Data Science

2 YEARS | ENGLISH TAUGHT | ON CAMPUS

The Data Science Master’s program offers students the advanced technical skills and broader understanding of how Data Science operates in the 21st century. Moreover, students develop necessary research skills so they can design and implement their own research projects to advance the field as a whole. Finally, the program places a high emphasis on preparing students to meet the real-world demands of the private sector by focusing on the skills (both technical and soft) needed to excel in field of data science. The program offers courses in both basic and advanced statistical methods, machine learning, data visualization, data mining, and business analytics. Students will learn computer programming, database management, and writing and other communication skills. With a Masters in Data Science, our graduates find careers in one of the fast-growing industries in the world today.



Elu


AIMS & OBJECTIVES

The importance of data in problem-solving, decision-making, and strategy has gained prominence over the last decade. We live in a world of big data. Many of our everyday actions, from watching videos on our phones to purchasing a product online create data. Since the advent of the technological revolution, data has played an increasingly important role in many fields and spheres of life. That’s why interpreting and understanding data has become such a valuable skill. Data science is the study and examination of data with the purpose of understanding patterns. It uses tools, techniques, and theories to produce a meaningful interpretation of data for decision-making and development. It is an interdisciplinary field of study that uses scientific methods, programming skills, and knowledge of mathematics and statistics to extract insight from data. Degrees in this field allow a diverse range of specializations and occupations.

CURRICULUM

DATA SCIENCE CURRICULUM
First Semester Credits Second Semester Credits
CS 141 Intro to Comp Sci I 4 CS 142 Intro to Comp Sci II 3
MA 131 Calculus I 3 MA 132 Calculus II 3
UNIV 190 Clarkson Seminar 3 MA 200 Math Modelling and Software 3
FY 100 First-Year Seminar 1   Knowledge Area Course 3
  Science Elective 4   Science Elective 4
Total 15 Total 16
Third Semester Credits Fourth Semester Credits
DS 241 Intro to Data Science 3 CS 344 Algorithm and Data Structure 3
IS 314 Database Design and Management 3 IS 415 Data Warehousing for Analytics 3
MA 211 Discrete Math and Proof 3 MA 231 Calculus III 3
STAT 383 Probability and Statistics 3 MA 339 Applied Linear Algebra 3
  Knowledge Area Course 3   Knowledge Area Course 3
Total 15 Total 15
Fifth Semester Credits Sixth Semester Credits
CS 449 Computational Learning 3 DS 392 Ethics of Data Analytics 3
IS 426 Big Data Architecture 3 STAT 382 Mathematical Statistics* 3
STAT 381 Probability 3   Knowledge Area/ University Courses 3
  Knowledge Area/ University Course 3   Free Electives 6
  Free Elective 3      
Total 15 Total 15
Seventh Semester Credits Eighth Semester Credits
MA 499 Professional Experience 0 STAT 384 Advanced Applied Statistics 3
STAT 385 Bayesian Data Analysis 3 STAT 488 Statistics Projects 2
  Application Elective 3   Application Electives 3
  Free Electives 9   Free Electives 6
Total 15 Total 14