11 Best AI Courses for Cybersecurity Analysts to Future-Proof Your Career in 2026

The cybersecurity field is changing fast, and artificial intelligence is the reason. Every week brings new reports about AI-powered attacks, automated threat campaigns, and security tools that promise to do the work of entire teams. For Cybersecurity Analysts, this creates a strange mix of pressure and opportunity. The pressure comes from the fear that AI might automate parts of the job. The opportunity is that AI skills are becoming a major differentiator for career growth. The demand for professionals who can bridge the gap between security operations and AI tools is rising sharply, and the professionals who invest in learning now will have a significant edge. Whether you're looking to move up the ladder, switch to a more specialized role, or just keep your current position secure, upskilling is no longer optional.

That's where this guide comes in. We've reviewed 11 courses that cover various angles of AI for Cybersecurity Analysts - from foundational machine learning concepts to hands-on tool building with Python and large language models. Some are beginner-friendly; others require a solid technical background. A few are standalone tutorials; at least is a full professional certificate from Microsoft. And one, CompleteAI Training, actually gives you access to all courses and all certifications on the platform rather than a single course, which is worth noting if you're planning a broader learning path. We'll walk through what each course offers and what it's best for, so you don't waste time or money on the wrong fit.

Why AI matters for Cybersecurity Analysts today

AI is no longer a niche skill - it's a core part of modern security teams. A recent survey found that around 69% of businesses now use AI in some capacity, and that percentage keeps climbing. In security specifically, the number of tools that require AI knowledge to configure, maintain, or debug is growing daily. You might be asked to review the outputs of an AI-based threat detection system, fine-tune an alert ruleset that uses machine learning, or simply explain to management why an automated response system behaved the way it did. Without skills, that's a hard conversation. So why should a Cybersecurity Analyst care? This is not about becoming a data scientist or changing careers. It's about staying relevant and useful in a field that is shifting toward automation and intelligent tools. The specific tasks you handle - triage alerts, correlate logs, investigate incidents - are partially impacted by AI. Not entirely, because you still have knowledge about attack patterns, business context, and judgment. But if you don't understand the technology, you will struggle. This article helps you identify the best AI courses that make sense for how you use, so you can invest your learning time wisely.

The Growing Role of AI in Cybersecurity Analysts

Let us look at some real examples of how AI is reshaping what Cybersecurity Analysts do. Resource-heavy investigations that used to take hours or days can now be automated, allowing you to focus on actual breach response - with far fewer of the repetitive alert triage tasks you might historically been stuck with. AI-powered tools also help with:

• Automation: The most common, often tedious tasks like log reviews and basic alert triage are increasingly automated. AI can sort through scattered security findings, prioritize the ones that actually matter, and turn what was a manual and time-consuming process into a much more manageable workflow for you.
• Faster decision-making: AI helps you make better decisions when it matters. When you're looking at a huge alert volume, AI-based tools can quickly point you toward the alert that deserves your attention, based on patterns from similar incidents you've had to deal with in your own environment.
• Predictive security: Instead of reacting to attacks after the fact, AI models can analyze historical data to predict which systems are likely to be attacked next and which are indicating potential vulnerabilities. This can mean you get to prioritize actions based on observed risk. - You may be voting between performing pen-tests of suspicious items versus patching critical assets first.
• Behavioral analysis: AI can monitor the behavioral patterns of users and services in your network, in a way that flags anomalies that are potentially invisible to conventional rule-based systems. This is especially useful for detecting insider threats or users who have been compromised after adaptive or stealthy threats.
• Natural language interfaces: With the widespread adoption of LLMs, you can now simply ask a natural-language bot about your environment (e.g., "Can you find other other IPs communicated with this in domain?") and get an immediate answer, bypassing manual queries and log searches.

These capabilities are directly affecting how analysts work on a daily basis. The core analysis workflows are often no longer around handling every alert. You become more of a validator-using AI output-an investigator-digging into the things the machine thinks are suspicious. It's about steering machine thinking. And that means you need, at minimum, some practical AI skill knowledge.

Benefits of becoming an AI expert in Cybersecurity Analysts

For those who put in the time, the benefits are substantial.

