Certified - Advanced AI Audio Course

<p>This episode explores the realities of working with AI vendors, a critical skill as few organizations build every component in-house. Vendor relationships require careful evaluation of offerings, service-level...

<p>This episode focuses on embedding ethics into AI development through practical guardrails. While high-level principles such as fairness and accountability provide guidance, practitioners need concrete methods to...

<p>This episode examines AI agents, which extend models beyond text generation into action. Agents use planning and tool integration to execute tasks on behalf of users, such as querying databases, calling APIs, or...

<p>This episode explores edge and on-device AI, where models run locally on hardware rather than in centralized cloud servers. Edge AI provides advantages in privacy, since data remains on the device; latency, because...

<p>This episode addresses the unique challenges of deploying AI in safety-critical sectors such as healthcare and finance. In these domains, errors can cause significant harm, from misdiagnosis in medicine to systemic...

<p>This episode explores the growing role of AI in cybersecurity, where the scale and speed of modern threats demand advanced detection and automation. AI techniques support intrusion detection, malware classification...

<p>This episode addresses AI in operations and IT, focusing on forecasting and anomaly detection. Forecasting uses historical patterns to predict future values, such as demand or resource usage. Anomaly detection...

<p>This episode explores how AI transforms marketing and sales functions through personalization and scoring. Personalization involves tailoring recommendations, messages, or offers based on customer data. Scoring...

<p>This episode examines AI in customer support, one of the most common enterprise applications. Chatbots and virtual agents handle routine inquiries, while escalation paths route complex cases to human representatives...

<p>This episode explores the organizational roles necessary for building and sustaining AI systems. Teams often include data scientists, data engineers, machine learning engineers, product managers, ethicists, and...

<p>This episode examines change management in the context of AI adoption. AI systems are not just technical tools but organizational shifts, and their success depends heavily on how teams accept and integrate them...

<p>This episode addresses the critical task of evaluating AI systems beyond raw performance metrics. While accuracy and loss functions matter during development, organizations ultimately need to measure value — the...

<p>This episode covers the legal and policy environment surrounding AI, an area increasingly tested in certification exams. Copyright concerns arise when models are trained on copyrighted material, raising questions...

<p>This episode introduces the security challenges unique to artificial intelligence systems. Unlike traditional software, AI models can be attacked through their training data, architecture, or outputs. Threats include...

<p>This episode covers data privacy and governance, critical areas for both ethical practice and regulatory compliance. Data privacy refers to protecting individual information from misuse, while governance involves...