Certificate in Big Data Analytics

Description

Leverage data-driven insights to help your organization keep pace with industry trends and stay competitive.

What you will learn
 
Featuring two learning formats—blended or intensive—our part-time Certificate in Big Data Analytics will help you develop expertise across the data analytics lifecycle. This program will help you:
  • Develop an up-to-date understanding of contemporary data analytics
  • Work with industry-standard data analytics software applications
  • Learn data analytics foundations, basic and advanced methods for analysis, and relevant tool sets
Program Benefits
  • Curriculum created in collaboration with data science leaders across several sectors
  • Learn from practicing data analytics instructors
  • Advance through the program with the same peer cohort and build your professional network
The Big Data Analytics Program also allows you to earn one or two distinct certificates to get an edge over your competition. You can choose to enrol only in the initial certificate or in both certificates as a bundle to complete the full program.
 
Certificate in Big Data Analytics (6 months)
Suitable for individuals who want to acquire foundational knowledge of data analytics and apply it to their core industry such as business, finance, IT or marketing.

Certificate in Advanced Data Science and Predictive Analytics (6 months)
Build on the initial certificate to further develop the skills required to pursue a career in the field of Data Analytics.
 
To earn the York University Certificate in Big Data Analytics, you will successfully complete all three courses.
 
CSDA1100  Data Analytics for Business
CSDA1110  Introduction to Data Science
CSDA1120  Accessing Data for Analysis
 
 

Overview

York University logo
  • Institution: York University
  • Program type: Certificat
  • Language: English
  • Program Code: PR0005
  • Delivery Method: Entièrement en ligne/à distance

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Disclaimer:
Check with the institution regarding start/end dates, prices, and delivery method. These may vary according to program, section, and/or semester.