AI for Security, Security for AI
Master the dual challenge of leveraging Artificial Intelligence for enhanced security operations while protecting AI systems from emerging threats. Enroll in our intensive hands-on training program where you will build real-world AI-powered security tools, implement enterprise-grade threat modeling systems, and develop frameworks for responsible AI deployment. Learn to create custom chatbots, automated security assessment platforms, and intelligent security co-pilots while understanding critical vulnerabilities in Large Language Model applications. This comprehensive program combines practical development skills with strategic security thinking, preparing you to evaluate AI vendors, implement governance frameworks, and lead AI security initiatives in your organization.
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Corporate Pricing
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Training Provider Pricing
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Features
Subsidies
What you'll learn
- Implement Retrieval Augmented Generation with custom security knowledge bases
- Build AI-powered security tools including chatbots and threat modeling systems
- Design agentic AI workflows for security co-pilots and incident response
- Establish responsible AI frameworks aligned with EU AI Act compliance requirements
- Develop Model Context Protocol servers for secure AI application integration
- Analyze and mitigate OWASP Top 10 risks for Large Language Model applications
- Create automated AWS security assessment tools using AI code generation
- Build governance processes for safely onboarding AI applications in enterprises
Why should you attend?
This comprehensive course bridges the critical intersection of artificial intelligence and cybersecurity, equipping participants with practical skills to leverage AI for security operations while understanding how to secure AI systems themselves. Participants will gain hands-on experience building AI-powered security tools, from simple chatbots to sophisticated threat modeling systems and automated security assessment platforms. The curriculum progresses through three intensive days, beginning with foundational concepts in generative AI and Large Language Models, then advancing to enterprise-grade application development and threat analysis. Participants will work directly with AWS AI services, implement Retrieval Augmented Generation systems with custom knowledge bases, and develop Model Context Protocol servers. Real-world applications include building AI-assisted threat modelers using STRIDE methodology, creating security questionnaire chatbots, and developing automated AWS security assessment tools. The course addresses critical security considerations throughout, including deep dives into the OWASP Top 10 for Large Language Model Applications, prompt injection vulnerabilities, and data poisoning risks. Participants will explore both Large Language Models and Small Language Models, understanding when each is appropriate for security contexts. Advanced topics include agentic AI workflows, building custom security co-pilots, and implementing responsible AI frameworks aligned with EU AI Act compliance requirements. By course completion, participants will have developed multiple functional security tools and established frameworks for safely onboarding AI applications within their organizations.
Course Syllabus
Day 1 - AI Fundamentals & Applications
Short Break
15 minsShort Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsShort Break
15 minsShort Break
15 minsRecap and Q&A
15 minsEnd of Day 1
Day 2 - AI Security & Threats
Short Break
15 minsShort Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsShort Break
15 minsShort Break
15 minsRecap and Q&A
15 minsEnd of Day 2
Day 3 - Responsible AI & Governance
Short Break
15 minsShort Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsShort Break
15 minsShort Break
15 minsRecap and Q&A
15 minsEnd of Day 3
Ratings and Reviews
Instructor
Pradeep Singh Naulia is a distinguished leader in the AI and data science arena with over two decades of professional experience spanning multiple industries and geographies. As a Chief Technology Officer and Co-Founder, he currently leads cutting-edge AI initiatives focused on agentic LLM platforms, embedded AI, and IoT solutions. His expertise encompasses the full spectrum of AI technologies, from computer vision and NLP to GenAI, transformers, and neural network optimization. With a recently completed Ph.D. in alternative methods to optimize Neural Networks from UTP Malaysia, Pradeep combines deep academic rigor with practical industry experience. He holds prestigious certifications including Certified Analytics Professional (CAP) from INFORMS, AWS and Azure Certified Data Scientist, PMP, and Master Black Belt (MBB). His research contributions are notable, with multiple IEEE and MDPI publications, best paper awards, and a patent application for agentic LLM optimization of deep neural networks. He serves as a journal reviewer for Springer Nature, IEEE, and MDPI, demonstrating his thought leadership in the field. Pradeep's professional journey showcases remarkable versatility across sectors including Oil & Gas, FMCG, Telecom, Financial Services, and Manufacturing. At Petronas, he pioneered the largest Advanced Driver Assistance System (ADAS) using NVIDIA and AWS IoT technologies. During his tenure at BAT Malaysia, he led end-to-end AI projects from data ingestion to cloud deployment, delivering high-impact solutions like Smart Credit Risk analytics. His 13-year career at Hewlett Packard saw him drive transformational projects across supply chain management, achieving multi-million-dollar savings and training over 200 employees in analytics and statistical tools. As a trainer and educator, Pradeep has successfully conducted a 10-week Data Science Bootcamp, training and certifying over 300 data scientists. His teaching approach combines theoretical foundations with hands-on practical applications, drawing from his extensive experience implementing AI solutions across Australia, Brazil, China, India, Malaysia, Philippines, Singapore, Taiwan, and the USA. His ability to translate complex AI concepts into actionable insights makes him an exceptional instructor for professionals seeking to advance their skills in machine learning, deep learning, cloud AI platforms, and data science methodologies.