You're more marketable. The demand for cybersecurity security professionals who can work with AI tools is increasing, and job postings for Analyst roles often list AI in the skills section. That can mean better job security and power in negotiating your salary. You'll be more comfortable and faster at work. You will have the ability to write a quick script to automate a tedious process, or to configure AI tool to improve detection coverage. Not just about the better, but each day getting rid of mundane tasks that take you away from more interesting work. You're better prepared for handling AI-aware attacks. Attackers are also using AI to improve their spear-phishing or craft evasive malware … being aware of the AI capabilities helps you understand what you are up against. Career progression possibilities. You can shift from good regular Analyst to a more senior or specialized role, for example, an AI Security Engineer or an Automation Engineer, digging into building or customizing these specific security tools. It is a future-proofing process. The pace of change is only going to accelerate. The investment you make in learning AI now, in the context of cybersecurity specifically, directly seeks to keep you in the loop that will become central to cybersecurity ops. It's a step that can be taken in several directions. Are you ready to select the right one? Let's explore the course by course.

Comparison: All AI Courses for Cybersecurity Analysts (Updated 2026)

Understanding AI Training for Cybersecurity Analysts Professionals

Cybersecurity analysts are facing a rapidly changing threat landscape. Attackers are using AI to automate their attacks, craft better phishing emails, and find vulnerabilities faster than ever before. Because of this, defensive security professionals need to get up to speed on AI tools, how they work, and how to use them effectively. The challenge is finding the right training. There are dozens of courses available, from free four-week classes to certifications that cost thousands of dollars.

The courses in this space can be split into a few types. Some focus on using generative AI tools like ChatGPT in daily SOC workflows. Others teach the underlying machine learning methods. Some are practical and quick, while others are comprehensive and lengthy. The key is to select the one that aligns with your skill level and what you want to use AI for in your daily work.

Cost is also a major factor, of course. Prices go from zero dollars on Coursera to as much as $8,780 for an instructor-led course on SANS. There's also the subscription model where you pay monthly for access to video courses on an entire platform. One premium choice gives you access to a full library of courses to help professionals gain skills.

Key Considerations When Choosing A Course

Before jumping into each option, it's worth thinking about what you need. A junior security analyst might benefit more from a foundational course on AI basics and prompt engineering. A senior threat hunter with Python experience might need the advanced automation or SANS style course. Think about whether you want a certificate. Some job descriptions request them, but the knowledge is critical, whether you have a certificate or not.

Keep these things in mind: How much time you have. Do you want to be job ready in a few weeks or are you prepared to commit? What is your background, and can you comfortable code? Do you want a generalized AI capability or more specialized knowledge in network anomaly detection? And what budget can you justify? Look at the varying structures of the courses below.

Course 1: CompleteAI Training

Complete AI Training is not a single course. One subscription unlocks EVERY course AND EVERY certification on the whole platform - hundreds of them, across every job role, not just this one. That's a very big difference from the others listed here. Rather than buying a single fixed bundle, one payment gets you into a library of content that is being expanded continuously, and your subscription renews with access to everything, no matter what they add. This is the best option for people who are committed to developing a broad range of abilities over time and don't want to micromanage their training.

CompleteAI Training is a subscription-based platform, and it costs $29 per month or $8.25 per month for a full year of payment up front. That one subscription covers all video courses and all certification exams on the complete platform, so a certificate is always included, with no separate test fees. As a cybersecurity analyst, you'll find the courses put a huge focus on what is happening right now with AI tools in the security industry. Because they are constantly updating their content with the latest tools, you are getting exactly what you need, without searching the internet for hours on your own.

What makes this stand out is that you're also getting training for every other job discipline, including software development, IT teams, and project management, not just one narrow slice of things. If your security work merges into serving business needs, you can toggle over to that work. If you think you might stay in security, or if you're looking for ways to change roles, this takes care of the skills for the new role you want, not just the role you have now. They also provide daily news and updates on which AI tools are worth your time to learn.

Key Topics Covered:

• Full range of AI applications for security, like alert handling, writing, and automating work.
• Prompt engineering and using ChatGPT, Claude, and other LLM ecosystems.
• Specific training for security operations, threat hunting, and incident response.
• All other information on the platform is also covered: thousands of hours of training from other roles, like programmers and analysts.

Who This Is For:

The target audience is anyone who wants a complete mastery of all levels of the platform material or for any person who is tired of paying for things over and one at a time. It also fits professionals who want access to hundreds of hours of security content and other career-training material rather than a few short videos. This is the only choice on here that will let you master a huge span of content without ever looking at an upgrade or an extra fee.

