What You Will Learn
Data Science is an interdisciplinary study of Computer Science, Statistics, Databases and Domains. This Associate of Science (A.S.) degree program in Computer Science with an option in Data Science ensures you will be prepared to solve today’s pressing technological challenges in every field from health care to entertainment!
- Analyze real-world data using data science principles, processes, implementation and visualization techniques.
- Use your computational thinking skills and practice of fundamental Computer Science topics using object-oriented programming, data structures and algorithms.
- Gain in-demand skills of R, Python, Java, Tableau and SQL and prepare themselves for further study or employment in Data Science.
- Implement industry recognized statistical software to analyze data.
- Gain an understanding of various data types and sources including Application Programming Interfaces (APIs) and database management using Structured Query Language (SQL).
- Build prediction models using machine learning and artificial intelligence.
- Consider the ethical uses of data, privacy, security, and integrity.
Curriculum
The 25-credit core of cutting-edge computer science, computer architecture, mathematics and engineering courses, plus a 35-credit general education foundation to meet the demand of industry. This associate degree program is designed for seamless transfer to a four-year college or university if you choose to do so upon graduation to pursue your bachelor’s degree and beyond.
Careers in the Field
Employment of computer and information research scientists is projected to grow 22 percent by 2030, much faster than the average for all occupations. About 3,200 openings for computer and information research scientists are projected each year.
According to Glassdoor, data scientists are one of the most highly in-demand and sought-after careers worldwide. The starting salary in New Jersey is over 100K for entry-level positions.
- Big Data Engineer
- Business Intelligence Engineer
- Data Analytics Consultant
- Data Architect
- Data Business Analyst
- Data Visualization Developer
- Data Scientist
- Junior Data Support Specialist
- Machine Learning Scientist
- Operations Analyst
- Predictive Analytics Professional
- Project Manager
- Quantitative Analyst
- Report and Analytics Designer
- Report and Analytics Developer
- Statistician
Why Study Data Science at CCM?
There are many reasons why you should study Data Science at CCM:
- CCM’s collaborative, team-based learning environment enables you to complete project-based work with others, analyzing real-world data to solve problems or answer questions.
- Courses are taught by professors with degrees and experience in the field.
- Classes are held in small classrooms equipped with industry-standard software to ensure you graduate with current and relevant skills.
- Flexible terms and class schedules that fit into your busy life.
- Extra-curricular activities such as team competitions and attendance at conferences enable you to extend knowledge and experiences outside of the classroom.
- Be eligible for an internship or entry-level job in the data analytics field.
- Transfer seamless to Ramapo College* or another four-year college or university for a bachelor’s and master’s degree.
- CCM students have successfully transferred to Ramapo College, Columbia University, New Jersey Institute of Technology (NJIT), and the University of Michigan – Ann Arbor, among other leading institutions.
Paying for Your Data Science Education
Earning an associate degree in data science is a powerful investment that will pay off over the course of your life, in both increased earnings and job satisfaction. But what is the upfront cost, and how do you afford it? There’s good news: Money is available to help you pay for school! Our Financial Aid staff can provide lots of information about the process of finding funds to help pay for your education.
Featured Courses
Computer Science I
In this introductory course you can acquire fundamental computer science knowledge and develop programming skills using an object-oriented approach, incorporating security awareness, human-computer interactions and social responsibility.
Introduction to Data Science
Introduction to Data Science will provide students with data literacy skills in order to understand techniques in data manipulation, visualization and interpretation. This project based course will allow students to utilize a toolkit of statistical software to perform data science methods. Ethical issues related to data privacy, authenticity and security will be addressed alongside an introduction to artificial intelligence.
Fundamentals of Programming (Python)
This is a fundamental course in problem solving and programming. This course introduces concepts such as how to solve problems by designing and implementing algorithms using a popular programming language. Topics include: pseudocode, algorithms, variables, constants, using decisions and loop structures to construct effective code, using built-in functions, creating functions and modules, and simple debugging techniques for detecting errors. Use of real-world problems in Web Development, Cybersecurity and Data Science are explored. No prior programming experience is required.
Resources
Colleen Bamford Chairperson / Associate Professor
Email: cbamford@ccm.edu
Office: Emeriti Hall, EH 225
Office hours: Tue 11-12; Wed 1-3
Phone: 973-328-5780
Department: Information Technologies
Nancy Binowski Professor
Email: nbinowski@ccm.edu
Office: Emeriti Hall, EH 221
Office hours: Mon 10-12 (online); Wed 12:30-1, 2:55-3:25
Phone: 973-328-5775
Specialization: Department of Information Technologies consists of Computer Information Systems, Digital Media Technology
Department: Information Technologies
Colleen Carmeli Assistant Professor
Email: ccarmeli@ccm.edu
Office: Emeriti Hall 201
Phone: 973-328-5773
Department: Information Technologies
Al Elbanna Associate Professor
Email: aelbanna@ccm.edu
Office: Emeriti Hall 221
Phone: 973-328-5799
Department: Information Technologies
Dawn Rywalt Associate Professor
Email: drywalt@ccm.edu
Office: CH 276
Office hours: Mon 11-12; Wed 11-12; Fri 11-12
Phone: 973-328-5783
Department: Information Technologies
Vickram Sawh Assistant Professor
Email: vsawh@ccm.edu
Office: Emeriti Hall, EH201
Office hours: Tue 4:50-6:20; Wed 2:30-3:15. 5:00-5:45
Phone: 973-328-5772
Department: Information Technologies
Michael Sidaras-Tirrito Associate Professor
Email: mtirrito@ccm.edu
Office: Emeriti Hall, EH 221
Office hours: Mon 12:15-1:15 (online); Wed 2:00-3:00 (Online); Thur 4:50-5:50
Phone: 973-328-5793
Specialization: Department of Information Technologies consists of Computer Information Systems, Digital Media Technology
Department: Information Technologies
Stephen Stoll Assistant Professor
Email: sstoll@ccm.edu
Office: Emeriti Hall, EH 201
Office hours: Tue 2-3; Wed 11:30-12:30; Fri 11-12
Phone: 973-328-5289
Department: Information Technologies
