Lean Six Sigma Advanced Certificate
A lean six sigma certification that utilizes the DMAIC methodology (define, measure, analyze, improve, and control) to expand your knowledge of statistics to improve business processes and enhance your career.
97%
Graduate Outcomes Rate
95K+
Average Salary Nationwide
65%
Lean Six Sigma Skills Appear in Over Half of All Job Postings for Engineers
24%
Demand Growth for Process Improvement Skills
Overview for Lean Six Sigma Adv. Cert.
Lean Six Sigma is a methodology for increasing organizational productivity and efficiency through a structured problem solving process called DMAIC (define, measure, analyze, improve, and control). The focus is on improving organizational systems and work processes.
Lean Six Sigma Certification: On-Campus or Online
The advanced certificate in Lean Six Sigma is for engineers, process-improvement facilitators, and other practitioners looking to increase their effectiveness or enhance their qualifications to broaden their careers. Lean Six Sigma has many benefits for organizations, among them:
- Reduction of new product development time
- Reduction of product delivery time
- Reduction of waste and costs
- Reduction of work-in-process inventory
- Reduction of product variability
- Increased profits
- Increased customer satisfaction, retention and loyalty
The focus of the courses in this certificate is on quality control situations in engineering and on driving process improvements in a broad range of business environments and industries to achieve the benefits outlined above. The certificate's courses may be completed on-campus or online.
Lean Six Sigma Training
Industry certifications such as Lean Six Sigma green belt and black belt are not the focus of this certificate program, however, students interested in obtaining these credentials are well prepared to do so after the deep topical coverage offered in this advanced certificate program. RIT’s Center for Quality and Applied Statistics offers three levels of certification for Lean Six Sigma practitioners: Yellow Belt, Green Belt, and Black Belt. Learn more about RIT’s offerings in Lean Six Sigma, including training schedules, examples of projects, and more.
What is a Graduate Certificate?
A graduate certificate, also called an advanced certificate, is a selection of up to five graduate level courses in a particular area of study. It can serve as a stand-alone credential that provides expertise in a specific topic that enhances your professional knowledge base, or it can serve as the entry point to a master’s degree. Some students complete an advanced certificate and apply those credit hours later toward a master’s degree.
This program is offered on-campus or online.
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Curriculum for 2024-2025 for Lean Six Sigma Adv. Cert.
Current Students: See Curriculum Requirements
Lean Six Sigma, advanced certificate, typical course sequence
| Course | Sem. Cr. Hrs. | |
|---|---|---|
| First Year | ||
| ISEE-682 | Lean Six Sigma Fundamentals This course presents the philosophy and methods that enable participants to develop quality strategies and drive process improvements. The fundamental elements of Lean Six Sigma are covered along with many problem solving and statistical tools that are valuable in driving process improvements in a broad range of business environments and industries. Successful completion of this course is accompanied by “yellow belt” certification and provides a solid foundation for those who also wish to pursue a “green belt.” (Green belt certification requires completion of an approved project which is beyond the scope of this course). (This course is restricted to degree-seeking graduate students and dual degree BS/MS or BS/ME students in KGCOE.) Lecture 3 (Fall, Spring, Summer). |
3 |
| Choose one of the following: | 3 |
|
| ISEE-660 | Applied Statistical Quality Control An applied approach to statistical quality control utilizing theoretical tools acquired in other math and statistics courses. Heavy emphasis on understanding and applying statistical analysis methods in real-world quality control situations in engineering. Topics include process capability analysis, acceptance sampling, hypothesis testing and control charts. Contemporary topics such as six-sigma are included within the context of the course. Note: Students required to take ISEE-560 for credit may not take ISEE-660 for credit. (This course is restricted to students in ISEE-MS, ENGMGT-MS, STATQL-ACT, MIE-PHD, or BIME-BS students with a BIMEISEE-U subplan that have completed STAT-205 or MATH-251 or ISEE-325 or MCEE-205 or equivalent course.) Lecture 3 (Fall). |
|