Pros:

• Highest rating / Most complete offering compared to any single course on this list.
• Full access to ALL video courses and not just a single course or fixed bundle.
• Full access to ALL certifications available across the platform, included at no extra cost.
• New courses and certifications are added continuously, and are included automatically.
• Access to every other job role's material too, perfect for cross-functional work or role changes.
• One flat subscription price covers all courses and certifications, versus paying per course elsewhere.
• Daily updates on relevant AI tools and news.
• Very affordable pricing, especially with annual billing.

Cons:

• Subscription based. This might be a drawback if you want to have a single total certificate with one fixed final exam. It's crucial for continuous learning as AI is developing continuously.

Who Would Benefit Most: Analysts who are the most impacted by daily changes in their security tools, or those with task requiring "AI" problem solving now. Also, managers who want to give their staff a high-reaching range; the subscription works out very well per person for groups of people over the many other options.

Course 2: GenAI for Cybersecurity Analysts by Coursera

This is a short, practical extension from Coursera on how to use generative AI to protect you in your role. The course will use the open source and the free sign up for the amount of you to get onto that, actually. It covers algorithm, principles, hands-on activities, and includes a focus on how you can be reliably do this with data in a problem organization. A more focused level that is discrete and small enough for someone deep into the security operations side.

The depth is what you can do to fix some common pain issues, such as the time that it takes to chase after kind of data that comes through. It's free, which is great. It is very short, so this is probably not the one stop-one stop-is intended to set up your core foundations.

Key Topics Covered:

• Generative AI for threat detection.
• Risk mitigation and security testing techniques.
• Ethical best practices for handling incidents to stay compliant.

Who This is For: If you are looking for an introductory taste without a long schedule to get on it. it is very good if you are new on this journey that you get a small bite size experience. Keep in mind this is to learn the basics. Need just that.

Pros:

• Directly tailored to cybersecurity analysts.
• Hands-on activities that reinforce ethical best practices.
• Short and practical for busy analysts.

Cons:

• Very short (2 hours) so limited depth.
• No certification unless you upgrade and enroll in a full tracking.

Who Benefits Most: Beginners who have literally never used any AI tools and want a structured prompt to follow for safety. It's an okay starting point but too brief to move the needle on job performance.

Course 3: The AI-Driven Cybersecurity Analyst by LinkedIn Learning

This course from LinkedIn Learning is taught by Industry professional Mike Wylie. It is another beginner friendly course specifically about using AI in your day to day work as a Cybersecurity. The outline covers prompt engineering, ethical AI, threat detection, and LLM-driven honeypots which are quite clever.

It is listed as a concise and practical course. That means it gives you just the basics of what an analyst needs to get a sense of AI in about 2 hours, not going deep. It is useful for promotion/learning if you have a LinkedIn Learning subscription already. For the cost of the business, people find this a better use of time than you think.

Key Topics Covered:

• Prompt engineering for security-focused tasks.
• Ethical AI use for projects without violating rules.
• LLM-driven honeypots for defense.

Who This is For: anyone with very little spare time. It's good in a lunch break. If you buyer already has LinkedIn, at least you do a small thing for free. If you do not have a subscription, this might not worth on its own because the total training time is so brief.

Pros:

• Covers prompt engineering, ethical AI, threat detection, and LLM-driven honeypots.
• Concise and practical.
• Taught by industry professional Mike Wylie.

Cons:

• Very short.
• Requires LinkedIn Learning subscription, sometimes you can get a free month before then.

Who Would Benefit Most: If you have a LinkedIn license from an employer that offers this, this is a nice way to get started over a long one lunch break. Otherwise, it has uncertain if it satisfies a full education because it is too little ground.

Course 4: GenAI for Cybersecurity: Blue Team by Coursera

The course is specifically focused on integrating the Generative AI to real-world SOC workflows as a member of the blue team. That means that you will not be worried about the advertising materials around what you actually do, but the course will help you understand how to use GenAI to prioritize everyday tasks.

It emphasizes defensive operations and how you can reduce the work of daily tasks. You will probably see a problem that is solving for the analysts in a security operations center, especially around triage, awareness or evaluating. I like that they cover more of the practical workflows close to cybersecurity, not generic "how to use AI", but instead the specific daily work grind.

