Last Updated on July 30, 2023
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njit data science ranking
- IR1. (2013 Payscale.com ROI rankings) NJIT ranked in the top 2% (27th out of 1486 colleges) in ROI (in-state tuition data used) or ranked 36th out of 1486 colleges if out-of-state tuition data are used.
- IR2-2020. (2020 US News & World Report) NJIT ranked 97th in the 2020 US News and World Report rankings published in September 2019 based on 2018 data.
- IR2-2021. (2021 US News & World Report) NJIT ranked 118th in 2021 US News and World Report rankings published in September 2020 based on 2019 data
njit data science course
Students in the Master of Science in Data Science (MSDS) program must successfully complete 30 credits based on any of the following options:
- Courses (30 credits)
- Courses (27 credits) + MS Project (3 credits)
- Courses (24 credits) + MS Thesis (6 credits)
Independent of the chosen option, all core courses in the respective tracks are required.
At most two courses can be chosen from outside the respective track with approval of the respective Program Co-Directors. Computational track students are allowed at most three electives that are non-Computer Science courses. Statistics track students are allowed at most three electives that are non-Math courses.
If a student chooses the MS project or MS thesis option, the project or thesis must be related to data science and requires approval from one of the Program Co-Directors.
The MSDS program has computational and statistics tracks that students must choose from at admission time. These tracks have different core courses but share the same admission requirements and electives.
Students may choose an elective outside the list after approval of their respective advisor.
M.S. in Data Science
Code | Title | Credits |
---|---|---|
Core Course Requirements for Computational Track | ||
CS 675 | Machine Learning | 3 |
CS 644 | Introduction to Big Data | 3 |
CS 636 | Data Analytics with R Program | 3 |
CS 677 | Deep Learning (Deep Learning) | 3 |
MATH 661 | Applied Statistics | 3 |
Code | Title | Credits |
---|---|---|
Electives and Foundation Courses | 15 | |
Computer Science Electives | ||
CS 610 | Data Structures and Algorithms | 3 |
CS 631 | Data Management System Design | 3 |
CS 632 | Advanced Database System Design | 3 |
CS 634 | Data Mining | 3 |
CS 636 | Data Analytics with R Program (only available to students in the Math core) | 3 |
CS 639 | Elec. Medical Records: Med Terminologies and Comp. Imp. | 3 |
CS 643 | Cloud Computing | 3 |
CS 645 | Security and Privacy in Computer Systems | 3 |
CS 656 | Internet and Higher-Layer Protocols | 3 |
CS 659 | Image Processing and Analysis | 3 |
CS 661 | Systems Simulation | 3 |
CS 670 | Artificial Intelligence | 3 |
CS 676 | Cognitive Computing | 3 |
CS 677 | Deep Learning (Deep Learning(available only to students in statistics track)) | 3 |
CS 683 | Software Project Management | 3 |
CS 684 | Software Testing and Quality Assurance | 3 |
CS 681 | Computer Vision | 3 |
CS 708 | Advanced Data Security and Privacy | 3 |
CS 731 | Applications of Database Systems | 3 |
CS 732 | Advanced Machine Learning | 3 |
CS 735 | High Performance Analytics Dat | 3 |
CS 744 | Data Mining and Management in Bioinformatics | 3 |
CS 782 | Pattern Recognition and Applications | 3 |
YWCC 691 | 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.) | 3 |
Math Electives | ||
MATH 630 | Linear Algebra and Applications | 3 |
MATH 631 | Linear Algebra | 3 |
MATH 644 | Regression Analysis Methods | 3 |
MATH 660 | Introduction to statistical Computing with SAS and R (only available to students in computational track) | 3 |
MATH 662 | Probability Distributions | 3 |
MATH 664 | Methods for Statistical Consulting | 3 |
MATH 665 | Statistical Inference | 3 |
MATH 678 | Stat Methods in Data Science | 3 |
CS 680 | Linux Kernel Programming | 3 |
CS 683 | Software Project Management | 3 |
MATH 699 | Design and Analysis of Experiments | 3 |
MATH 717 | Inverse Problems and Global Optimization | 3 |
MATH 786 | Large Sample Theory and Inference | 3 |
MATH 787 | Non-Parametric Statistics | 3 |
Other Electives | ||
BIOL 638 | Computational Ecology | 3 |
BME 698 | Selected Topics | 3 |
MGMT 635 | Data Mining and Analysis | 3 |
MGMT 630 | Decision Analysis | 3 |
FIN 600 | Corporate Finance I | 3 |
FIN 641 | Derivatives Markets | 3 |
FIN 642 | Derivatives and Structured Finance | 3 |
MRKT 630 | Models Of Consumer Behavior | 3 |
IS 601 | Web Systems Development | 3 |
IS 631 | Enterprise Database Management | 3 |
IS 650 | Data Visualization and Interpretation | 3 |
IS 657 | Spatiotemporal Urban Analytics | 3 |
IS 665 | Data Analytics for Info System | 3 |
IS 687 | Transaction Mining and Fraud Detection | 3 |
IS 688 | Web Mining | 3 |
BNFO 601 | Foundations of Bioinformatics I | 3 |
BNFO 602 | Foundations of Bioinformatics II | 3 |
BNFO 615 | Data Analysis in Bioinformatics | 3 |
BNFO 620 | Genomic Data Analysis | 3 |
Total Credits | 30 |
Recommended course sequence M.S. in Data Science for Computational Track