| STAT-621 | Statistical Quality Control A practical course designed to provide in-depth understanding of the principles and practices of statistical process control, process capability, and acceptance sampling. Topics include: statistical concepts relating to processes, Shewhart charts for attribute and variables data, CUSUM charts, EWMA charts, process capability studies, attribute and variables acceptance sampling techniques. (This class is restricted to students in the APPSTAT-MS, SMPPI-ACT, STATQL-ACT or MMSI-MS programs.) Lecture 3 (Fall, Spring). |
|
| Choose one of the following: | 3 |
|
| ISEE-760 | Design of Experiments This course presents an in-depth study of the primary concepts of experimental design. Its applied approach uses theoretical tools acquired in other mathematics and statistics courses. Emphasis is placed on the role of replication and randomization in experimentation. Numerous designs and design strategies are reviewed and implications on data analysis are discussed. Topics include: consideration of type 1 and type 2 errors in experimentation, sample size determination, completely randomized designs, randomized complete block designs, blocking and confounding in experiments, Latin square and Graeco Latin square designs, general factorial designs, the 2k factorial design system, the 3k factorial design system, fractional factorial designs, Taguchi experimentation. (Prerequisites: ISEE-325 or STAT-257 or MATH-252 or MCEE-205 or STAT-205 or equivalent course or students in ISEE-MS, ENGMGT-MS, or MIE-PHD programs.) Lecture 3 (Spring). |
|
| STAT-670 | Design of Experiments How to design and analyze experiments, with an emphasis on applications in engineering and the physical sciences. Topics include the role of statistics in scientific experimentation; general principles of design, including randomization, replication, and blocking; replicated and unreplicated two-level factorial designs; two-level fractional-factorial designs; response surface designs. Lecture 3 (Fall, Spring). |
|
| Elective | 3 | |
| Total Semester Credit Hours | 12 |
|
Electives
| Course | |
|---|---|
| BANA-680 | Data Management for Business Analytics This course introduces students to data management and analytics in a business setting. Students learn how to formulate hypotheses, collect and manage relevant data, and use standard tools such as Python and R in their analyses. The course exposes students to structured data as well as semi-structured and unstructured data. There are no pre or co-requisites; however, instructor permission is required for students not belonging to the MS-Business Analytics or other quantitative programs such as the MS-Computational Finance which have program-level pre-requisites in the areas of calculus, linear algebra, and programming. Lecture 3 (Fall). |
| PROF-710 | Project Management This course addresses project management from a multidisciplinary perspective, covering the fundamental nature of and techniques for managing a broad range of projects. Topics cover the Project Management Life Cycle from Planning to Termination. It also addresses the behavioral and quantitative facets of project management, as well as the use of methods, tools and techniques for the initiation, planning, and execution of projects. Introduces the standard framework, processes and knowledge areas of the Project Management Institute. *Note: Bachelors degree or minimum of 5 years of work experience in a project related business environment. Recommended education or work experience in organizational behavior, mathematics and basic accounting. *Note: BUSI-510 may not be substituted for BUSI-710 in a graduate concentration or the advanced certificate in project management. Additionally, a student may not register for and receive credit for both BUSI-510 and BUSI-710, whether taken as an undergraduate or graduate student. (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Lecture 3 (Fall, Spring, Summer). |
| PROF-711 | Advanced Project Management Advanced Project Management covers the topics necessary for implementation of and excellence in project management. It deals with turning the principles and theory of project management into practice. The course addresses the best practices for project management in the world; project portfolio management and ROI; the project office and Six Sigma; project risk management and integrated projects; corporate cultures, behavior, and cultural failures; informal, adaptive, and extreme project management; and critical chain project management. Integrates aspects of the framework, processes and knowledge areas of the Project Management Institute. *Note: Advanced Project Management is available in on-campus and online formats. (Prerequisite: (PROF-710 or DECS-744 or ISEE-750) or PROF-714 or equivalent course.) Lecture 3 (Fall, Spring, Summer). |
