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 15 to July 09, 2024

Classes Bi-Weekly Wed 6:45 PM-9:45 PM (22 May 2024 to 03 Jul 2024)

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 10 to September 03, 2024

Classes Bi-Weekly Wed 6:45 PM-9:45 PM (17 Jul 2024 to 28 Aug 2024)

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 04 to October 29, 2024

Classes Bi-Weekly Wed 6:45 PM-9:45 PM (11 Sep 2024 to 23 Oct 2024)

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 24 to November 18, 2024

Classes Bi-Weekly Tue 6:45 PM-9:45 PM (01 Oct 2024 to 12 Nov 2024)

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 19, 2024 to January 27, 2025

Classes Bi-Weekly Tue 6:45 PM-9:45 PM (26 Nov 2024 to 10 Dec 2024); Bi-Weekly Tue 6:45 PM-9:45 PM (07 Jan 2025 to 21 Jan 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

January 28 to March 24, 2025

Classes Bi-Weekly Tue 6:45 PM-9:45 PM (04 Feb 2025 to 18 Mar 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

May 14 to July 08, 2025

Classes Bi-Weekly Wed 6:45 PM-9:45 PM (21 May 2025 to 02 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 09 to September 02, 2025

Classes Bi-Weekly Wed 6:45 PM-9:45 PM (16 Jul 2025 to 27 Aug 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 03 to October 28, 2025

Classes Bi-Weekly Wed 6:45 PM-9:45 PM (10 Sep 2025 to 22 Oct 2025)