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This lesson introduces the core principles of cloud security through the CIA (Confidentiality, Integrity, Availability) triad. It then dives deep into AWS Identity and Access Management (IAM), the foundation of AWS security. You will learn to create and manage IAM users and groups, enforce strong password policies, and apply the principle of least privilege using IAM policies. The session will cover the structure of an IAM policy, including Effect, Action, Resource, and Condition, and differentiate between AWS Managed, Customer-Managed, and Inline policies.
This lesson covers the essential non-advertising groundwork and technical setup required before launching a Google Ads campaign for lead generation. It focuses on the strategic business prerequisites, such as defining a Unique Selling Proposition (USP) and detailed customer avatars. It then walks through the critical first steps of account creation, emphasizing the importance of selecting "Expert Mode" to gain full control. We will introduce Google Tag Manager (GTM) as the central hub for managing tracking codes and establish the fundamental concepts of conversion tracking, explaining why it is the most critical step to complete before any campaigns go live.
This lesson introduces the core challenge of maintaining model performance in production: model drift. We will define the concept of drift and explore its four primary types as identified by AWS: Data Drift (changes in input data statistics), Model Drift (degradation of prediction quality), Bias Drift (changes in fairness metrics), and Feature Attribution Drift (shifts in feature importance). We will then introduce Amazon SageMaker Model Monitor as the primary service to combat this, covering its automated workflow: establishing a baseline from training data, capturing live inference data, and running scheduled monitoring jobs to compare production data against the baseline to detect deviations.
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