Building Robust AI Products
Building Robust AI Products
Published 4/2025
Duration: 1h 43m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 589 MB
Genre: eLearning | Language: English
Published 4/2025
Duration: 1h 43m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 589 MB
Genre: eLearning | Language: English
Design secure, reliable, and compliant AI systems with best practices in data quality, and risk mitigation
What you'll learn
- Apply best practices to design resilient AI systems
- Evaluate data quality, diversity, and bias in AI training
- Identify and mitigate risks in AI supply chains
- Build a roadmap for secure, compliant AI deployment
Requirements
- Basic understanding of AI concepts and machine learning fundamentals
- An interest in AI product development, governance, or risk management
Description
Are you building AI products that need to operate reliably in the real world? Do you want to ensure your AI systems are secure, resilient, and aligned with regulatory expectations?
This course is your complete guide to building robust AI products—from concept to continuous improvement.
Whether you're an AI product manager, data scientist, tech leader, or ML engineer, this course will equip you with the frameworks and real-world practices to design, deploy, and maintain AI solutions that perform consistently and responsibly.
What You’ll Learn:
How to evaluate data quality, coverage, bias, and robustness
Ways to avoid brittle models through smart data and architecture choices
How to manage risks from AI supply chains, vendors, and third-party models
Techniques for testing AI across multiple use cases and data scenarios
Methods for identifying and defending against prompt injection and adversarial attacks
The principles of AI governance and aligning with GDPR, ISO 27701, and NIST
Secure deployment practices and continuous monitoring strategies
How to build an actionable AI product roadmap
Each concept is illustrated usingGenAI Assist, a model AI system built by IntelliTech Solutions. This helps you apply lessons directly to real-world use cases in legal, financial, and compliance-focused AI solutions.
You’ll complete hands-on labs, interactive quizzes, and a final project where you’ll create your ownResilient AI Product Roadmap—a practical plan you can apply to any AI project.
Who This Course Is For:
AI product managers and tech leads seeking real-world deployment strategies
Data scientists and ML engineers looking to improve AI reliability and fairness
Security professionals involved in AI red teaming and threat mitigation
Business and compliance leaders responsible for AI accountability
No coding required. Whether you're leading AI development or managing its risks, this course helps you deliverAI systems that are trustworthy, scalable, and secure.
Join us and start building AI that lasts.
Who this course is for:
- Tech leaders, AI product managers, and startup founders seeking to build trustworthy AI systems
- Data scientists and ML engineers interested in production-ready AI strategies
- Security professionals and compliance teams involved in AI governance
- Anyone responsible for launching, scaling, or securing AI products in real-world environments
More Info