Business Analytics Methods | CU Online

Overview

Prepare for a competitive career in the exciting field of big data by earning a graduate certificate in Business Analytics Methods online from the Leeds School of Business. Our four-course, fully online certificate program is designed to teach you how to interpret and utilize data to make business decisions that can make a positive impact in the world.

Completing this certificate will give you the skills to find a job or expand your career as an analyst in many positions, including business intelligence, marketing, accounting, human resource management, and more.

Program at a Glance

Degree Program:

Business Analytics Methods Certificate

Offered By:

Tuition:

For tuition information, please contact our CU Online Enrollment Team at 303-860-5604.

Application Deadline:

August 23, 2022

Credit Hours:

12

Turn a Professional Certificate into a Master’s Degree

If you’re interested in returning to school after some time, a graduate certificate is a great way to get started and immediately access knowledge that can be applied to your everyday life. A certificate also allows you to quickly demonstrate proficiencies to employers while adding value to your resume.

The Leeds School of Business provides the option to begin with a certificate en route to completing the master’s program, further progressing your knowledge of and marketability in the field. All you need to do is apply for your master’s degree before the end of your third class, and you’ll already be well on your way to developing an in-demand toolkit to enhance your career.

AACSB Accreditation

The CU Denver Business School is accredited by AACSB International, a global nonprofit association that is committed to providing excellence in education for future business leaders. This accreditation represents the highest standard of achievement for business schools, with less than five percent of the world’s business programs obtaining AACSB accreditation. As an AACSB accredited degree, our online MBA program must meet rigorous academic standards and commit to providing high-quality education through strategic curriculum design and dynamic thought leadership. When you earn your MBA from an AACSB accredited program, you’ll graduate with the confidence that you’ve received the best business education available and the valued credentials that employers are looking for.

Timeline

The graduate certificate in Business Analytics Methods is a four-course, 12 credit-hour program that allows you to specialize in the interpretation of business data.

Admissions

Admission requirements and deadlines vary based on the program. Learn more about the admissions process by filling out the form above or contacting an Enrollment Navigator today.

Admissions Requirements

Online Application
Statement of Purpose (1-2 pages)
Transcript showing completion of an undergraduate degree
Current resume
One letter of recommendation

Required Courses
MSBC 5030 — Quantitative Methods Covers foundations for statistical reasoning and statistical applications in business. Topics include graduate-level treatment of descriptive statistics, probability, probability distributions, sampling theory and sampling distributions, and statistical inference (estimation and hypothesis testing). Provides an introduction to regression analysis, analysis of variance, time series forecasting, decision analysis, index numbers, and nonparametric methods. Heavy use of R programming in course execution.
MSBX 5405 — Structured Data Modeling & Analysis Explores both the functional and technical environment for the creation, storage, and use of the most prevalent source and type of data for business analysis, ERP and related structured data. Students will learn how to access and leverage information via SQL for analysis, aggregation to visualization, create dashboards, and be a source for business intelligence.
MSBX 5420 — Unstructured & Distributed Data Modeling & Analysis Moves the student beyond structured data and sources into business scenarios where data is semi-structured to unstructured such as those from social and web applications. Specific topics include an introduction to SQL-on-Hadoop, NoSQL and related distributed processing technologies. Students will learn practical applications and mechanisms for getting this sort of data ready for analytics.
MSBX 5415 — Advanced Data Analytics Explores the capabilities and challenges of data-driven business decision making and prepares students to lead in analytics-driven organizations. Introduces a set of common predictive and prescriptive analytics tools. Students apply analytics tools to important decisions based on practical data sets. from various companies. Analytics software packages are used extensively in the course.

Required Courses

MSBC 5030 — Quantitative Methods

Covers foundations for statistical reasoning and statistical applications in business. Topics include graduate-level treatment of descriptive statistics, probability, probability distributions, sampling theory and sampling distributions, and statistical inference (estimation and hypothesis testing). Provides an introduction to regression analysis, analysis of variance, time series forecasting, decision analysis, index numbers, and nonparametric methods. Heavy use of R programming in course execution.

MSBX 5405 — Structured Data Modeling & Analysis

Explores both the functional and technical environment for the creation, storage, and use of the most prevalent source and type of data for business analysis, ERP and related structured data. Students will learn how to access and leverage information via SQL for analysis, aggregation to visualization, create dashboards, and be a source for business intelligence.

MSBX 5420 — Unstructured & Distributed Data Modeling & Analysis

Moves the student beyond structured data and sources into business scenarios where data is semi-structured to unstructured such as those from social and web applications. Specific topics include an introduction to SQL-on-Hadoop, NoSQL and related distributed processing technologies. Students will learn practical applications and mechanisms for getting this sort of data ready for analytics.

MSBX 5415 — Advanced Data Analytics

Explores the capabilities and challenges of data-driven business decision making and prepares students to lead in analytics-driven organizations. Introduces a set of common predictive and prescriptive analytics tools. Students apply analytics tools to important decisions based on practical data sets. from various companies. Analytics software packages are used extensively in the course.