| PROF-712 | International Project Management With the increasing frequency of globalization, mergers, and acquisitions, international projects are becoming more prevalent and approaching the norm for many organizations. This course addresses a wide range of international projects—based in different industries and multiple countries. It deals with cultural and social differences within firms; cultural and social differences among countries and within countries; languages and dialect variations; different management practices and structures; religious practices; legal, regulatory, and reporting requirements; technology and infrastructure differences in different regions; and time zone differences. Incorporates aspects of the framework, processes and knowledge areas of the Project Management Institute. (Prerequisite: PROF-710 or PROF-711 or PROF-714 or equivalent course.) Lecture 3 (Fall, Spring, Summer). |
| PROF-714 | Agile Project Management Business agility allows organizations to quickly adapt to new markets. In a fast paced ever changing world of highly competitive products and services, organizations need to be able to deliver solutions to market quickly in an uncertain environment. Agile Project Management provides an iterative and incremental framework to explore and deliver high risk solutions efficiently in a rapid response timeframe. We will explore Agile Project Management practices across multiple industries including Agile project roles following the Project Management Institute® Agile Practice Guide. (This course is available to RIT degree-seeking graduate students.) Lecture 3 (Fall, Spring). |
| DECS-743 | Operations and Supply Chain Management Study of the management of operations and supply chain management. Encompasses both manufacturing and services. Topics include operations and supply chain strategy, ethical behavior, forecasting; work systems, inventory management, capacity and materials planning, lean operation, supply chain design and closed-loop supply chains, global operations, quality management, quality control, and quality improvement, project management; and current issues. (Prerequisites: DECS-782 or MGIS-650 or equivalent course.) Lecture 3 (Fall, Spring, Summer). |
| DECS-744 | Project Management A study in the principles of project management and the application of various tools and techniques for project planning and control. This course focuses on the leadership role of the project manager, and the roles and responsibilities of the team members. Considerable emphasis is placed on statements of work and work breakdown structures. The course uses a combination of lecture/discussion, group exercises, and case studies. (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Lecture 3 (Fall, Spring). |
| DECS-745 | Quality Control and Improvement |
| INTB-710 | Global Business Analytics This course is designed to help students, regardless their backgrounds, to identify global business opportunities, possess necessary analytical skills to evaluate these opportunities, and understand the strategies to explore these opportunities to serve transnational businesses’ goals. Students will be exposed to a variety of analytical skill sets such as collecting and analyzing institutional and primary international business data, reading the multinational firm-level data and understanding how global expansion impacts firms’ bottom lines, developing foreign exchange hedging strategies, and apprehending the basic practices of international trade and foreign investment. (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Lecture 3 (Fall). |
| ISEE-626 | Lean System Design In today’s competitive business environment, organizations strive to deliver high-quality products and services efficiently while continuously improving their processes. This course explores the principles and methodologies of lean manufacturing and service systems design, providing students with the knowledge and skills to improve operational systems across various industries. Topics covered include value stream mapping, just-in-time production, pull systems, continuous improvement, standardization, and visual management. The course also explores strategies for aligning operational systems with customer needs and market demands, fostering a culture of continuous improvement, to drive change and innovation. (This course is restricted to students in ISEE-MS, ENGMGT-MS, MIE-PHD, BIME-BS students with a BIMEISEE-U subplan, ISEE-BS students with a ISEEMS-U or ISEEEGMT-U subplan, or those with 5th year standing in ISEE-BS or ISEEDU-BS.) Lecture 3 (Fall). |
| ISEE-703 | Supply Chain Management Supply chain management is unique in that it is one of the oldest business activities and yet has been recently discovered as a potentially powerful source of competitive advantage. Supply chain system activities, such as planning production levels, forecasting demand, managing inventory, warehousing, transportation, and locating facilities have been performed since the start of commercial activity. It is difficult to visualize any product that could reach a customer without a consciously designed supply chain. Yet it is only recently that many firms have started focusing on supply chain management. There is a realization that no company can do any better than its supply chain and logistics systems. This becomes even more important given that product life cycles are shrinking and competition is intense. Logistics and supply chain management today represents a great challenge as well as a tremendous opportunity for most firms. (Prerequisites: ISEE-420 or equivalent course or degree-seeking graduate students or BIME-BS students with a BIMEISEE-U subplan.) Lecture 3 (Spring). |
