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AI Foundations and Secure AI Fundamentals

Packt via Coursera

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Overview

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Build a strong foundation in artificial intelligence while learning to secure AI systems, aligned with the CompTIA SecAI+ certification. The course covers AI types, machine learning, statistical learning, transformers, deep learning, and their applications in AI security. Explore NLP, large and small language models, GANs, and model training techniques, including supervised, unsupervised, and reinforcement learning. Learn data security, prompt engineering, and AI data structures to strengthen secure AI practices. Finally, discover Retrieval-Augmented Generation, embeddings, AI lifecycle management, and human-centric design to deploy AI systems safely. Hands-on exercises ensure practical understanding of securing AI models throughout their lifecycle. By the end of the course, you will be able to apply AI fundamentals, secure AI workflows, perform prompt engineering, manage AI data and models, implement RAG workflows, and maintain AI systems safely.

Syllabus

Introduction

In this module, we will introduce learners to the CompTIA SecAI+ AI Security certification and the course designed to master it. We will explore the certification’s importance, its exam structure, and key strategies to approach it confidently. Additionally, we will highlight what makes this course uniquely effective for SecAI+ success.

CompTIA SecAI+ AI Types and Techniques Certification Exam Guide

In this module, we will explore the foundational AI concepts essential for SecAI+ certification. Learners will dive into generative AI, machine learning, and deep learning techniques tailored for AI security. We will also examine advanced models like transformers and statistical learning to strengthen your AI security expertise.

CompTIA SecAI+ NLP and Language Models Certification Guide

In this module, we will introduce learners to NLP and its application in securing AI systems. We will explore large and small language models, highlighting their significance in AI security frameworks. Additionally, we will explain GANs and their potential uses and risks within AI security contexts.

CompTIA SecAI+ Model Training Techniques Certification Guide

In this module, we will focus on model training techniques vital for AI security. Learners will explore supervised, unsupervised, and reinforcement learning methods. We will also cover optimization strategies such as pruning and quantization and provide quizzes to reinforce understanding of model training techniques.

CompTIA SecAI+ Prompt Engineering Certification Exam Guide

In this module, we will introduce the principles of prompt engineering in AI systems. Learners will explore the distinctions between system and user prompts and understand how different prompting techniques affect AI security. We will also cover prompt templates and system roles to enhance model reliability.

CompTIA SecAI+ Data Security for AI Certification Guide

In this module, we will cover essential data security practices for AI systems. Learners will explore data processing, cleansing, verification, and provenance. Additionally, we will discuss techniques for maintaining data integrity, augmentation, and balancing to ensure secure AI operations.

CompTIA SecAI+ AI Data Types and Structures Guide

In this module, we will explore various AI data types and their role in security. Learners will differentiate between structured, semi-structured, and unstructured data. We will also cover watermarking techniques to safeguard AI data and models against unauthorized use.

CompTIA SecAI+ Retrieval-Augmented Generation Certification Guide

In this module, we will explain Retrieval-Augmented Generation (RAG) and its role in AI security. Learners will explore vector storage and embeddings to optimize secure AI systems. We will also discuss practical applications of RAG to enhance data retrieval while maintaining AI security.

CompTIA SecAI+ AI Security Lifecycle Certification Guide

In this module, we will cover the complete AI security lifecycle from business alignment to model deployment. Learners will explore secure data collection, model development, and evaluation techniques. The module also emphasizes validation, monitoring, and iterative design for robust AI security.