Certificate in Advanced Data Science and Predictive Analytics

As organizations gather more and more data from their business processes, traditional computer systems and tools cannot handle the massive volume of data. Distributive computing platforms and tools are needed to digest, store and retrieve data. This course looks at distributive tools for data analysis, machine learning, data digestion and visualization. These tools are employed in real world examples to find trends and make informed business decisions.

4 Classes

36 Hours

Schedule

May 26 to July 20, 2025

Classes Bi-Weekly Wed 6:45 PM-9:45 PM (28 May 2025 to 09 Jul 2025)

Discover the complete process of building prediction functions, including complex data collection, feature creation, applying advanced algorithms, evaluation and deploying models as an app in this advanced course. A range of machine learning model based and algorithmic machine learning methods will be introduced. You’ll also learn how to apply learning algorithms to mining social media and network (sentiment, influence), text understanding (web search, anti-spam), association rule mining (recommender systems), time series analysis, and other areas.

4 Classes

36 Hours

Schedule

July 21 to September 14, 2025

Classes Bi-Weekly Wed 6:45 PM-9:45 PM (23 Jul 2025 to 03 Sep 2025)

Exercise the skills acquired in the previous courses as you work end-to-end on an analytics project. Students have an opportunity to select to either work: a) with a business on a sponsored project, or b) independently on their own project. This hands-on course requires defining the business problem, scoping out the project, review and preparing of collected data, as well as integrating, modelling and analyzing the data. Students are expected to also derive insights and offer recommendations based on their analysis.

4 Classes

36 Hours

Schedule

September 15 to November 09, 2025

Classes Bi-Weekly Wed 6:45 PM-9:45 PM (17 Sep 2025 to 29 Oct 2025)

As organizations gather more and more data from their business processes, traditional computer systems and tools cannot handle the massive volume of data. Distributive computing platforms and tools are needed to digest, store and retrieve data. This course looks at distributive tools for data analysis, machine learning, data digestion and visualization. These tools are employed in real world examples to find trends and make informed business decisions.

4 Classes

36 Hours

Schedule

September 22 to November 23, 2025

Classes Sat 9:30 AM-12:30 PM (27 Sep 2025); Bi-Weekly Sat 9:30 AM-12:30 PM (18 Oct 2025 to 15 Nov 2025)

Discover the complete process of building prediction functions, including complex data collection, feature creation, applying advanced algorithms, evaluation and deploying models as an app in this advanced course. A range of machine learning model based and algorithmic machine learning methods will be introduced. You’ll also learn how to apply learning algorithms to mining social media and network (sentiment, influence), text understanding (web search, anti-spam), association rule mining (recommender systems), time series analysis, and other areas.

4 Classes

36 Hours

Schedule

November 24, 2025 to February 01, 2026

Classes Bi-Weekly Sat 9:30 AM-12:30 PM (29 Nov 2025 to 13 Dec 2025); Bi-Weekly Sat 9:30 AM-12:30 PM (10 Jan 2026 to 24 Jan 2026)

Exercise the skills acquired in the previous courses as you work end-to-end on an analytics project. Students have an opportunity to select to either work: a) with a business on a sponsored project, or b) independently on their own project. This hands-on course requires defining the business problem, scoping out the project, review and preparing of collected data, as well as integrating, modelling and analyzing the data. Students are expected to also derive insights and offer recommendations based on their analysis.

4 Classes

36 Hours

Schedule

February 02 to March 29, 2026

Classes Bi-Weekly Sat 9:30 AM-12:30 PM (07 Feb 2026 to 21 Mar 2026)

As organizations gather more and more data from their business processes, traditional computer systems and tools cannot handle the massive volume of data. Distributive computing platforms and tools are needed to digest, store and retrieve data. This course looks at distributive tools for data analysis, machine learning, data digestion and visualization. These tools are employed in real world examples to find trends and make informed business decisions.

4 Classes

36 Hours

Schedule

May 25 to July 19, 2026

Classes Bi-Weekly Wed 6:45 PM-9:45 PM (27 May 2026 to 08 Jul 2026)

Discover the complete process of building prediction functions, including complex data collection, feature creation, applying advanced algorithms, evaluation and deploying models as an app in this advanced course. A range of machine learning model based and algorithmic machine learning methods will be introduced. You’ll also learn how to apply learning algorithms to mining social media and network (sentiment, influence), text understanding (web search, anti-spam), association rule mining (recommender systems), time series analysis, and other areas.

4 Classes

36 Hours

Schedule

July 20 to September 13, 2026

Classes Bi-Weekly Wed 6:45 PM-9:45 PM (22 Jul 2026 to 02 Sep 2026)

Exercise the skills acquired in the previous courses as you work end-to-end on an analytics project. Students have an opportunity to select to either work: a) with a business on a sponsored project, or b) independently on their own project. This hands-on course requires defining the business problem, scoping out the project, review and preparing of collected data, as well as integrating, modelling and analyzing the data. Students are expected to also derive insights and offer recommendations based on their analysis.

4 Classes

36 Hours

Schedule

September 14 to November 08, 2026

Classes Bi-Weekly Wed 6:45 PM-9:45 PM (16 Sep 2026 to 28 Oct 2026)