| ISEE-704 | Logistics This course discusses several strategic, tactical, and operational concepts used in improving the distribution of goods and services by companies worldwide. The course emphasis is on understanding when and how these concepts are applied, as well as on using mathematical programming and optimization methods for their adequate implementation. (Prerequisites: ISEE-420 or ISEE-601 or equivalent course.) Lecture 3 (Fall). |
| ISEE-720 | Production Control This course covers the process and the analysis methods used to produce goods and services to support of the production and operations management functions. Topics include: forecasting, inventory policies and models, job shop scheduling, aggregate production planning, and ERP systems. Students will understand the importance of production control and its relationship to other functions within the organization, and the role of mathematical optimization to support production planning. The course emphasizes how a production process can be characterized by a process that requires answering a sequence of decision-making problems. The course will show how the production functions integrate with each other and how their coordination can be automated through mathematical programming. Identifying opportunities for improvement through optimization is also highlighted. (Prerequisites: ISEE-601 or (ISEE-301 and (STAT-251 or MATH-251)) or equivalent courses.) Lecture 3 (Spring). |
| ISEE-723 | Global Facilities Planning Facilities planning determines how an activity's tangible fixed assets best support achieving the activity's objective. This course will provide knowledge of the principles and practices of facility layout, material handling, storage and warehousing, and facility location for manufacturing and support facilities. Tools for sizing the resources needed, planning, design, evaluation, selection, and implementation will be covered. The focus of the course will cover both management and design aspects, with the focus being more heavily on the management aspects. (This course is available to RIT degree-seeking graduate students.) Lecture 3 (Fall). |
| ISEE-728 | Production Systems Management The focus of this course is Lean. Students who take this course should be interested in building on their basic knowledge of (lean) contemporary production systems and developing the breadth and depth of their understanding, with a focus on the managerial, quantitative, and systems aspects. It will also address value streams beyond manufacturing - specifically logistics. This course should enable the student to practice the application of lean concepts in the context of systems design at the enterprise level. (Prerequisites: ISEE-420 or ISEE-626 or equivalent course.) Lecture 3 (Spring). |
| ISEE-745 | Manufacturing Systems This course will provide an introduction to concepts and techniques in the design and analysis of production systems. A blend of traditional and modern approaches is brought into the classroom. At the end of the term, the student will be able to assess and analyze the performance of a given manufacturing system as well as to provide a framework for system redesign and improvement. Modern aspects such as lean manufacturing and setup time reduction are included in the context of the course. (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Lecture 3 (Spring). |
| ISEE-750 | Systems and Project Management This course ensures progress toward objectives, proper deployment and conservation of human and financial resources, and achievement of cost and schedule targets. The focus of the course is on the utilization of a diverse set of project management methods and tools. Topics include strategic project management, project and organization learning, chartering, adaptive project management methodologies, structuring of performance measures and metrics, technical teams and project management, risk management, and process control. Course delivery consists of lectures, speakers, case studies, and experience sharing, and reinforces collaborative project-based learning and continuous improvement. (Prerequisites: ISEE-350 or equivalent course or students in ISEE-MS, ENGMGT-MS, PRODDEV-MS, MFLEAD-MS, or MIE-PHD programs or BIME-BS students with a BIMEISEE-U subplan.) Lecture 3 (Fall). |
