Certificate of Advanced Study (CAS)
in Data Science Program

Earn Your Certificate of Advanced Study in Data Science at iSchool

The Certificate of Advanced Study in Data Science offered by the Syracuse University School of Information Studies is a 15-credit program that combines core skills in database management and data science with electives like machine learning and data visualization.

With our Data Science certificate program, you’ll gain the theoretical background and technical skills needed to give you a competitive edge in any industry.

  • Customizable electives in cutting-edge topics like machine learning, NLP, and data visualization.
  • Practical, real-world applications emphasized across courses.
  • Access to faculty and resources from a leading information school.
  • Opportunities to network with professionals across diverse industries like healthcare, finance, and defense.
Program Info
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Next term starts: 

Spring 2025

15

Total Credit Hours

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Program Delivery: 

On-campus

5

Courses

 
Admissions Requirements

  1. Complete the Graduate Program Application – Submit your application through the Graduate Program Application portal.
    After submission, you’ll receive an email confirmation from Syracuse University.
  2. Pay the Application Fee  – A non-refundable fee of $75 is required. If you’re applying to multiple programs, each requires a separate application and fee.
    Post-9/11 veterans may qualify for a fee waiver; contact the Veterans Resource Center at veterans@syr.edu for details.
  3. Submit Academic Transcripts – Provide one copy of transcripts from all postsecondary institutions you’ve attended. While unofficial transcripts are acceptable for initial review, official transcripts confirming a U.S. bachelor’s degree (or equivalent) are necessary upon admission.
  4. Write a Personal Statement – In approximately 500 words, discuss your academic and personal interests, relevant experiences, reasons for choosing this degree and Syracuse University, and your future plans post-graduation.
  5. Obtain One Letter of Recommendation – Request one letter from individuals who can assess your qualifications.
  6. Consider Exam Scores – Submitting GRE scores is optional.

Provide a Current Resume or Curriculum Vitae (CV) – Include an up-to-date resume or CV with your application.

 
Program Learning Outcomes

  • Manage, query, and optimize databases effectively to support data-driven projects.
  • Apply advanced data analysis techniques, including machine learning and natural language processing.
  • Design and implement data visualization strategies to communicate insights clearly.
  • Apply ethics in the development, use, and evaluation of data and predictive models (e.g., fairness, bias, transparency, privacy)
 
How to Apply

  1. Gather Required Documents
  2. Complete the Graduate Program Application:
    • Visit the Graduate Program Application portal on the Syracuse University website.
    • Create an account and fill out your personal information, educational background, and program-specific details.
  3. Submit Supporting Documents
  4. Pay the Application Fee
  5. Track Your Application

Contact the Enrollment Management team at iGrad@syr.edu with further questions or for assistance. A member of our team will be happy to assist you.

We look forward to receiving your application!

 

What Can You Do with a CAS in Data Science?

A Certificate of Advanced Study in Data Science opens doors to diverse career opportunities by equipping students with in-demand data skills.

Graduates of our program can pursue roles such as:

  • Data Scientist
  • Data Analyst
  • Machine Learning Engineer
  • Business Intelligence Analyst
  • Database Administrator
  • Data Engineer
  • AI Specialist
  • Analytics Consultant

Courses & Curriculum

This certificate requires 15 graduate credits. All courses are 3 graduate credits unless specified otherwise.

View Full Course Catalog

Primary Core – 6 credits

IST 659 | 3 CREDITS
Definition, development, and management of databases for information systems. Learn data analysis techniques, data modeling, data normalization query writing for information retrieval and query performance tuning using the SQL language.

IST 687 | 3 CREDITS
Introduction to using data science across many different situations. Covers concepts such as data management, transformation, analysis, and machine learning, using R. No programming experience required. Hands-on projects and real-world problem-solving help identify when data science is useful, with emphasis on ethically applying data science.

Electives – 9 credits

Students need to choose three classes from the list of electives below

IST 644 | 3 CREDITS
Increase the agility of a data science project by improving the process a team uses to execute their project. Explore data science life cycles (e.g., CRISP-DM, TDSP) and collaboration frameworks (e.g., Kanban, Scrum).

