SUNY Polytechnic Institute Ranked #2 Top Public School and #2 Best Value College in the U.S. News and World Report’s list of Regional Universities North, SUNY Poly offers a range of popular academic programs, many in fields with increasing demand, taught by caring faculty. The new Center for Advanced Manufacturing (CGAM) gives students 16,000+ sq. ft. of high-tech state-of-the-art space to model, visualize, and test in the world of virtual-to-real manufacturing with a five-axis CNC machining center, industry level 3D printers, prototyping centers, and design studios. Opportunities like CGAM, small class sizes, successful graduates and affordability are all reasons students choose SUNY Poly.
>> FULLY ONLINE PROGRAM Certificate for Advanced Study (Post Bachelor’s)
Data Analysis
For More Information: Graduate Admissions Office State University of New York Polytechnic Institute 100 Seymour Road Utica, NY 13502 315-792-7347 graduate@sunypoly.edu www.sunypoly.edu
Ranked #2 Top Public School and #2 Best Value College: Regional Universities North 12/19
— U.S. News & World Report, 2020
SUNY Polytechnic Institute Ranked #2 Top Public School and #2 Best Value College in the U.S. News and World Report’s list of Regional Universities North, SUNY Poly offers a range of popular academic programs, many in fields with increasing demand, taught by caring faculty. The new Center for Advanced Manufacturing (CGAM) gives students 16,000+ sq. ft. of high-tech state-of-the-art space to model, visualize, and test in the world of virtual-to-real manufacturing with a five-axis CNC machining center, industry level 3D printers, prototyping centers, and design studios. Opportunities like CGAM, small class sizes, successful graduates and affordability are all reasons students choose SUNY Poly.
>> FULLY ONLINE PROGRAM Certificate for Advanced Study (Post Bachelor’s)
Data Analysis
For More Information: Graduate Admissions Office State University of New York Polytechnic Institute 100 Seymour Road Utica, NY 13502 315-792-7347 graduate@sunypoly.edu www.sunypoly.edu
Ranked #2 Top Public School and #2 Best Value College: Regional Universities North 12/19
— U.S. News & World Report, 2020
Degree Requirements The 12 credit hour Advanced Certificate in Data Analysis consists of 4 courses: 1. MAT 505 Introduction to Probability (3 credits) 2. MST 570 Design & Analysis of Experiments (3 credits) 3. STA 510 Regression and Analysis of Variance (3 credits) 4. MST 680 Reliability and Quality Assurance (3 credits) Certificate for Advanced Study in Data Analysis (Online)
The Program The post-bachelor’s Certificate for Advanced Study in Data Analysis provides both a practical and theoretical foundation for professionals who need to understand randomness and variability, its causes and consequences. Students will learn how to design efficient and effective experiments and observational studies in order to answer questions they find interesting. The program works students through important probability models and the underlying mathematics to understand random phenomena. Software is used to analyze data and make effective presentations of results to different audiences. The program is designed for students who have a bachelor’s degree in any field. In addition, a background in mathematics including calculus I, II, III, and linear algebra/matrix methods is required.
Career Opportunities The Advanced Certificate in Data Analysis allows students the opportunity to expand their analytical and presentation skills in this dynamic and growing field, resulting in increased career advancement opportunities. Actuaries, electrical engineers, computer scientists and quality and system engineers all need strong foundations in probability and data analysis and would benefit professionally from this program.
OR
MAT 550 Time Series (3 credits)
Students are required to consult with a faculty member to develop an academic plan.
Admission Guidelines To be considered for admission, all applicants to the Data Analysis program must possess a baccalaureate degree from an accredited university or college with an average of B or better (a GPA of 3.0 on a 4.0 scale). In addition, a background in mathematics including calculus I, II, III, and linear algebra/ matrix methods is required. Applicants not meeting the above admission criteria will be considered on an individual basis. The Application for Graduate Admission and all required forms are available at: www.sunypoly.edu/graduate
Online Learning Online students find it easy to pursue their studies through Angel, our interactive online learning environment. Course lectures, class discussions, assignments and exams are conducted through an easy-to-navigate web tool. This learning option appeals to busy working professionals and others interested in pursuing advanced coursework while juggling multiple life commitments.