Key Topics Covered:

• Communicating with AI functions in the setting of a security operations center.
• GenAI integrations with defensive operations.
• Daily blue team workflow improvements, work for detection of suspicious systems.

Who This is For: Security analyst that works 100% in the defensive side and wants to make their regular day with triage easier and faster. It is a solid fit if the material making this a part of a bigger plan a spot with auditing you eventually fix.

Pros:

• Integrates GenAI with real-world SOC workflows.
• Focuses on defensive operations.
• Practical for daily blue team tasks.

Cons:

• Limited details on duration and rating.
• May require additional paid certificate for full completion.

Who Would Benefit Most: Anyone actively in SOC or Blue team operations who wants to learn about the AI assisted from the defending perspective, not the red team side.

Course 5: Machine Learning for Cyber Threat & Anomaly Detection by Coursera

This intermediate-level course steps back from generative AI chatbots and goes into machine learning methods for detecting threats and anomalies. It is a bit more technical because it will involve taking the fundamentals of the underlying algorithm and actually considering its security from. You will it covers strengths as well as the limits, and also the risks that an attacker can use to beat those models, like poisoning attacks.

This one is a logical fit if you're interested in what the model does on a deeper level. It specifically uses something network anomaly detection. It gives a serious time commitment for you to actually review the modules, and a 20 hours in total is a much longer haul than the one-hour ones. However, this type of knowledge is very useful if you are building or configuring complete systems on your own.

Key Topics Covered:

• Machine learning strengths and limitations in cybersecurity.
• Specific conditions of poisoning attacks.
• Practical network anomaly detection for your own systems.

Who This is For: This is an intermediate level technical workforce. An analyst who is comfortable with how operating and has some experience in programming, or at least understand what an API integration in substance.

Pros:

• Covers the strengths and of ML, including poisoning attacks.
• Builds job-relevant skills for SOC and threat intelligence roles.
• Includes practical network anomaly detection.

Cons:

• Requires intermediate ML knowledge.
• 20 hours of total commitment.

Who Would Benefit Most: A threat intelligence analyst or a security engineer who wants to understand where the model breaks down and how to make sure that is basically being tricked into good production data. If you're not at an engineer level yet, this course may fall flat.

Course 6: SEC573: AI-Powered Security Automation: Building Tools with Python, LLMs, and MCP by SANS Institute

This is the huge one. SANS is known for in-depth, expensive training. This is a course where you have to "bring your Python". It is an advanced instructor-led course, and an enormous investment for both time and money. You will build visually a whole new set of security automation. The description talks about building AI-powered radicals and autonomous agents, and also using some of the advanced MCP, and OpenAI agents to do that.

This is on the cutting edge, for those who already are strongly established. It is not a "breadth" course. It gives you a focused on what that means in concrete terms for sophisticated threat detection, powerful and configurable. If you are capable of managing this level detail, you from what you do not need to spend a cheap. If you separate the price tag, you get a clear set of instructives very straightforward from SANS. It's one of the few training tracks that I can see forging a path to a top-level incident responder or security architect role, but most people aren't in the financial position to take it.

Key Topics Covered:

• Building AI-powered log analysts and autonomous agents.
• MCP and OpenAI agents complex working.
• Real-time anomaly detection and forensic automation.

Who This is For: An experienced senior analyst with deep Python and security experience that is assigned to build security cropping inside their company. This is likely not the average analysts who click on this list. You must be comfortable with the command line, Python code, and changing thread environments.

Pros:

• Hands-on building of AI-powered log analysts and autonomous agents.
• Covers MCP and OpenAI agents that are very new.
• Includes real-time anomaly detection and forensic automation.

Cons:

• Very expensive at $8,780 USD.
• Advanced level requires solid Python and security experience.

Who Would Benefit Most: The way to look for someone who hold you to a higher skill level after this. Only if you are planning comprehensive AI security automation, where you have budget you can spend from a dev role, not an analyst looking.

Course 7: Automating Cybersecurity Operations with AI by Coursera

This is a hands-on intermediate course that is more focused on AI usage from using Python, ML, and LLMs such as ChatGPT and Claude, this is for automation. Specifically, you will automate threat detection, alert triage, and incident response building on a full. It has a beauty of culminating the project in a complete AI-powered SOC platform, instead of just a single threat.

