Data Analytics Certificate in Data Analytics

Diploma Description

Data is a group of facts that can take many different forms, such as numbers, pictures, words, videos, observations, and more, and is constantly being amassed across industries in order to better understand and solve important issues. Data analytics is the collection, transformation, and organization of these facts in order to draw conclusions, make predictions, and drive informed decision-making. Organizations need data analysts to prepare, process, analyze, and visualize data to discover patterns and trends. Their work empowers their wider team to make better business decisions. See the program outline here.

This program is designed for professionals across disciplines who are seeking to develop the analytical mindset needed to make actionable decisions and strategies by analyzing and interpreting multiple types of data. 

Courses will provide a foundational grounding in statistical analysis, database management, analytic software and tools, and training to communicate findings. Through industry-based electives, participants will be able to apply the skills within a practical context and gain experience with real-world applications.

Program Prerequisite:

Individuals starting the program should possess the following core competencies in Excel:

  • PivotTables
  • Creating basic charts
  • Filtering and sorting data
  • Formulas such as SUM, SUMIF, COUNT, COUNTIF, IF, VLOOKUP

Program Details:

5 Courses Total - View the overview here.

For more information about the Certificate in Data Analytics, please reach out to Michelle D’Amico at michelle.damico@nyu.edu.

Must be completed within

3 years

You'll Walk Away With

  • A foundational grounding in statistical analysis, database management, and analytic software and tools
  • The ability to compile and communicate findings

 

Program Curriculum

COURSES THAT GIVE YOU THE SKILLS AND TRAINING YOU NEED TO START YOUR NEW CAREER

Program Curriculum

COURSES THAT PROVIDE FOUNDATIONAL INFORMATION IN THE FIELD WITH OPTIONS TO SPECIALIZE IN AN AREA RELEVANT TO YOUR NEEDS

REQUIRED COURSES

All Courses Required

Foundational Statistics

This course will provide a practical, hands-on foundation in basic statistics. It will begin by covering the essential concepts and steps to...

2023 Spring
1 section

Introduction to Data Science Methods in R & Python

Gain the foundational knowledge to collect, manipulate, visualize, and analyze common HR data sources using the R and Python programming language.

2023 Spring
1 section

SQL Programming Language

Learn to use SQL to select, update, insert, and delete data from database tables, and acquire hands-on experience with both Oracle and MySQL.

2023 Spring
1 section

DATA VISUALIZATION ELECTIVE - SELECT ONE

Complete 1

Visual Analytics with Tableau

Master the art and science of communicating business-relevant implications of data analyses using Tableau, the industry’s leading software.

2023 Spring
1 section

Data Visualization for Business

Learn to generate, analyze, and communicate data for a specific business-related project.

2023 Spring
1 section

Interactive Data Visualization

Gain the ability to scrape, clean, and process data, as well as to use standalone visualization applications to quickly explore data.

2023 Spring
1 section

INDUSTRY ELECTIVE COURSES - SELECT ONE

Advanced Topics in Real Estate Data Analytics

Gain hands-on experience creating statistical models to drive informed decision-making in real estate investment.

Foundations of Sports Analytics

This course outlines the fundamental principles and key methodologies relevant to sports analytics problems. The course charts the significance...

2023 Spring
1 section

Analytics for Energy Professionals

Explore methods for energy analysis and management and processes to collect and analyze data, and then practice interpreting and utilizing it.

2023 Spring
1 section

Data Analytics for Public Policy and Social Good

Typically associated with business and tech, analytics is quickly being adopted as a vital tool for government and nonprofit organizations to...

2023 Spring
1 section

Data Mining, Predictive Analytics, and Big Data

Gain an overview of the collection, analysis, and visualization of complex data, as well as the relevant pivotal concepts.

2023 Spring
1 section

Fundamentals of People Analytics

Beginning with fundamentals, identify human capital issues in the workplace and learn to apply metrics that can yield insights into the workforce.

2023 Spring
1 section

General Admission Requirements

For those who have completed some college Completion of 32 credits with at least 2 years work experience OR 60 credits with no work experience required