Certificate in Advanced Data Science and Predictive Analytics
Description
Integrate advanced skills in data science with your leadership abilities to target organizational growth through data analytics.
What you will learn
In the part-time Certificate in Advanced Data Science and Predictive Analytics, you’ll explore the building blocks of data analytics through an organizational lens. This program will allow you to:
- Explore relevant data analytics tools and advanced methods for data analysis
- Prepare to lead an organization and data science team through collecting, analyzing, and communicating data insights
- Demonstrate how data supports business decisions
- Apply your knowledge with a hands-on capstone course that includes analyzing real-life scenarios
Program Benefits
- Designed in collaboration with data science and business leaders across several sectors
- Learn from practicing data analytics instructors
- Complete experiential learning activities, including an end-to-end analytics project with a business, giving you hands-on experience
- Option to complete an independent project or start-up venture
- Advance through the program with the same peer cohort and build your professional network
To earn the York University Certificate in Certificate in Advanced Data Science and Predictive Analytics, you will successfully complete all three courses.
CSDA2000 Big Data Management and Tools
CSDA2010 Advanced Methods of Data Analysis for Management
CSDA2020 Advanced Analytics Capstone
Note: Check with the institution regarding start/end dates, prices, and delivery method. These may vary according to program, section, and/or semester.
Overview
- Institution: York University
- Program type: Certificat
- Language: English
- Program Code: PR0007
- Delivery Method: Entièrement en ligne/à distance
Disclaimer:
Check with the institution regarding start/end dates, prices, and delivery method. These may vary according to program, section, and/or semester.
Check with the institution regarding start/end dates, prices, and delivery method. These may vary according to program, section, and/or semester.