The impact of AI on cybersecurity is a hot topic that is generating a lot of attention and conversation. Staying informed of artificial intelligence developments is essential to protecting your digital assets as cyber attacks grow more complex. But sorting through all of the information might take time, given the abundance of it.
While many cybersecurity AI courses go into intricate technical details, it might be difficult to locate a course that simplifies AI for cybersecurity and makes it understandable to all.
Fortunately, we’ve chosen courses for both beginners and individuals who have some experience with AI in Cybersecurity. Both IBM and CFTE’s course offers an insight to AI in Cybersecurity for individuals with minimal experience unlike the SANS and Oxford courses who are designed for individuals with prior coding experience. This guide is designed to help you navigate the wide range of options and find the course that best fits your needs, empowering you to stay ahead in the ever-changing world of cybersecurity
1. CFTE's Cybersecurity with Generative AI Course
This course covers the core concepts of Generative AI, from its main principles to its practical applications in cybersecurity. Participants will gain hands-on experience with tools and techniques for detecting and mitigating cyber threats such as phishing attacks and social engineering attempts.
With an emphasis on real-world examples and use cases, the course includes practical exercises and case studies from leading organisations. You’ll learn how to use AI for threat detection and understand the ethical considerations surrounding AI in cybersecurity. Danny Lopez, the CEO of Glasswall also gives an exclusive insight into the uses of AI and how it has impacted his business. You will discover how leading organisations are harnessing generative AI for cybersecurity and enhance your skills with our hands-on exercises and learn from industry best practices. He will also explain the future outlook of AI within the cybersecurity industry.
Designed for both beginners and professionals, CFTE’s course will equip you with the knowledge and skills needed to navigate the complex and rapidly changing field of AI-driven cybersecurity.
Features
Target Audience
Everyone from executives and senior leaders to professionals in managerial positions
Format
Self-paced, fully online
Level
Foundational
Time to Complete
6 weeks, about 1 hour per week
Add-Ons
N/A
Instructors
1. Huy Nguyen Trieu, Co-founder and Programme Director, CFTE; Former Managing Director, Citi
2. Danny Lopez, CEO of Glasswall
Topics
1. Generative AI Fundamentals
2. The Landscape of Generative AI
3. Landscape of GenAI in Cybersecurity
4. Current Applications and Use Cases of GenAI in Cybersecurity
5. From Theory to Practice – Practical Approach
6. Opportunities & risks in Cybersecurity
Use Cases
Navigate key Generative AI tools, Case studies on IBM, HSBC and JPMorgan
Accreditation
IBF Accredited
Pricing
GBP 450
2. SANS' Applied Data Science and AI/Machine Learning for Cybersecurity Professionals
This course focuses on applying these tools to real-world information security problems. While it covers necessary mathematical fundamentals, the emphasis is on practical application, helping participants understand and apply machine learning tools effectively. The course includes hands-on projects designed to build a solid foundation for creating your own machine learning solutions. It’s perfect for those wanting to understand how AI tools like ChatGPT work and how to build effective cybersecurity solutions using machine learning and AI. The course uses Python examples, requiring intermediate Python knowledge, and is geared towards cybersecurity professionals and data scientists looking to apply their skills to cybersecurity data for threat hunting, anomaly detection, and monitoring. Pre-calculus mathematics skills are helpful but not required.
Features
Target Audience
Cybersecurity professionals who are seeking to add machine learning, data science, and artificial intelligence skills. Intermediate Python fluency is important
Format
In person (USA) and online
Level
Intermediate
Time to Complete
144 Hours
Add-Ons
Anaconda, TensorFlow (and supporting libraries), Matploitb
VMWare, Workstation/Player/Fusion
Instructors
David Hoelzer, Principal examiner and director of research for Enclave Forensics
Topics
1. Data Acquisition, Cleaning, and Manipulation
2. Data Exploration and Statistics
3. Essentials of Machine Learning: Trees, Forests, & K-Means
4. Essentials of Machine Learning: Deep Learning
5. Essentials of Machine Learning: Autoencoders
6. Essentials of Machine Learning: Functional Models and Deployment
Use Cases
Trees, Forests, & K-Means, Autoencoders, Functional Models and Deployment
Accreditation
GMLE Accredited
Pricing
USD 8525
3. IBM's Generative AI for Cybersecurity Professionals Specialisation
This course starts by explaining the differences between Generative and Discriminative AI, setting the stage for a deeper look into AI’s applications in cybersecurity.