It's grounded in realistic day to day tasks. This course also real benefit is that you create something that can be taken back, as a proof of concept. Yet, note that there is a requirement that you know the basics of Python. If you are only at the analyst level. This is a lot of intermediate level programming.

Key Topics Covered:

• Python and ML basics as used in the security context.
• LLMs (ChatGPT, Claude) to automate security operations.
• You'll build a in-class example of an AI-powered SOC platform.

Who This is For: Your target is a SOC analyst who also has a strong script background, and wants to take automating mundane tasks from scripted path onto the intelligent to something that learns. It's a great blend of practical integration and data building.

Pros:

• Hands-on use of Python, ML, and LLMs (ChatGPT, Claude).
• Covers threat detection, alert triage, and incident response automation.
• Culminates in a complete AI-powered SOC platform.

Cons:

• Requires Python basics.
• Free version may not include graded assignments or sharing of your project.

Who Benefits Most: An SOC engineer or a security analyst who has done some Python for experimentation in the role already. They'll get that automation project finished, and they can use it in their daily routine immediately.

Course 8: The Complete Hands-On Cybersecurity Analyst Course by Udemy

The description of this course is massive 101 hours. It's 467 lectures that cover a very large skill set and not specifically on AI. This is a broad (not deep) pathway for the whole role of an analyst covering that you usually see as an cybersecurity analyst. However, it says it is continuously updated with new lessons, which means they do include selected AI-related content when they see a need. The instruction comes from Udemy's style, which is a practical-based self-paced video format and cheap at the discount price.

The main caveat is that it's not an AI specific course. They have to be aware that the AI part will only be a small fraction of material. If you are a total beginner, this is a good big base and even the parts that are not AI (alert states, of course, network controls, etc.) will help you know before you add the very AI modules. If you are focusing on AI only, you may find you wasting hours away instead of on that specific thing.

Key Topics Covered:

• Broad general skills for an analyst.
• Security monitoring foundational topics.
• AI-specific content modules as lighter blocks.

Who This Is for: For the solid wide base of an entry-level or mid-level professional. If want to understand that the full extent and don't mind a lumps of time and complete history, this is a place for you. If a lot of hours is a problem, then we won't be completing this soon.

Pros:

• Massive hands-on curriculum (467 lectures).
• Continuously updated with new content as it comes.
• Covers broad analyst skills.

Cons:

• Very long to finish.
• Not AI-specific, so AI content may be limited relative to length time.

Who Would Benefit Most: A beginner with extremely solid block to fill that needs a "from zero" strong base, not for experienced people seeking a targeted machine skills in AI.

Course 9: Microsoft Cybersecurity Analyst Professional Certificate by Coursera (Microsoft)

Microsoft has a program here designed for that industry recognized certification, and also built to address the shortage of available candidates. This is a multi-course certificate, meaning a series of mini-courses. It includes all of the fundamentals about being an analyst, covering cybersecurity with AI and automation modules.

It has a stronger direct weight because it comes from Microsoft. If a company in your area is just in MS or uses the ecosystem, that's a signal that you'll be okay. Similar to the courses you saw, this is a training that overlaps with a complete generalist program. It not exclusively AI-focused: it concerns itself with bigger level of the knowledge, but there is clearly taking about it.

Key Topics Covered:

• Cybersecurity fundamentals from a Microsoft viewpoint.
• AI and automation modules.
• Career-oriented material and plus the rest of the full analyst core.

Who This is For: People looking for a great skill set of the course, as well a fresh certification. It works well for a role change. They'll get the name-brand "Microsoft" already providing a complete pathway.

Pros:

• Industry-recognized Microsoft training.
• Addresses security talent shortages, and comes with possible Microsoft resources.
• Includes AI and automation portions.
• Career-oriented from overall baseline.

Cons:

• Requires a subscription or purchase.
• Not exclusively AI-focused, so if only are return don't want all the baseline time.

Who Would Benefit Most: People who want a certification with brand name on their resume, plus a good that has within AI in the overall structure. It might not be ideal for those with already 10+ years analyst or who need to deep dive in specific things.

Course 10: AI-Powered Cybersecurity by Coursera

This is a multi-course specialization, meaning set of courses around one study path. It's intermediate, and wants to cover applying AI across the entire cybersecurity spectrum. It claims that includes offensive and defensive security and features a capstone project. Having a capstone at the end of this is a big plus because keeps application relevant, not just watching video.