The Faculty SUNY Poly faculty work closely with students and challenge them to excel. Many have experience in industry in addition to strong academic credentials. A low student-to-faculty ratio (18:1) means faculty really get to know and work closely with students. Dr. Andrea Dziubek is an Assistant Professor of Applied Mathematics with a Ph.D in Energy and Process Engineering from Berlin University of Technology, Germany. Her research interests include modeling and simulation of problems in biomedical engineering, continuum mechanics, shell theory, structure preserving numerical methods and finite element methods. She loves teaching courses where she can share her academic interests and excitement, such as vector calculus, numerical mathematics, and differential equations. Dr. Edmond Rusjan is an Associate Professor of Applied Mathematics with a PhD in Mathematical Physics from Virginia Tech. His research focus is on geometry and symmetry inspired mathematical models. In particular, he has applied the Boltzmann equation, Lie groups and Lie algebras and Calabi-Yau spaces to solve problems in physics and engineering. He is currently studying the discretization of the Hodge star operator and implications for partial differential equations. Dr. William Thistleton is an Associate Professor of Applied Mathematics, with degrees in Electrical Engineering and Mathematics, and a PhD in Applied Mathematics from SUNY Stony Brook. In addition to his extensive teaching experience in areas including Analysis, Computational Mathematics, and Data Analysis, he has scholarly publications in Probability and Statistics. He consults regularly with industry in a variety of settings. Dr. Zora Thomova is a Professor of Applied Mathematics with PhD in Mathematics from University of Montreal, Canada and MS in Engineering Physics from the Czech Technical University in Prague. She is a recipient of the SUNY Chancellor’s Award for Excellence in teaching; her teaching experience includes mathematics courses at both the undergraduate and graduate level to mathematics and engineering students. She also teaches financial mathematics and fundamentals of derivative markets to MBA students and finance professionals at a major investment institution. She regularly publishes in the area of continuous symmetries of differential and difference equations and has served as an adviser on quantitative projects for financial clients.
“The Advanced Certificate in Data Analysis provides both a practical and theoretical foundation for professionals who need to understand randomness and variability, its causes and consequences.”
Degree Requirements The 12 credit hour Advanced Certificate in Data Analysis consists of 4 courses: 1. MAT 505 Introduction to Probability (3 credits) 2. MST 570 Design & Analysis of Experiments (3 credits) 3. STA 510 Regression and Analysis of Variance (3 credits) 4. MST 680 Reliability and Quality Assurance (3 credits) Certificate for Advanced Study in Data Analysis (Online)
The Program The post-bachelor’s Certificate for Advanced Study in Data Analysis provides both a practical and theoretical foundation for professionals who need to understand randomness and variability, its causes and consequences. Students will learn how to design efficient and effective experiments and observational studies in order to answer questions they find interesting. The program works students through important probability models and the underlying mathematics to understand random phenomena. Software is used to analyze data and make effective presentations of results to different audiences. The program is designed for students who have a bachelor’s degree in any field. In addition, a background in mathematics including calculus I, II, III, and linear algebra/matrix methods is required.
Career Opportunities The Advanced Certificate in Data Analysis allows students the opportunity to expand their analytical and presentation skills in this dynamic and growing field, resulting in increased career advancement opportunities. Actuaries, electrical engineers, computer scientists and quality and system engineers all need strong foundations in probability and data analysis and would benefit professionally from this program.
OR
MAT 550 Time Series (3 credits)
Students are required to consult with a faculty member to develop an academic plan.
