DATA VISUALIZATION & CLOUD TECHNOLOGIES

Name: DATA VISUALIZATION & CLOUD TECHNOLOGIES
Availability: OutOfStock
Rating: 4.9 (130 reviews)

GENBUS 883

과목 설명

Provides experience in data visualization and cloud technologies to support business analytics. Create and share compelling data visualizations to enhance decision making. Use cloud technologies to build scalable data warehouses, analyze big data, and develop and deploy machine learning models.

선수과목

Graduate/professional standing or declared in graduate Business Exchange program. Not open to students with credit for GENBUS 720 or GENBUS 780 .

충족 요건

GENBUS 891 , GENBUS 894 , GENBUS 884 , and GENBUS 746

학점

미보고

개설 시기

미보고

평점

3.9

-0.33% 과거 데이터 대비

수료율

100%

과거 데이터 대비 변화 없음

A 비율

87.8%

1.01% 과거 데이터 대비

학급 규모

26.15% 과거 데이터 대비

Cumulative Grade Distribution

강사 (2026 Summr)

다음 사이트의 평점순으로 정렬 Rate My Professors

유사 과목

CLOUD TECHNOLOGY FOR BUSINESS ANALYTICS

GENBUS 780

Provides an overview of cloud services that support business analytics. Load and analyze data, build and deploy machine learning models, and develop data pipelines through hands-on, in-class activities working in cloud environments.

DATA TECHNOLOGY FOR BUSINESS ANALYTICS

GENBUS 760

Focuses on various technologies needed to perform data analytics. Techniques of extracting structured and unstructured data from databases, applications, or social networks. Transform and combine data with other relevant information and load into targeted systems. How to use programming languages to collect data from the web and leverage libraries for other, more, advanced data analysis.

APPLIED ANALYTICS - CASE STUDIES

GENBUS 884

Project-based applications of statistics, programming, data visualization, and database management.

CLOUD ANALYTICS AND ARTIFICIAL INTELLIGENCE TOOLS FOR BUSINESS

GENBUS 308

Apply statistics and data literacy to business problems using popular analytics and artificial intelligence tools in the cloud.

DATA VISUALIZATION FOR BUSINESS ANALYTICS

GENBUS 720

Introduce students to principles of data visualization and provide hands-on experience using data visualization tools and techniques for business applications. Develop proficiency in current visualization software tools, and leverage these tools for data exploration, insight into decision-making, and data presentation. Recommended for students to have general computing skills and familiarity with MS Word, MS Excel and MS PowerPoint; introductory-level exposure to coding in any language; some R experience; basic statistical literacy, equivalent to at least one semester of statistics.