AI & LLM Security Course

What Is the AI & LLM Security Course?

Companies are embedding large language models into chatbots, customer service tools, code assistants and internal search. These systems introduce a new class of vulnerabilities: attackers can manipulate behaviour with crafted text, extract confidential data from connected documents, abuse tool-calling agents or poison the data the model learns from.

This course covers the OWASP Top 10 for LLM applications, practical prompt injection and jailbreak testing, retrieval-augmented generation (RAG) security, agent and tool-use risks and defensive patterns such as input and output filtering, least privilege for tools and monitoring. We also show how analysts use AI assistants for log summarisation, detection drafting and report writing — and where that is risky.

It is best taken after the Cyber Security Course or Bug Bounty & Web Application Security Course.

AI & LLM Security Course at a Glance

Who Should Join This Course?

• Security professionals who need to assess AI features.
• Developers building LLM applications.
• Pentesters adding AI red teaming to their services.
• Managers responsible for AI governance and risk.

AI & LLM Security Course Syllabus – Module by Module

The curriculum below is the practical sequence we follow in class. Each module ends in a lab so you can prove to yourself, and later to an interviewer, that you can perform the task rather than just describe it.

Module 1: AI and LLM Fundamentals for Security People

Enough machine learning to reason about risk.

• How LLMs, embeddings and RAG work
• AI application architecture
• Where trust boundaries sit

Hands-on lab: Draw a trust-boundary diagram of a RAG chatbot.

Module 2: Prompt Injection and Jailbreaks

The core attack class.

• Direct and indirect prompt injection
• Jailbreak patterns and defences
• Data exfiltration through model output

Hands-on lab: Exploit a deliberately vulnerable chatbot and fix it.

Module 3: Data, Model and Supply Chain Risks

Beyond the prompt.

• Training data poisoning and model backdoors
• Insecure plugins and agent tools
• Model supply chain and dependency risks

Hands-on lab: Review an agent configuration for excessive permissions.

Module 4: AI Red Teaming and Evaluation

Systematic testing.

• Test plans for LLM features
• Automated attack frameworks
• Reporting AI risks

Hands-on lab: Write an AI red team report for a sample application.

Module 5: Using AI in Security Operations

Productivity with safeguards.

• Log summarisation and enrichment
• Detection and query drafting
• Risks: hallucination, data leakage

Hands-on lab: Build a safe AI-assisted triage workflow.

Module 6: Governance, Privacy and Compliance for AI

Policies for responsible use.

• AI usage policies, DPDP considerations
• NIST AI RMF overview
• Vendor risk for AI tools

Hands-on lab: Draft an AI acceptable-use policy.

Tools and Technologies You Will Practise

Tool names on a syllabus mean little unless you have actually used them under time pressure. In this course you work with the following, mostly open-source or free-tier, tools so that you can keep practising at home after the batch ends:

• Python
• Burp Suite
• Garak / PyRIT concepts
• LangChain (lab)
• Vector databases (lab)
• OWASP LLM Top 10
• Jupyter

Projects and Capstone Work

Recruiters and clients trust evidence. These are the projects you complete and can document in a portfolio or GitHub repository:

• Vulnerable chatbot assessment: find and fix prompt injection flaws.
• AI policy draft: acceptable-use and risk policy for a company.
• AI-assisted triage prototype: safe workflow with human review.

Why Learn AI & LLM Security Course in 2026?

Almost every product roadmap now includes AI features, and security teams are being asked to assess them without established playbooks. Those who learn early become the internal experts.

AI also changes security work itself, so understanding its strengths and limits is becoming a baseline skill.

Career Roles and Indicative Salary After This Course

The table lists roles that this skill set maps to. Salary figures are indicative market ranges for India expressed in lakhs per annum (LPA); actual offers depend on your city, prior experience, practical skill demonstrated in interviews and the hiring company. They are not a guarantee or promise of placement.

Certifications and Exams This Course Prepares You For

• Vendor AI security learning paths: emerging and evolving.
• Cloud AI certifications: Azure/AWS AI fundamentals as context.
• Security+ / CEH: baseline credentials.