Admission Guidelines To be considered for admission, all applicants to the Data Analysis program must possess a baccalaureate degree from an accredited university or college with an average of B or better (a GPA of 3.0 on a 4.0 scale). In addition, a background in mathematics including calculus I, II, III, and linear algebra/ matrix methods is required. Applicants not meeting the above admission criteria will be considered on an individual basis. The Application for Graduate Admission and all required forms are available at: www.sunypoly.edu/graduate
Online Learning Online students find it easy to pursue their studies through Angel, our interactive online learning environment. Course lectures, class discussions, assignments and exams are conducted through an easy-to-navigate web tool. This learning option appeals to busy working professionals and others interested in pursuing advanced coursework while juggling multiple life commitments.
The Faculty SUNY Poly faculty work closely with students and challenge them to excel. Many have experience in industry in addition to strong academic credentials. A low student-to-faculty ratio (18:1) means faculty really get to know and work closely with students. Dr. Andrea Dziubek is an Assistant Professor of Applied Mathematics with a Ph.D in Energy and Process Engineering from Berlin University of Technology, Germany. Her research interests include modeling and simulation of problems in biomedical engineering, continuum mechanics, shell theory, structure preserving numerical methods and finite element methods. She loves teaching courses where she can share her academic interests and excitement, such as vector calculus, numerical mathematics, and differential equations. Dr. Edmond Rusjan is an Associate Professor of Applied Mathematics with a PhD in Mathematical Physics from Virginia Tech. His research focus is on geometry and symmetry inspired mathematical models. In particular, he has applied the Boltzmann equation, Lie groups and Lie algebras and Calabi-Yau spaces to solve problems in physics and engineering. He is currently studying the discretization of the Hodge star operator and implications for partial differential equations. Dr. William Thistleton is an Associate Professor of Applied Mathematics, with degrees in Electrical Engineering and Mathematics, and a PhD in Applied Mathematics from SUNY Stony Brook. In addition to his extensive teaching experience in areas including Analysis, Computational Mathematics, and Data Analysis, he has scholarly publications in Probability and Statistics. He consults regularly with industry in a variety of settings. Dr. Zora Thomova is a Professor of Applied Mathematics with PhD in Mathematics from University of Montreal, Canada and MS in Engineering Physics from the Czech Technical University in Prague. She is a recipient of the SUNY Chancellor’s Award for Excellence in teaching; her teaching experience includes mathematics courses at both the undergraduate and graduate level to mathematics and engineering students. She also teaches financial mathematics and fundamentals of derivative markets to MBA students and finance professionals at a major investment institution. She regularly publishes in the area of continuous symmetries of differential and difference equations and has served as an adviser on quantitative projects for financial clients.
“The Advanced Certificate in Data Analysis provides both a practical and theoretical foundation for professionals who need to understand randomness and variability, its causes and consequences.”
Degree Requirements The 12 credit hour Advanced Certificate in Data Analysis consists of 4 courses: 1. MAT 505 Introduction to Probability (3 credits) 2. MST 570 Design & Analysis of Experiments (3 credits) 3. STA 510 Regression and Analysis of Variance (3 credits) 4. MST 680 Reliability and Quality Assurance (3 credits) Certificate for Advanced Study in Data Analysis (Online)
The Program The post-bachelor’s Certificate for Advanced Study in Data Analysis provides both a practical and theoretical foundation for professionals who need to understand randomness and variability, its causes and consequences. Students will learn how to design efficient and effective experiments and observational studies in order to answer questions they find interesting. The program works students through important probability models and the underlying mathematics to understand random phenomena. Software is used to analyze data and make effective presentations of results to different audiences. The program is designed for students who have a bachelor’s degree in any field. In addition, a background in mathematics including calculus I, II, III, and linear algebra/matrix methods is required.
Career Opportunities The Advanced Certificate in Data Analysis allows students the opportunity to expand their analytical and presentation skills in this dynamic and growing field, resulting in increased career advancement opportunities. Actuaries, electrical engineers, computer scientists and quality and system engineers all need strong foundations in probability and data analysis and would benefit professionally from this program.
OR
MAT 550 Time Series (3 credits)
Students are required to consult with a faculty member to develop an academic plan.
