks of data and maintain databases. 
    Business Intelligence Analyst: Every moment, there is a huge momentum in the market, competitors, customers, anything that may take a huge turn at any moment, and that will have a huge impact on the business and its future. Therefore it is important for a business to analyze these shifts and turns in the market and make correct decisions accordingly. This is where the role of a Business Analyst comes to play. They analyze the shifts in market trends so that management can make appropriate decisions timely. 

    Career options in data science: 

    Data Engineer: This role is within the field of data science so this field will require more technical skills, and the problems will be more complex. The role of a data analyst requires maintenance of databases, the responsibilities of a data engineer are one step ahead. They are also responsible for updating those databases and data structures. 
    Project Manager: Project managers work with a team of data analysts and track their team's efficiency and progress. Project managers also maintain coordination with the data analysts and data scientists to maximize productivity and deliver the best results.

    Is Master's in Data Science a good career option in Australia?Among the courses Data Science, Data Analytics and Business Analytics comparatively which is the best option for a B. TECH student?

    Australia is home to some of the greatest universities in the world for studying Data Science and Business Analytics. As a result, Australian universities have become a popular alternative among overseas students seeking a Master's degree in Data Science. These universities also give you the option of studying part-time or full-time. Aside from that, data scientists are in high demand in Australia. A data scientist's annual income in Australia is now AU $95000, but this figure could rise dramatically based on experience. After earning a master's degree in data science, job chances in Australia are great, with salaries of up to $200,000 per year. Data Scientist, Data Analyst, Data Engineer, BI Developer, Data Manager, and other job titles are available. Among the courses, Data Science, Data Analytics and Business Analytics comparatively, data science is the best option because of its usefulness in all disciplines of science, technology, and business is the best option for a B. TECH student. If you have any further questions just ask me.

    The option of not having a data science library is bad for a Data Scientist?

    Well of-course it is. How would you suppose to work with no reference material? Or better, what would you work on if you don’t have the very core thing you need for your job? Data library is basically a storage unit that conserves data and information. But along with that it does more things.


    For example, there are separate systems and tech that operate regularly.  Having all work on one system increases the risk of failure and malfunction. However, there are small tasks within a machine that cannot be separated. For example, a data science library is not just a storage unit. It reprocessed data as well. When you transfer data from a drive to another, it encodes it, then formulates it and then decodes to get to your assistance.


    These tasks are not a work of a separate machine or say a part. Data libraries are one of the most crucial tech a data scientist may have. Without it, it will be like a manager without employees to management. I’m not saying that having a data library is utmost and things can’t function without it. However, if you do not keep a large database like it, you would simply have to rely upon your brain and piece of papers (which is not ideal in modern times).


    Now one may argue that data and information can be stored in the cloud as frequencies. And it will be right, unless it has a separate meaning, because the time you upload your data into the cloud, the cloud becomes your storage unit hence; data library. A data library is anything that can store data and formulate it. Basically, it’s up to you how you manage to keep and where.


    If you are working in a small-time business, it may be possible to work without  a data library. But large multinational corporations and firms need regular flow of information to keep their errands running. This can be in the form of orders or even an invoice. Anything that is helping to run your business is data. Data libraries are the most crucial thing for data scientists as it facilitates their work smoothly.


    By your question, I can assume that you are a data science aspirant. Are you in between your studies or looking for a program to apply? If you need any kind of information regarding data science, you can just leave a comment. 

    How much is the living cost in USA as a student?Also, which university is cheap and best for a data science degree?Can you suggest me universities with around $20-30k tuition?

    The USA is one of the top universities for earning an MS in data science. The USA is home to numerous institutions, including Ivy League schools, that strive to be the finest in the educational field. The best-known feature of an American institution is its multicultural and high-quality international student body. A postgraduate degree in data science takes between 12 and 24 months in the USA. The United States is among the top 3 nations for MS in Data Science programs and job opportunities.

    Top 10 universities in the US that you must consider studying in:

    1. Stanford University
    2. Columbia University
    3. Harvard University
    4. Yale University
    5. New York University
    6. University of Southern California
    7. Indiana University Bloomington
    8. University of Massachusetts Amherst
    9. Boston University
    10. University of Washington

    Salary and Job roles after MS in Data Science in the USA: 

    • Analytics Engineer ($111,480)
    • Business Analyst ($72,000)
    • Data Analyst ($73,372)
    • Data Scientist ($96,494)
    • Data Engineer ($116,591)
    • Statistician ($97990)
    • Data Visualisation Specialist ($76065)

    Data Science has established a niche for itself in many disciplines, be it the healthcare sector, retail marketing, or Life sciences, due to technological innovation and the wealth of data growing with each passing day in every field. Students throughout the world anticipate this course since it offers great employment chances. 


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