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The Master of Science in Machine Learning and Data Science (MLDS) at Northwestern University is a rigorous, industry-oriented STEM degree designed to train students in advanced techniques across machine learning, data science, and artificial intelligence. Housed within the McCormick School of Engineering, this program emphasizes both technical excellence and business acumen, preparing graduates to lead data-driven innovation across sectors.
Formerly known as the MS in Analytics, the rebranded MLDS program reflects the evolving needs of the industry and provides cutting-edge training in data engineering, machine learning, model development, and stakeholder communication.
Program Format & Duration
Full-time, cohort-based residential program
Duration: 15 months (September to December of the following year)
Location: Northwestern University, Evanston, Illinois
STEM-designated (eligible for OPT extension for international students)
GRE optional
Core Curriculum Components
The MLDS curriculum is designed to cover the full spectrum of the data science workflow—spanning data collection, model development, deployment, and business impact.
Core Courses Include:
Data Engineering & Management
Relational Databases & SQL
Big Data Architecture & Cloud Platforms
Data Pipelines & APIs
Mathematics & Statistical Foundations
Linear Algebra for Machine Learning
Statistical Inference & Regression
Bayesian Methods
Machine Learning & AI
Supervised & Unsupervised Learning
Deep Learning & Neural Networks
Natural Language Processing
Model Evaluation & Interpretability
Programming & Tools
Python, R, Spark
AWS, Hadoop, Docker
Git, Jupyter Notebooks
Professional Development
Storytelling with Data
Communication for Technical Leaders
Team Management & Agile Workflows
The MLDS program is deeply experiential, providing hands-on opportunities through projects, competitions, and professional immersion.
Capstone Practicum
A 10-month team-based consulting project sponsored by corporate partners
Students solve real-world problems using data science methods for companies in finance, healthcare, retail, tech, and manufacturing
Includes client presentations, technical deliverables, and executive summaries
Past partners: Allstate, Deloitte, Walgreens, IBM, AbbVie, United Airlines
Internship (Summer Quarter)
Students participate in a full-time summer internship after completing two quarters of coursework
Supported by the program’s dedicated career services team
100% of students typically secure paid internships with top-tier employers
Competitions & Hackathons
Students engage in Kaggle-style machine learning challenges
Participate in internal “DataThons” and national data science competitions
Graduates of Northwestern’s MLDS program are trained to bridge the gap between data and decision-making. With strengths in both technical implementation and business strategy, they are highly sought after across industries.
Career Outcomes
Common job titles include:
Top Employers
Graduates go on to work at:
Graduate Competencies
Salary Overview-
Top Employers-
Geographic Placement-
Industry Sectors-
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What This Means for You-
Letters of Recommendation: Provide three letters—preferably a mix of academic and professional depending on how recently you graduated.Personal Statement: Submit a statement that highlights your motivations, experience, interest in MLDS, and future goals. Scholarship Statement: Include optional content explaining any scholarship needs or eligibility.Transcripts & GPA: Upload unofficial transcripts from all relevant institutions showing a minimum cumulative GPA of 3.0; certified English translations required if not in English. Prerequisites (Recommended): Demonstrate aptitude in calculus, linear algebra, probability, statistics, and programming languages like Python, R, Java, or C++.GRE/GMAT (Optional): Test scores are optional and considered only if provided and taken within the past five years.English Proficiency: International applicants must submit TOEFL (≥ 95 iBT) or IELTS (≥ 7.5) unless exempt via a degree taught in English. Resume/CV: Upload a résumé or CV outlining your academic and professional background.Candidate Video (Optional): Submit an optional video to showcase your personality, leadership, and fit for the collaborative cohort.Supplementary Materials (Optional): Include project portfolios, GitHub links, or relevant coursework/certifications. Fee Waiver: U.S. veterans, active-duty military, and GEM fellows are eligible for application fee waivers.Deadlines: Apply between September 1 and January 15, with scholarship priority deadline on December 1, and final decisions typically released in mid-March. Three‑Year Bachelor’s Degrees: Northwestern accepts three-year undergraduate degrees from accredited international institutions with no disadvantage or special conditions imposed.WES Evaluation: Applicants do not need to submit WES or other credential evaluations, as official transcripts sent directly are sufficient for admission assessment.Data AnalystData ScientistBusiness AnalystStatisticianStatistical ProgrammerSAS ProgrammerMachine Learning EngineerDeep Learning EngineerAI ResearcherData EngineerBI DeveloperData ArchitectAnalytics ConsultantAdvisory ConsultantQuantitative AnalystRisk AnalystOperations AnalystMarketing AnalystResearch ScientistInsights AnalystForecasting AnalystHealthcare Data AnalystFinancial Data AnalystProduct Analyst
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Northwestern University