Admission Guidelines To be considered for admission, all applicants to the Data Analysis program must possess a baccalaureate degree from an accredited university or college with an average of B or better (a GPA of 3.0 on a 4.0 scale). In addition, a background in mathematics including calculus I, II, III, and linear algebra/ matrix methods is required. Applicants not meeting the above admission criteria will be considered on an individual basis. The Application for Graduate Admission and all required forms are available at: www.sunypoly.edu/graduate
Online Learning Online students find it easy to pursue their studies through Angel, our interactive online learning environment. Course lectures, class discussions, assignments and exams are conducted through an easy-to-navigate web tool. This learning option appeals to busy working professionals and others interested in pursuing advanced coursework while juggling multiple life commitments.
The Faculty SUNY Poly faculty work closely with students and challenge them to excel. Many have experience in industry in addition to strong academic credentials. A low student-to-faculty ratio (18:1) means faculty really get to know and work closely with students. Dr. Andrea Dziubek is an Assistant Professor of Applied Mathematics with a Ph.D in Energy and Process Engineering from Berlin University of Technology, Germany. Her research interests include modeling and simulation of problems in biomedical engineering, continuum mechanics, shell theory, structure preserving numerical methods and finite element methods. She loves teaching courses where she can share her academic interests and excitement, such as vector calculus, numerical mathematics, and differential equations. Dr. Edmond Rusjan is an Associate Professor of Applied Mathematics with a PhD in Mathematical Physics from Virginia Tech. His research focus is on geometry and symmetry inspired mathematical models. In particular, he has applied the Boltzmann equation, Lie groups and Lie algebras and Calabi-Yau spaces to solve problems in physics and engineering. He is currently studying the discretization of the Hodge star operator and implications for partial differential equations. Dr. William Thistleton is an Associate Professor of Applied Mathematics, with degrees in Electrical Engineering and Mathematics, and a PhD in Applied Mathematics from SUNY Stony Brook. In addition to his extensive teaching experience in areas including Analysis, Computational Mathematics, and Data Analysis, he has scholarly publications in Probability and Statistics. He consults regularly with industry in a variety of settings. Dr. Zora Thomova is a Professor of Applied Mathematics with PhD in Mathematics from University of Montreal, Canada and MS in Engineering Physics from the Czech Technical University in Prague. She is a recipient of the SUNY Chancellor’s Award for Excellence in teaching; her teaching experience includes mathematics courses at both the undergraduate and graduate level to mathematics and engineering students. She also teaches financial mathematics and fundamentals of derivative markets to MBA students and finance professionals at a major investment institution. She regularly publishes in the area of continuous symmetries of differential and difference equations and has served as an adviser on quantitative projects for financial clients.
“The Advanced Certificate in Data Analysis provides both a practical and theoretical foundation for professionals who need to understand randomness and variability, its causes and consequences.”
SUNY Polytechnic Institute Ranked #2 Top Public School and #2 Best Value College in the U.S. News and World Report’s list of Regional Universities North, SUNY Poly offers a range of popular academic programs, many in fields with increasing demand, taught by caring faculty. The new Center for Advanced Manufacturing (CGAM) gives students 16,000+ sq. ft. of high-tech state-of-the-art space to model, visualize, and test in the world of virtual-to-real manufacturing with a five-axis CNC machining center, industry level 3D printers, prototyping centers, and design studios. Opportunities like CGAM, small class sizes, successful graduates and affordability are all reasons students choose SUNY Poly.
>> FULLY ONLINE PROGRAM Certificate for Advanced Study (Post Bachelor’s)
Data Analysis
For More Information: Graduate Admissions Office State University of New York Polytechnic Institute 100 Seymour Road Utica, NY 13502 315-792-7347 graduate@sunypoly.edu www.sunypoly.edu
Ranked #2 Top Public School and #2 Best Value College: Regional Universities North 12/19
— U.S. News & World Report, 2020