Artificial Intelligence Application (Synchronous E-learning)
About This Course
The Artificial Intelligence Application course is sequenced by order of step-by-step application. Sequencing these steps in the order listed would achieve a comprehensive and effective approach to developing an Artificial Intelligence Application program.
1. LU1: AI applications strengths and limitations.
LO1: Apply fundamental concepts and applications during algorithm analysis and evaluation to AI applications.
2. LU2: Optimizing AI Applications Through Efficient Algorithm Design
LO2: Analyze the efficiency of algorithms taking into consideration of the correlation between design of algorithms and efficiency in AI applications.
3. LU 3: Measuring the Impact of AI: Assessing Performance and Effectiveness
LO3: Evaluate the frameworks and metrics to determine the performance and effectiveness of AI applications.
4. LU 4: Evaluating AI for the Built Environment: Applicability, Feasibility, and Optimization
LO4: Assess the applicability and feasibility improvements in the Built Environment (BE) sector AI applications.
What You'll Learn
Artificial Intelligence has various applications in today's society and is essential to solve complex problems with an efficient way in multiple industries.
As AI continues to evolve and become more advanced, it is important to be equipped with knowledge and hands-on experience with up-to-date technologies that prepare the employees for the future workforce
With sectors becoming more data-driven, learning and development needs of a specific group of individuals from the various industries to integrate Artificial Intelligence into project execution and maintenance processes
To support this transformation, it is essential that employees be trained with specialist skills to understand the current trends and emerging technologies in future possibilities of AI to increase productivity and precision in their process enhancement.
Hence, there is a need for training to enhance the ability of Team Leaders, Managers and owners of SMEs, and organizations to evaluate the effectiveness of AI applications by using appropriate evaluation frameworks and metrics.
Therefore, the need for training is driven by a number of factors, such as automating business processes, gaining insight through data analysis and optimizing internal business operations
In summary here is a need to train Team Leaders, Managers and owners of SMEs, and organizations to apply statistical techniques, programming essentials, and mathematical theories relevant to AI in the organization and to understand the principles of data management for AI applications
Entry Requirements
The basic entry requirements will ensure that learning is pitched at a correct level:
- Basic requirement is GCE 'O' level Credit in English and Mathematics or Workplace Literacy and Numeracy (WPLN) score: Level 6 for Reading, Listening and Numeracy or
- Diploma or Higher Level Diplomas
- Minimum service industrial experience for at least 3 years or have prior experience in similar capacity
- Learners job roles for example, Supervisory, Team Leadership positions are acceptable