You’ll begin by exploring practical uses of Generative AI, examining popular models and tools from various sources. Then you will go through the basics of prompt engineering, including techniques like zero-shot and few-shot prompting, and become skilled in using prompt engineering tools such as IBM Watsonx, Prompt Lab, Spellbook, and Dust.
Next, the course will cover core concepts of Generative AI with a focus on cybersecurity. You’ll gain hands-on experience by applying Generative AI methods to real-world situations, including Unsupervised Behavioural Analysis (UBE).
Throughout the course, you’ll develop a portfolio showcasing your new skills, providing concrete evidence of your abilities to potential employers. Upon finishing, you’ll receive a certificate to share your accomplishments and enhancing your professional profile
Features
Target Audience
Anyone interested in launching a cybersecurity career using prompt engineering. No experience is necessary.
Format
Self-paced, fully online
Level
Beginner
Time to Complete
7 hours
Add-Ons
N/A
Instructors
1. Dr. Manish Kumar, IBM
2. Rav Ahuja, IBM
3. Antonio Cangiano, IBM
Topics
1. Concept and relevance of prompt engineering in generative AI models.
2. Apply best practices for creating prompts and explore examples of impactful prompts.
3. Practice common prompt engineering techniques and approaches for writing effective prompts.
4. Explore commonly used tools for prompt engineering to aid with prompt engineering.
Use Cases
Artificial Intelligence, Prompt Engineering, ChatGPT, Prompt patterns, Generative AI
Accreditation
IBM Accredited
Pricing
Free for 7 days then 38 GBP per month
4. Oxford's Artificial Intelligence for Cyber Security
This course has been designed for cyber security professionals who want to understand AI, and AI professionals who want to work with cyber security.
In this course, the aim is to create an overall framework spanning personas, technology components, and platforms and study the impact of artificial intelligence on this ecosystem.
Where coding is needed, Python will be used. You are expected to be familiar with coding but are not required to master any specific language or code in class. Some code will be used in demonstrations, but you will not need to do any coding yourself. Participants are also expected to have an understanding of Cybersecurity but not Artificial Intelligence.
Features
Target Audience
Anyone interested in cybersecurity and familiar with coding
Format
Online in November only
Level
Intermediate
Time to Complete
24 Hours
Add-Ons
N/A
Instructors
1. Ajit Jaokar, Data Scientist at Feynlabs
2. Nadeem Bukhari, Over two decades dedicated to Information Security Governance, Risk, and Compliance
3. Vikram Tegginamath, Cyber Security leader at McKinsey & Company
4. Raj Sharma, 24 years of experience in software consulting, entrepreneurship with artificial intelligence
5. Anjali Jain, Digital Solutions Architect at Metrobank
6. David Stevens, Regional Director for Customer Success at Neo4j
7. Olu Odeniyi, 30 years’ experience helping organisations maximise commercial gain from technology solutions.
8. Ayşe Mutlu, Data scientist working on Azure AI
Topics
1. Identity Authentication
2. Confidentiality
3. Privacy
4. Anonymity
5. Availability and integrity
6. Cryptographic algorithm
7. Major attack types
8. High-level security protocols
9. Authentication
10. Compliance
11. Security assessment
Use Cases
Log Technologies, Intrusion Prevention System, Anti-virus / Anti- Malware Solutions
Accreditation
UOO Accredited
Pricing
GBP 1295
