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Your Learner Verification

This is to verify that James Mangunza has completed the course Machine Learning with Artificial Intelligence on Alison.

James Mangunza

Alison ID: 22329668

Course Completed: Machine Learning with Artificial Intelligence

Date of Completion: 7th July 2026

Email: [email protected]

Total Study Time: 4h 20m

Final Assessment Score:

Alison courses requires at least
80% to pass the final assessment

88%
CPD Hours Completed:

CPD approved learning hours
completed through this course

3-5h

Course Information

This free online course on Alison takes you through the rudiments and fundamentals of artificial intelligence.

This course begins by explaining the thoughts and ideas that have influenced the growth of artificial intelligence. You will learn about the definition of artificial intelligence and the different dimensions of artificial intelligence. You will learn about the differences between artificial intelligence, programming and general computational paradigms. You will also learn about production systems and how they capture the essence of artificial intelligence systems.

The course then explains the meaning and types of various search techniques used in solving problems. You will learn about how heuristic functions are formulated. You will learn about the integral role games play in the development of artificial intelligence. You will also learn about how knowledge representation in reasoning forms the backbone of any intelligent behaviour through computational means.

The course then explains resolution as an important rule of inference used in well formed formulas in knowledge representations. You will be introduced to planning in its abstract form, and how it can be used in problem solving. You will also learn how machine learning addresses the fundamental question of how to build computer programs that could learn automatically from experience.

Prerequisites; Learners will need good knowledge and ability in programming in order to study this course.

Modules Completed

Module 1: Reasoning Under Uncertainty
Module 2: Planning
Module 3: Course assessment

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