| ISEE-751 | Decision and Risk Benefit Analysis This course addresses decision making in the face of risk and uncertainty. Various methodologies will be introduced that are useful in describing and making decisions about risks, with particular emphasis on those associated with the design of products. Students will be exposed to issues related to balancing risks and benefits in situations involving human safety, product liability, environmental impact, and financial uncertainty. Presentations will be made of risk assessment studies, public decision processes, and methods for describing and making decisions about the societal risks associated with engineering projects. Topics include probabilistic risk assessment, cost-benefit analysis, reliability and hazard analysis, decision analysis, portfolio analysis, and project risk management. (This course is restricted to students in MFLEAD-MS and PRODDEV-MS .) Lecture 3 (Spring). |
| ISEE-752 | Decision Analysis This course presents the primary concepts of decision analysis. Topics important to the practical assessment of probability and preference information needed to implement decision analysis are considered. Decision models represented by a sequence of interrelated decisions, stochastic processes, and multiple criteria are also addressed. We cover EMV and Non-EMV decision-making concepts. Finally, the organizational use of decision analysis and its application in real-world case studies is presented. (Srerequisites: ISEE-325 or MATH-251 or MATH-252 or STAT-205 or MCEE-205 or equivalent course or students in ISEE-MS, ENGMGT-ME, or MIE-PHD programs.) Lecture 3 (Spring). |
| ISEE-771 | Engineering of Systems I The engineering of a system is focused on the identification of value and the value chain, requirements management and engineering, understanding the limitations of current systems, the development of the overall concept, and continually improving the robustness of the defined solution. EOS I & II is a 2-semester course sequence focused on the creation of systems that generate value for both the customer and the enterprise. Through systematic analysis and synthesis methods, novel solutions to problems are proposed and selected. This first course in the sequence focuses on the definition of the system requirements by systematic analysis of the existing problems, issues and solutions, to create an improved vision for a new system. Based on this new vision, new high-level solutions will be identified and selected for (hypothetical) further development. The focus is to learn systems engineering through a focus on an actual artifact (This course is restricted to students in ISEE-MS, PRODDEV-MS, MFLEAD-MS, ENGMGT-MS, MIE-PHD, BIME-BS students with a BIMEISEE-U subplan, ISEE-BS students with a ISEEMS-U or ISEEEGMT-U subplan, or those with 5th year standing in ISEE-BS or ISEEDU-BS.) Lecture 3 (Fall, Spring). |
| ISEE-786 | Lifecycle Assessment This course introduces students to the challenges posed when trying to determine the total lifecycle impacts associated with a product or a process design. Various costing models and their inherent assumptions will be reviewed and critiqued. The inability of traditional costing models to account for important environmental and social externalities will be highlighted. The Lifecycle Assessment approach for quantifying environmental and social externalities will be reviewed and specific LCA techniques (Streamlined Lifecycle Assessment, SimaPro) will be covered. (This course is restricted to students in ISEE-MS, SUSTAIN-MS, ENGMGT-ME, MECE-MS, MECE-ME, SUSPRD-MN, MIE-PHD or those with at least 4th year standing in ISEE-BS or ISEEDU-BS.) Lecture 3 (Spring). |
| MGIS-650 | Introduction to Data Analytics and Business Intelligence This course serves as an introduction to data analysis including both descriptive and inferential statistical techniques. Contemporary data analytics and business intelligence tools will be explored through realistic problem assignments. Lecture 3 (Fall). |
| SERQ-723 | Service Analytics Analytics in service organizations is based on four phases: analysis and determination of what data to collect, gathering the data, analyzing it, and communicating the findings to others. In this course, students will learn the fundamentals of analytics to develop a measurement strategy for a given area of research and analysis. While this measurement process is used to ensure that operations function well and customer needs are met; the real power of measurement lies in using analytics predicatively to drive growth and service, to transform the organization and the value delivered to customers. Topics include big data, the role of measurement in growth and innovation, methodologies to measure quality, and other intangibles. Lecture 3 (Fall, Summer). |
