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We're here to help you find itIn this course you will learn about business drivers for AI, the ethical challenges and impacts of AI and Data Science, the business and societal dynamics at work in an AI world, the key principles for building responsible AI, and more. This course introduces some of the principles and frameworks that puts ethics and responsibility into practice in the data analytics profession. And offers practical approaches to technical, business and leadership dilemmas and challenges posed by work in AI and Data Science.
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Koenig Learning Stack
Free Pre-requisite TrainingJoin a free session to assess your readiness for the course. This session will help you understand the course structure and evaluate your current knowledge level to start with confidence.
Assessments (Qubits)Take assessments to measure your progress clearly. Koenig's Qubits assessments identify your strengths and areas for improvement, helping you focus effectively on your learning goals.
Post Training ReportsReceive comprehensive post-training reports summarizing your performance. These reports offer clear feedback and recommendations to help you confidently take the next steps in your learning journey.
Class RecordingsGet access to class recordings anytime. These recordings let you revisit key concepts and ensure you never miss important details, supporting your learning even after class ends.
Free Lab ExtensionsExtend your lab time at no extra cost. With free lab extensions, you get additional practice to sharpen your skills, ensuring thorough understanding and mastery of practical tasks.
Free Revision Classes Join our free revision classes to reinforce your learning. These classes revisit important topics, clarify doubts, and help solidify your understanding for better training outcomes.
Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
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♱ Excluding VAT/GST
You can request classroom training in any city on any date by Requesting More Information
Inclusions in Koenig's Learning Stack may vary as per policies of OEMs
The "Ethics in AI and Data Science (LFS112)" course is designed to be accessible to individuals from various professional backgrounds. However, to ensure a productive learning experience, it is recommended that participants meet the following minimum prerequisites:
These prerequisites are designed to ensure that you can effectively engage with the course material and apply the ethical principles and frameworks discussed to your specific context.
Introduction:
The Ethics in AI and Data Science (LFS112) course equips leaders and data scientists with the knowledge to embed ethical principles in AI and data science for transparency and trust.
Target Audience:
The Ethics in AI and Data Science (LFS112) course aims to equip leaders and data scientists with the knowledge and strategies needed to incorporate ethical principles and frameworks into AI and data science initiatives, focusing on transparency, trust, and responsibility.