Certification exams are conducted by their respective owners (EC-Council, CompTIA, ISC2, OffSec, ISACA and others). We are an independent training provider; exam fees are paid directly to the certifying body and we do not claim any official partnership.

What You Will Be Able to Do After the AI & LLM Security Course

Learning outcomes should be observable. By the end of this program you will be able to demonstrate the following, each backed by a lab or assignment you complete during the course:

• After AI and LLM Fundamentals for Security People you can: draw a trust-boundary diagram of a RAG chatbot.
• After Prompt Injection and Jailbreaks you can: exploit a deliberately vulnerable chatbot and fix it.
• After Data, Model and Supply Chain Risks you can: review an agent configuration for excessive permissions.
• After AI Red Teaming and Evaluation you can: write an AI red team report for a sample application.
• After Using AI in Security Operations you can: build a safe AI-assisted triage workflow.
• After Governance, Privacy and Compliance for AI you can: draft an AI acceptable-use policy.

How the AI & LLM Security Course Compares With Related Courses

Choosing between neighbouring courses is easier with a side-by-side view. The table compares this program with the options learners most often consider alongside it.

Checklist: Are You Ready to Join?

• Prerequisites: basic cyber security and web knowledge; Python helpful.
• A laptop with 8 GB RAM (16 GB recommended for virtual machine labs) and stable internet.
• About 5 hours per week for live classes, labs and practice.
• An ethical mindset: all techniques are practised only in authorised lab environments.
• Curiosity about how systems fail, and patience to debug when a lab does not work the first time.

If you meet most of these, you are ready; if not, the free demo will tell you which foundation course to take first.

Career Growth Path After This Course

A first role is rarely the destination. Learners who complete the AI & LLM Security Course typically begin as aI Security Specialist or similar and progress towards aI Governance / Risk Analyst and aI Governance / Risk Analyst roles over the following years. Growth depends less on the number of certificates and more on documented work: lab write-ups, a GitHub or blog portfolio, contributions to capture-the-flag teams and clear communication during interviews. Re-skilling every year is part of the profession, so we also share a post-course learning plan and recommend the next logical courses.

How the Online AI & LLM Security Course Training Works

Every class is delivered live by a working trainer over video, so you can ask questions the moment they come up, share your screen when a lab breaks and get an answer on the spot. Sessions are recorded and shared with the batch for revision, which matters if you are a working professional who occasionally misses a class. Lab access is provided on a hosted practice environment, so you do not need an expensive laptop; a basic machine with 8 GB RAM and a stable internet connection is enough for most exercises, and we guide you through the virtual machine setup in the very first week.

The expected duration for this program is About 6-8 weeks, and the pace is designed for people who are studying or working at the same time. Each week combines concept sessions, guided labs, an assignment and a doubt-clearing session. In the final weeks you complete a capstone exercise and go through resume, LinkedIn and mock-interview preparation so that your skills are visible to recruiters.

Batch Timings, Free Demo and How to Register

A new batch for AI & LLM Security Course starts every week, with weekday evening, weekend and fast-track options depending on trainer availability. The simplest way to begin is the free demo class: you join a live session, see the lab platform, review the syllabus with the trainer and ask any question about fees, schedule or career outcomes before you decide.

1. Fill the enquiry form on this page or message us on WhatsApp at +91 81888 77720.
2. We call you back, understand your background and suggest the right course and batch.
3. Attend the free demo class and review the complete syllabus.
4. Confirm your seat for the upcoming batch and receive lab and class access.

Courses That Pair Well with AI & LLM Security Course

Most learners combine this program with one more track. Popular pairings are Bug Bounty & Web Application Security Course, Python for Cyber Security Course, Cloud Security Course and Cyber Security GRC & ISO 27001 Course. You can also compare every track on our all cyber security courses page, or read the fees guide and complete syllabus overview before choosing.

Join From Any City in India

Because the training is fully online, learners join from every state. Popular cities include Delhi, Mumbai, Pune, Hyderabad, Bengaluru, Chennai, Kolkata, Ahmedabad, Noida, Gurugram, Lucknow and Jaipur. See the complete list of states and cities or find the nearest option through our cyber security training near me guide.