| STAT-611 | Statistical Software - R This course is an introduction to the statistical-software package R, which is often used in professional practice. Some comparisons with other statistical-software packages will also be made. Topics include: data structures; reading and writing data; data manipulation, subsetting, reshaping, sorting, and merging; conditional execution and looping; built-in functions; creation of new functions; graphics; matrices and arrays; simulations and app development with Shiny. (This course is restricted to students in APPSTAT-MS or SMPPI-ACT.) Lecture 3 (Fall, Spring). |
| STAT-614 | Applied Statistics Statistical tools for modern data analysis can be used across a range of industries to help you guide organizational, societal and scientific advances. This course is designed to provide an introduction to the tools and techniques to accomplish this. Topics covered will include continuous and discrete distributions, descriptive statistics, hypothesis testing, power, estimation, confidence intervals, regression, one-way ANOVA and Chi-square tests. (This class is restricted to degree-seeking graduate students or those with permission from instructor.) Lecture 3 (Fall). |
| STAT-641 | Applied Linear Models - Regression A course that studies how a response variable is related to a set of predictor variables. Regression techniques provide a foundation for the analysis of observational data and provide insight into the analysis of data from designed experiments. Topics include happenstance data versus designed experiments, simple linear regression, the matrix approach to simple and multiple linear regression, analysis of residuals, transformations, weighted least squares, polynomial models, influence diagnostics, dummy variables, selection of best linear models, nonlinear estimation, and model building. (This class is restricted to students in the APPSTAT-MS, SMPPI-ACT, or APPSTAT-U programs.) Lecture 3 (Fall, Spring, Summer). |
| STAT-642 | Applied Linear Models - ANOVA This course introduces students to analysis of models with categorical factors, with emphasis on interpretation. Topics include the role of statistics in scientific studies, fixed and random effects, mixed models, covariates, hierarchical models, and repeated measures. (This class is restricted to students in the APPSTAT-MS, SMPPI-ACT, or APPSTAT-U programs.) Lecture 3 (Spring, Summer). |
| STAT-745 | Predictive Analytics This course is designed to provide the student with solid practical skills in implementing basic statistical and machine learning techniques for the purpose of predictive analytics. Throughout the course, many real world case studies are used to motivate and explain the strengths and appropriateness of each method of interest. In those case studies, students will learn how to apply data cleaning, visualization, and other exploratory data analysis tools to a variety of real world complex data. Students will gain experience with reproducibility and documentation of computational projects and with developing basic data products for predictive analytics. The following techniques will be implemented and then tested with cross-validation: regularization in linear models, regression and smoothing splines, k-nearest neighbor, and tree-based methods, including random forest. (Prerequisite: This class is restricted to students in APPSTAT-MS and SMPPI-ACT who have successfully completed STAT 611 and STAT-741 or equivalent courses.) Lecture 3 (Spring). |
| STAT-747 | Principles of Statistical Data Mining This course covers topics such as clustering, classification and regression trees, multiple linear regression under various conditions, logistic regression, PCA and kernel PCA, model-based clustering via mixture of gaussians, spectral clustering, text mining, neural networks, support vector machines, multidimensional scaling, variable selection, model selection, k-means clustering, k-nearest neighbors classifiers, statistical tools for modern machine learning and data mining, naïve Bayes classifiers, variance reduction methods (bagging) and ensemble methods for predictive optimality. (Prerequisites: This class is restricted to students in APPSTAT-MS or SMPPI-ACT who have successfully completed STAT-611, STAT-731 and STAT-741 or equivalent courses.) Lecture 3 (Fall, Spring). |
Certain countries and individuals are subject to comprehensive embargoes under US Export Controls, which prohibit virtually ALL exports, imports and other transactions without a license or other US Government authorization. Individuals applying for online study who are subject to these embargoes will be notified during the application process.
Note for online students
The frequency of required and elective course offerings in the online program will vary, semester by semester, and will not always match the information presented here. Online students are advised to seek guidance from the listed program contact when developing their individual program course schedule.