Fall | Spring | |
---|---|---|
Year 1 | CS 675 Machine Learning | CS 631 Data Management and System Design |
MATH 661 Applied Statistics | CS 644 Big Data | |
CS 636 R for Data Science | CS 677 Deep Learning | |
Year 2 | Free elective or Master thesis course | Free elective or Masters thesis course |
Free elective or Master project course | ||
Free elective |
njit m s data science fees
For each academic year, the standard cost of attendance as defined by the Student Financial Aid Services (SFAS) depends on your program, year in school, residency and housing selection.Tuition & Aid
Undergraduate Cost of Attendance for 2021 – 2022 (two semesters at full-time)
New Jersey Residents | Non-New Jersey Residents | |
Tuition | $14,790 | $30,808 |
Fees | $3,226 | $3,226 |
Total Tuition and Fees | $18,016 | $34,034 |
* For New Jersey resident and Non-New Jersey resident students living on campus, the value for Room & Board is $14,200 and Additional Indirect Cost is $4,100.
* For New Jersey resident and Non-New Jersey resident students living off campus, the value for Room & Board is $12,700 and Additional Indirect Cost is $6,300.
* The value for Books & Supplies is $3,000 (first-time freshmen and transfer non-architecture. $5,400 first-time freshmen and transfer architecture).
Graduate Cost of Attendance for 2021 – 2022 (two semesters at full-time)
New Jersey Residents | Non-New Jersey Residents | |
Tuition | $21,342 | $31,556 |
Fees | $3,204 | $3,204 |
Total Per Year | $24,546 | $34,760 |
* For New Jersey resident and Non-New Jersey resident students living on campus, the value for Room & Board is $14,200 and Additional Indirect Cost is $4,100.
* For New Jersey resident and Non-New Jersey resident students living off campus, the value for Room & Board is $12,700 and Additional Indirect Cost is $6,300.
* The value for Books & Supplies is $1,500 (non-architecture. $1,700 architecture).
Graduate e-Tuition (100% online)
- Cost per credit – $1,082
Njit Data Science
The Department of Data Science is the newest addition to the Ying Wu College of Computing. It was founded by well established, prominent researchers and educators with outstanding track records in Artificial Intelligence, Machine Learning, High Performance Data Analytics, Security/Privacy/Ethics in Data Science, Health Data Science, Green Data Science, and Data Visualization. The Department of Data Science was founded in 2021. The M.S. degree program in Data Science is jointly administered by the Department of Data Science and the Department of Mathematical Sciences. This degree program responds to a strong demand from employers for trained Data Scientists. Data is revolutionizing most industries and M.S. graduates in Data Science command high starting salaries.
Data Science combines powerful methods from Computer Science, Statistics, Artificial Intelligence and Machine Learning into a unique new blend of techniques for deriving valuable insights from Big Data. Data Science is an ideal choice for students who are interested in applying data processing methods to ever larger and more varied real-world data sets, including image, video, natural language and speech data that go substantially beyond traditional text and table data to solve real-world problems. The Department of Data Science closely collaborates with the Department of Mathematical Sciences and the Department of Computer Science. Students also can get involved in state-of-the-art research projects at the NJIT Institute for Data Science, where top notch scientists work with users to develop data-driven technologies to innovate the way the world works and lives.
Master of Science in Data Science
The Master of Science (M.S.) in Data Science (DS) is intended for students who are interested in pursuing advanced studies in data science.
Admission Requirements
- GPA
- Undergraduate GPA of at least 3.0 out of 4.0 is required for students with a data science, applied statistics, or computer science background.
- Undergraduate GPA of at least 3.0 out of 4.0 is required for students without a data science, applied statistics, or computer science background. Students wishing to pursue the computing track who have an insufficient computing background will be asked to enroll in a relevant Certificate Program and obtain a GPA of at least 3.0 before being admitted to the M.S. program. Students wishing to pursue the statistics track with an insufficient mathematics/statistics background will be asked to successfully complete suitable bridge courses as per the advisor’s review.
- Foreign students without GPA must have graduated “first class,” corresponding to a B average.
- International students TOEFL score: the Institute requires a minimum score of 213 paper based or 79 online.
- International students: GRE required.
- Students with a US or Canadian degree in data science, computer science, mathematical sciences, or engineering: GRE recommended but not required.
- Students with a US or Canadian degree not in data science, computer science, mathematical sciences, or engineering: GRE required.