FAQs
Courses you may like
Why should you attend?
This comprehensive course bridges the critical intersection of artificial intelligence and cybersecurity, equipping participants with practical skills to leverage AI for security operations while understanding how to secure AI systems themselves. Participants will gain hands-on experience building AI-powered security tools, from simple chatbots to sophisticated threat modeling systems and automated security assessment platforms. The curriculum progresses through three intensive days, beginning with foundational concepts in generative AI and Large Language Models, then advancing to enterprise-grade application development and threat analysis. Participants will work directly with AWS AI services, implement Retrieval Augmented Generation systems with custom knowledge bases, and develop Model Context Protocol servers. Real-world applications include building AI-assisted threat modelers using STRIDE methodology, creating security questionnaire chatbots, and developing automated AWS security assessment tools. The course addresses critical security considerations throughout, including deep dives into the OWASP Top 10 for Large Language Model Applications, prompt injection vulnerabilities, and data poisoning risks. Participants will explore both Large Language Models and Small Language Models, understanding when each is appropriate for security contexts. Advanced topics include agentic AI workflows, building custom security co-pilots, and implementing responsible AI frameworks aligned with EU AI Act compliance requirements. By course completion, participants will have developed multiple functional security tools and established frameworks for safely onboarding AI applications within their organizations.
What you'll learn
- Implement Retrieval Augmented Generation with custom security knowledge bases
- Build AI-powered security tools including chatbots and threat modeling systems
- Design agentic AI workflows for security co-pilots and incident response
- Establish responsible AI frameworks aligned with EU AI Act compliance requirements
- Develop Model Context Protocol servers for secure AI application integration
- Analyze and mitigate OWASP Top 10 risks for Large Language Model applications
- Create automated AWS security assessment tools using AI code generation
- Build governance processes for safely onboarding AI applications in enterprises
Course Syllabus
Day 1 - AI Fundamentals & Applications
Short Break
15 minsShort Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsShort Break
15 minsShort Break
15 minsRecap and Q&A
15 minsEnd of Day 1
Day 2 - AI Security & Threats
Short Break
15 minsShort Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsShort Break
15 minsShort Break
15 minsRecap and Q&A
15 minsEnd of Day 2
Day 3 - Responsible AI & Governance
Short Break
15 minsShort Break
15 minsRecap and Q&A
15 minsLunch
1 hourShort Break
15 minsShort Break
15 minsShort Break
15 minsRecap and Q&A
15 minsEnd of Day 3
Public Pricing
Corporate Pricing
Pax:
Training Provider Pricing
Pax:
Features
Subsidies
Ratings and Reviews
Instructor
Pradeep Singh Naulia is a distinguished leader in the AI and data science arena with over two decades of professional experience spanning multiple industries and geographies. As a Chief Technology Officer and Co-Founder, he currently leads cutting-edge AI initiatives focused on agentic LLM platforms, embedded AI, and IoT solutions. His expertise encompasses the full spectrum of AI technologies, from computer vision and NLP to GenAI, transformers, and neural network optimization. With a recently completed Ph.D. in alternative methods to optimize Neural Networks from UTP Malaysia, Pradeep combines deep academic rigor with practical industry experience. He holds prestigious certifications including Certified Analytics Professional (CAP) from INFORMS, AWS and Azure Certified Data Scientist, PMP, and Master Black Belt (MBB). His research contributions are notable, with multiple IEEE and MDPI publications, best paper awards, and a patent application for agentic LLM optimization of deep neural networks. He serves as a journal reviewer for Springer Nature, IEEE, and MDPI, demonstrating his thought leadership in the field. Pradeep's professional journey showcases remarkable versatility across sectors including Oil & Gas, FMCG, Telecom, Financial Services, and Manufacturing. At Petronas, he pioneered the largest Advanced Driver Assistance System (ADAS) using NVIDIA and AWS IoT technologies. During his tenure at BAT Malaysia, he led end-to-end AI projects from data ingestion to cloud deployment, delivering high-impact solutions like Smart Credit Risk analytics. His 13-year career at Hewlett Packard saw him drive transformational projects across supply chain management, achieving multi-million-dollar savings and training over 200 employees in analytics and statistical tools. As a trainer and educator, Pradeep has successfully conducted a 10-week Data Science Bootcamp, training and certifying over 300 data scientists. His teaching approach combines theoretical foundations with hands-on practical applications, drawing from his extensive experience implementing AI solutions across Australia, Brazil, China, India, Malaysia, Philippines, Singapore, Taiwan, and the USA. His ability to translate complex AI concepts into actionable insights makes him an exceptional instructor for professionals seeking to advance their skills in machine learning, deep learning, cloud AI platforms, and data science methodologies.
FAQs
Courses you may like
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