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Explore how AI-driven automation enhances efficiency, reduces manual tasks, and enables intelligent decision-making. Learn to design, implement, and optimize AI-based automation, transforming workflows with advanced Python and AI techniques.
No pre-requisite. Suitable for everyone, regardless of prior technology experience.
Who Should Attend
Senior Managers, Business Unit Leaders, IT Professionals, Process Engineers, Project Managers, Product Owners, Operation Professional, Software Engineer, Software Developers, Data Scientists, Data Analysts, and Anyone interested in Automation with Artificial Intelligence.
In this module, Learners have the opportunity to acquire knowledge on the foundational techniques for handling data in AI automation. Explore data sourcing, cleaning, and preprocessing methods, ensuring high-quality inputs for AI models.
Deep dive into optimizing data handling for AI-driven automation. Learners will gain first-hand experience on data quality checks, validation, and improving data consistency to ensure efficient data access, management, and scalability for AI models and automation systems.
Acquire essential knowledge of SEM concepts, practical application using Google Ads, and the creation of standard search campaigns.
Learn to construct and train machine learning models using Python, covering techniques like supervised and unsupervised learning. Acquire practical skills in model development, including data preparation, training, validation, and evaluating model performance for effective automation solutions.
In this module, learners will gain a deep understanding on how to measure performance using key metrics such as accuracy, precision, and recall. Learners will also have the opportunity to explore evaluation techniques like cross-validation and A/B testing, and discusses methods for continuous monitoring and optimization to ensure automation solutions achieve desired outcomes and adapt to evolving needs.
Explores methods like hyperparameter tuning, model refinement, and techniques for reducing overfitting and underfitting and to enhance the performance of AI models. Learn how to ensure that AI models deliver high accuracy and robust performance in automation scenarios.
This course involves extensive practical/hands-on exercises, rigorous usage of real-time case studies, role-playing and group discussion
Upon completion of the course, participants are required to attempt an examination. This exam tests a candidate’s knowledge and skills related to Digital Transformation, based on the syllabus covered.
Participants are expected to score a minimum of 70% to pass the examination
Add Value to your prolific portfolio a Certificate of Competency from CASUGOL.
All certificates issued by CASUGOL are to individuals who have successfully completed CASUGOL Certification Programs / Executive Workshops and have fulfilled all requirements by demonstrating proficiency in applying the knowledge and skills acquired.
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Their contribution as an Academic Partner / Contributor and active participation in our International Advisory Committee (IAC) shapes the designing of our programs to incorporate the latest research findings on frontier technologies.
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