Students are expected to have good programming skills and a grasp of the fundamentals of computer science, data science, and the mathematical sciences (students should have acquired this knowledge in the undergraduate degree Bachelor of Science in Data Science, Applied Statistics, or Computer Science or an equivalent degree). Detailed topics are listed below.
Applicants to the computing concentration lacking the computing background should first enroll in one of the three associated Data Science Certificates (Data Mining, Data Visualization, Big Data), and, upon successful completion of the Certificate, apply for transfer into the M.S. in DS program – computing concentration. Applicants to the statistics concentration with insufficient background in mathematics/statistics will be asked to complete suitable bridge courses as per the advisor’s review.
Students must maintain a cumulative graduate GPA of 3.0 or better throughout the course of studies and for graduation.
Application Processing
The Departments of Data Science and Mathematical Sciences review only completed applications submitted to the Office of Graduate Admissions. Applicants are advised to request status information on their application directly from the Graduate Admissions Office, not the Departments of Data Science or Mathematical Sciences. Graduate Admissions can be reached at [email protected] or www.njit.edu/gadmission or by mail at
NJIT, Graduate Admissions Office, University Heights, Newark NJ 07102.
Detailed Topics:
Students entering the M.S. in DS program are expected to have mastered the following topics: Basic programming constructs, writing and debugging programs, iteration, recursion; basic data structures (lists, arrays, hash tables), search and sort, algorithm analysis; basic probability distributions and statistical analysis; linear algebra, calculus (derivatives, integrals, applications, functions of multiple variables).
njit data science online
Online M.S. in Data Science: We live in a data driven world. Get in the driver’s seat.
In today’s AI-driven economy, there is a strong demand for data scientists equipped with computational skills to develop, design and apply models and tools for data-driven decision making. This program provides students a strong understanding of basic and advanced methods in statistical inference, machine learning, data visualization, data mining, and big data, all of which are essential skills for a high-performing data scientist.
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$75,800
Starting Salary, NJIT Average
$113,000
Mid-Career Salary, National Average
NJIT is the first university in New Jersey to offer an independent, standalone Master’s degree in Data Science.
Discover the Foundations of Data Science at NJIT
The M.S. in Data Science covers basic and advanced methods in statistical inference, machine learning, data visualization, data mining, and big data, all of which are essential skills for a high-performing data scientist. To be admitted to the program, we require a basic background in Mathematics (calculus, linear algebra), Statistics (probability and basic stats) and Software Development (programming, data structures and algorithms). Courses consist of formal lectures as well as hands-on programming projects. The program curriculum uses the Python programming language with its data science libraries and features tools like R for statistical analysis and Tableau for data visualization.
Students work on homework assignments and projects covering both theory and applications on real data with guidance from the professor and teaching assistants.
MS in Data Science graduates will enter the workplace with the education and training to:
- Be able to acquire, clean, and manage massive data sets.
- Play an analytical role in your company where you design, implement, and evaluate advanced statistical models and approaches for application to your company’s most complex problems.
- Be able to provide econometric and statistical models for a variety of problems including projections, classification, clustering, pattern analysis, sampling and simulations.
- Research new ways for predicting and modeling end-user behavior as well as investigating data summarization and visualization techniques for conveying key applied analytics findings.
- Apply modern artificial intelligence and deep learning methods to complex prediction and recognition tasks.
30 | Credits |
$1082 | cost per credit* |
Financial Aid Options Available | |
*View tuition and fee information or contact an Enrollment Services Manager for more information. |
Where do Data Science (Computing Option) majors work?
Common Job Titles
- Data Scientist
- Machine Learning Engineer
- Quantitative Analyst
- Data Warehouse Architect
- Business Intelligence Analyst
Top Employers
- Hearst
- ADP
- EY
- Cisco
Housed in the Department of Computer Science and offered in collaboration with the Department of Mathematical Sciences, the interdisciplinary Data Science program offers you the choice of a Computational or a Statistics track, while equipping you with the fundamentals and application tools to solve data science problems.
$101,000
Mid-Career Salary, National Average
NJIT is the first university in New Jersey to offer an independent, standalone Master’s degree in Data Science.
In addition to our main campus, students can also pursue an M.S. in Data Science at NJIT@JerseyCity
What do Data Science majors do?
Data Science specialists are expected to make informed architectural decisions based on a firm understanding of how available technologies differ and complement each other. As a Data Scientist, you will build and analyze predictive models from data using machine learning and statistical inference, program data science applications in high-level languages and extract patterns from large datasets using high-performance computing and distributed computing methods.
Degrees Offered
- M.S. Data Science
- M.S. Data Science (Online)
Where do Data Science majors work?
Common Job Titles
- Data Scientist
- Machine Learning Engineer
- Quantitative Analyst
- Data Warehouse Architect
- Business Intelligence Analyst
Top Employers
- Hearst
- ADP
- EY
- Cisco