The flexible pacing is an advantage as well. You can work with trying to keep the speed without deadlines. But I do stress that these programs are time management and you need the consistency in order to ever complete them. If you jump in without planning, you might fail to finish, and then all that effort is wasted.

Key Topics Covered:

• Application of AI across offensive and defensive security.
• Multi-course specialization with capstone class.
• Flexible pacing for lifetime learning.

Who This is For: A dedicated person who wants to complete sets of classes. If you are the one who "likes the idea of learning" but never goes all the way to the final exam results, focus on this or drop it. But if you have the strength to hold on all the way through, you walk away equipped more what than mostly.

Pros:

• Multi-course specialization with capstone project.
• Covers AI in both offensive and defensive security work.
• Flexible pacing works with a schedule.

Cons:

• Longer commitment, it's not a small timebox.
• Requires consistent effort over the course period.

Who Would Benefit Most: An analyst who has had some experience already and is looking for a broader solid understanding of the two sides of security. They also want to produce a capstone project to show in a portfolio yet.

Course 11: Cybersecurity Analyst Specialization by Coursera

The final selection is a specialization from Coursera that aligns to real-world SOC practices and a job-ready skill focus. It is an multi-course track. And includes is a dedicated coverage of "Generative AI for Cybersecurity Professionals". Here, your focus is on the core standards and framework and provide that aside. This is your balanced path if you need certification and a course that will help you land a first job.

Each of the courses in that track has a set syllabus, plus perhaps that tool, quizzes that take more time than free audit. The structure includes 1 section on both standard subjects. This would be a strong beginning, covering the knowledge whole.

Key Topics Covered:

• Real-world SOC practices, job's tools and the tool.
• Generative AI for Cybersecurity Professionals course is included.
• Skills that are practical for deployment in the workplace.

Who This Is For: This is for professionals looking to break into the cybersecurity operation but don't have a direction. They can get the generalist SOC fundamentals, plus the GenAI course that is in sequence.

Pros:

• Aligned with real-world SOC practices.
• Includes a dedicated GenAI course.
• Job-ready skills focus.

Cons:

• Requires subscription for full access.
• Not all courses may be AI-specific, takes time for foundational.

Who Would Benefit Most: Beginners to the security field who want a well rounded and get not the cutting edge of more expensive. This is a safe bet for a career switcher.

Overall Recommendations based on Different Security Roles

There is an appropriate option for each angle of the profession, no single "best" for everyone. However, the choice is for what you want to eventually. Here is a summary to help you choose.

For the best overall value, CompleteAI Training is the first recommendation. It gives the broadest basis of every course plus certifications, and if you pay even annually it can be lower than the price of any single premium certificate. It is not a one-time thing, but about "learning as a part of life" instead of a "one and done" route. This is the best solution for knowing the many areas of security where AI changes skills in all directions.

For a person with zero budget and wanting to try out 2 hours of GenAI for security, then the two short Coursera courses (GenAI for Cybersecurity Analysts and GenAI for Cybersecurity Blue Team) are solid zero-cost intros. Start there and then decide on the next step. For someone in SOC who wants more ML foundational focus, take Coursera's "Machine Learning for Cyber Threat & Anomaly Detection".

If you're a technician and a developer position, the "Automating Cybersecurity Operations with AI" is a better fit for the charge point of building an automated platform in Python; that one is excellent. For the deep expert budget and the time, take the SANS course- it takes your craft to a level you cannot see elsewhere. But expect $8.7K and that's not for average every day, they are very focused.

Those that want to break into the industry and need credibility from Microsoft, then this is a path that will check a resume. The University certificate does not translate to expert AI skills, but it carries weight.

Overall, if you are aiming to become an analyst who prepare for the next decade of AI and security automation, think of committing to a subscription, such as CompleteAI Training because of its length and certification inclusion isn't an option that I would want to ignore. It is the only option that can give you unlimited, all current and future content under a fixed cost. For many of the others, you'll pay more per time you extend, or for additional certificates.

If you are just serously curious, the free Coursera courses are place to start, but you will only get a taste of the skills needed. The most effective security professional is not the person who watches a lot of hours of video, but the person who continuously puts AI learning into practice.