IST 652 | 3 CREDITS
Introduction to scripting techniques for automating, managing, and analyzing data in various formats. The course focuses on practical applications of Python to preprocess, clean, analyze, and visualize data to support data-driven decision-making and the creation of data analysis pipelines.

IST 664 | 3 CREDITS
Crosslisted with CIS 668
Linguistic and computational aspect of natural language processing technologies. Lectures, readings, and projects in the computational techniques required to perform all levels of linguistic processing of text. Additional work required of graduate students.

IST 681| 3 CREDITS
Introduces metadata concepts, models, encoding, vocabulary, interoperability, and quality control as well as new development and trends. Students will apply metadata principles, tools, and best practices in creating metadata descriptions and models  using established standards.
PREREQ IST 659

IST 686 | 3 CREDITS
Multiple strategies for inferential reasoning about quantitative data. Methods for connecting data provenance to substantive analytical conclusions.

IST 691 | 3 CREDITS
An introduction to the concepts and techniques needed to build deep learning applications. Gain hands-on experience training neural networks using open-source tools (Python, Tensorflow/Keras). The course culminates in a project applying deep learning methods to real-world challenges.

PREREQ IST 687 OR IST 387 (B grade or higher)

IST 692 | 3 CREDITS
Through hands-on coding exercises and critical analysis, you’ll learn to identify and address biases in AI systems, evaluate the social and environmental impact of AI, navigate AI regulations, and apply best practices for responsible AI design and deployment.
PREREQ IST687 OR IST387 (B grade or higher)

IST 707 | 3 CREDITS
Provides a comprehensive overview of industry standard machine learning techniques, including an introduction to deep learning. Focus on model building and optimization in Python, real-world applications, and stakeholder communication. Students will apply their skills to an original machine learning project to showcase their skills.
PREREQ IST 687, OR IST 387 with a minimum grade of B or higher

IST 718 | 3 CREDITS
Learn to develop actionable insights from big data using open-source tools (Python and Spark). This course prepares students to build scalable data analytics pipelines and apply advanced machine learning techniques, culminating in a hands-on project tackling real-world challenges.

PREREQ IST687 & IST707, or IST387 & IST407 (B grade or higher)

Electives – 9 credits (continued)

IST 719 | 3 CREDITS
A broad introduction to data visualization for information professionals. Students will develop a portfolio of resources, demonstrations, recipes, and examples of various data visualization techniques.
PREREQ IST 687, OR IST 387 with a minimum grade of B or higher

IST 722 | 3 CREDITS
Introduction to the concepts of data warehousing and business intelligence (BI). Data warehouse architectures and design. Dimensional modeling, extract-load-transform (ELT) in the SQL language. Emphasis on using data warehouses to make better organizational decisions.

PREREQ IST 659 OR IST 359 with a minimum grade of B or higher

IST 736 | 3 CREDITS
Introduces concepts and methods for knowledge discovery from large amount of text data, and the application of text mining techniques for business intelligence, digital humanities, and social behavior analysis

IST 737 | 3 CREDITS
Analytic dashboards find valuable insights from large scale data. Students will gain knowledge of human visual reasoning, and obtain technical skills necessary to design, develop and implement analytic dashboards for business, government, or personal data.

IST 769 | 3 CREDITS
Double Numbered with IST 469
Analyze relational and non-relational databases and corresponding database management system architectures. Learn to build complex database objects to support a variety of needs from big data and traditional perspectives. Data systems performance, scalability, security. Additional work required for graduate students.
PREREQ IST 659 OR IST 359 with a minimum grade of B or higher

MBC 638 | 3 CREDITS
Concepts, principles and methods to support scientific approach to managerial problem solving and process improvement. Basic statistical techniques, their appropriateness to situations and assumptions underlying their use.

SCM 651 | 3 CREDITS
Scripting methods, languages, tools and theory for the efficient and effective management of resources and services in enterprise data systems.

Frequently Asked Questions

Is a Certificate of Advanced Study (CAS) a degree?

No, a CAS is not a degree. It is a specialized credential that signifies advanced training in a specific field.

Is an advanced certificate the same as a Master’s degree?

No, an advanced certificate focuses on specific skills and is shorter than a full Master’s program.

Can you become a data scientist with just a Certificate (CAS) in Data Science?

Yes, a CAS in Data Science can help qualify you for entry-level roles, depending on your background.

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