Accounting and Financial Analytics Advanced Certificate

In RIT’s accounting analytics certificate you’ll complete advanced financial analytics courses that equip you with the knowledge and tools to mine and analyze data that impacts financial strategy.


Overview

Today's accounting and finance professionals are now expected to serve as business partners and experts who can use data analytics to inform recommendations on business strategy. RIT’s accounting analytics certificate provides you with knowledge in data science and statistical analysis so that you–as an accounting and finance professional–can mine and analyze data to apply it in ways that benefit and improve business operations and outcomes.

Advanced Financial Analytics Courses

The accounting analytics certificate provides you with the skills you need to operate effectively in today’s modern data-centric business environment. A selection of advanced financial analytics courses will help you learn how to access, interpret, analyze, and report business and financial data. Courses completed in the certificate program can be applied later to RIT’s master’s degree in business analytics, or they may be used as a valuable add-on for students pursuing graduate degrees from RIT in fields such as finance, accounting and analytics, applied statistics, and computer science.

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. Graduate certificates can serve as a stand-alone credential that provides expertise in a specific topic that enhances your professional knowledge base, or they 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 also offered online. View Online Option.

Curriculum for Accounting and Financial Analytics Adv. Cert.

Accounting and Financial Analytics, advanced certificate, typical course sequence

Course Sem. Cr. Hrs.
First Year
ACCT-745
Accounting Information and Analytics
The objective for this course is helping students develop a data mindset which prepare them to interact with data scientists from an accountant perspective. This course enables students to develop analytics skills to conduct descriptive, diagnostic, predictive, and prescriptive analysis for accounting information. This course focuses on such topics as data modeling, relational databases, blockchain, visualization, unstructured data, web scraping, and data extraction. (Prerequisites: ACCT-110 or ACCT-603 or equivalent course.) Lecture 3 (Fall, Summer).
3
FINC-780
Financial Analytics
This course provides a survey of financial analytics applications in contexts such as investment analysis, portfolio construction, risk management, and security valuation. Students are introduced to financial models used in these applications and their implementation using popular languages such as R, Matlab, and Python, and packages such as Quantlib. A variety of data sources are used: financial websites such as www.finance.yahoo.com, government sites such as www.sec.gov, finance research databases such as WRDS, and especially Bloomberg terminals. Students will complete projects using real-world data and make effective use of visualization methods in reporting results. There are no pre or co-requisites; however, instructor permission is required – student aptitude for quantitative work will be assessed; waived for students enrolled in quantitative programs such as the MS-Computational Finance which have pre-requisites in the areas of calculus, linear algebra, and programming. Lecture 3 (Fall).
3
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).
3
Choose one of the following:
3
   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).
 
   MGIS-725
   Data Management and Analytics
This course discusses issues associated with data capture, organization, storage, extraction, and modeling for planned and ad hoc reporting. Enables student to model data by developing conceptual and semantic data models. Techniques taught for managing the design and development of large database systems including logical data models, concurrent processing, data distributions, database administration, data warehousing, data cleansing, and data mining. Lecture 3 (Spring).
 
Total Semester Credit Hours
12

Admission Requirements

To be considered for admission to the advanced certificate in accounting and financial analytics, candidates must fulfill the following requirements:

  • Complete an online graduate application. Refer to Graduate Admission Deadlines and Requirements for information on application deadlines, entry terms, and more.
  • 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.
  • Recommended minimum cumulative GPA of 3.0 (or equivalent).
  • Submit a current resume or curriculum vitae.
  • Letters of recommendation are optional.
  • Not all programs require the submission of scores from entrance exams (GMAT or GRE). Please refer to the Graduate Admission Deadlines and Requirements page for more information.
  • Submit a personal statement of educational objectives. Refer to Application Instructions and Requirements for additional information.
  • International applicants whose native language is not English must submit official test scores from the TOEFL, IELTS, or PTE. Students below the minimum requirement may be considered for conditional admission. Refer to Graduate Admission Deadlines and Requirements for additional information on English requirements. International applicants may be considered for an English test requirement waiver. Refer to Additional Requirements for International Applicants to review waiver eligibility.

Learn about admissions, cost, and financial aid 

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