Admissions and Financial Aid
This program is available on-campus or online.
On Campus
| Offered | Admit Term(s) | Application Deadline | STEM Designated |
|---|---|---|---|
| Part-time | Fall, Spring, or Summer | Rolling | No |
Online
| Offered | Admit Term(s) | Application Deadline | STEM Designated |
|---|---|---|---|
| Part-time | Fall, Spring, or Summer | Rolling | No |
Part-time study is 1‑8 semester credit hours. RIT will not issue a student visa for advanced certificates.
Application Details
To be considered for admission to the Lean Six Sigma Adv. Cert. program, candidates must fulfill the following requirements:
- Complete an online graduate application.
- Submit copies of official transcript(s) (in English) of all previously completed undergraduate and graduate course work, including any transfer credit earned.
- Hold a baccalaureate degree (or US equivalent) from an accredited university or college. A minimum cumulative GPA of 3.0 (or equivalent) is recommended.
- Satisfy prerequisite requirements and/or complete bridge courses prior to starting program coursework.
- Submit a current resume or curriculum vitae.
- Submit a personal statement of educational objectives.
- Submit one letter of recommendation.
- Entrance exam requirements: None
- Submit English language test scores (TOEFL, IELTS, PTE Academic), if required. Details are below.
English Language Test Scores
International applicants whose native language is not English must submit one of the following official English language test scores. Some international applicants may be considered for an English test requirement waiver.
| TOEFL | IELTS | PTE Academic |
|---|---|---|
| 79 | 6.5 | 56 |
International students below the minimum requirement may be considered for conditional admission. Each program requires balanced sub-scores when determining an applicant’s need for additional English language courses.
How to Apply Start or Manage Your Application
Cost and Financial Aid
An RIT graduate degree is an investment with lifelong returns. Graduate tuition varies by degree, the number of credits taken per semester, and delivery method. View the general cost of attendance or estimate the cost of your graduate degree.
A combination of sources can help fund your graduate degree. Learn how to fund your degree
Additional Information
Prerequisites
Applicants must have college-level credit or practical experience in statistics (at least one course in probability and statistics).
Online Degree Information
The online Lean Six Sigma Advanced Certificate can only be completed part-time, taking one or two courses per term. The average time to completion is one year. Delivery is a blend of asynchronous and synchronous study, and academic advisors work with students to select courses that meet degree requirements and student schedules. Students typically spend 10-12 hours per week per class, depending on the content and their background knowledge. For specific details about the delivery format and learning experience, contact the Program Contact listed on this page. RIT does not offer student visas for online study.
Online Tuition Eligibility
The online Lean Six Sigma Adv. Cert. is a designated online degree program that is billed at a 43% discount from our on-campus rate. View the current online tuition rate.
Online Study Restrictions for Some International Students
Certain countries are subject to comprehensive embargoes under US Export Controls, which prohibit virtually ALL exports, imports, and other transactions without a license or other US Government authorization. Learners from the Crimea region of the Ukraine, Cuba, Iran, North Korea, and Syria may not register for RIT online courses. Nor may individuals on the United States Treasury Department’s list of Specially Designated Nationals or the United States Commerce Department’s table of Deny Orders. By registering for RIT online courses, you represent and warrant that you are not located in, under the control of, or a national or resident of any such country or on any such list.
Contact
Admissions Contact
- Lindsay Lewis
- Senior Assistant Director
- Office of Graduate and Part-Time Enrollment Services
- Enrollment Management
- 585‑475‑5532
- lslges@rit.edu
Program Contact
- Rebecca Ziebarth
- Assistant Dean of Graduate Studies
- John D. Hromi Center for Quality and Applied Statistics
- Kate Gleason College of Engineering
- 585‑475‑2033
- razeqa@rit.edu
Offered within
the
John D. Hromi Center for Quality and Applied Statistics
John D. Hromi Center for Quality and Applied Statistics