Online Learning Platforms

𝐑𝐀𝐆 𝐢𝐬 𝐬𝐢𝐦𝐩𝐥𝐞—𝐮𝐧𝐭𝐢𝐥 𝐲𝐨𝐮 𝐭𝐫𝐲 𝐭𝐨 𝐛𝐮𝐢𝐥𝐝 𝐢𝐭. Here's how I'd learn it from zero again (minus the rabbit holes): 🧠 𝑺𝒕𝒂𝒓𝒕 𝒘𝒊𝒕𝒉 𝒕𝒉𝒆 𝒘𝒉𝒚 RAG = Retrieval-Augmented Generation. It connects LLMs with real-time information using their knowledge base to avoid hallucinations. 🔧 𝑳𝒆𝒂𝒓𝒏 𝒕𝒉𝒆 𝒄𝒐𝒓𝒆 𝒃𝒖𝒊𝒍𝒅𝒊𝒏𝒈 𝒃𝒍𝒐𝒄𝒌𝒔 • Retriever → Finds the most relevant chunks of data. • Generator → Crafts a smart answer using those chunks. • Vector DB → Stores your knowledge in a searchable, semantic way. Understanding these 3 roles early = 50% of the game. ⚙️ 𝑷𝒊𝒄𝒌 𝒕𝒐𝒐𝒍𝒔 𝒕𝒉𝒂𝒕 𝒉𝒆𝒍𝒑 𝒚𝒐𝒖 𝒕𝒉𝒊𝒏𝒌, 𝒏𝒐𝒕 𝒋𝒖𝒔𝒕 𝒃𝒖𝒊𝒍𝒅 • LangChain & Haystack for structure. • FAISS or Pinecone for vector search. • Sentence Transformers for embeddings. The tools are less important than understanding what each part is doing. 📚 𝑫𝒐𝒏’𝒕 𝒄𝒐𝒍𝒍𝒆𝒄𝒕 𝒅𝒂𝒕𝒂. 𝑪𝒖𝒓𝒂𝒕𝒆 𝒊𝒕. • Chunk long docs — smaller = better retrieval. • Embed with care — garbage in, garbage vectors out. • Store smart — test your indexing early. ✍️ 𝑷𝒓𝒐𝒎𝒑𝒕𝒊𝒏𝒈 𝒊𝒔 𝒘𝒉𝒆𝒓𝒆 𝒊𝒕 𝒊𝒔 𝒓𝒆𝒍𝒆𝒗𝒂𝒏𝒕 Once you retrieve context, you frame the question. • Bad prompt = wasted context. • Good prompt = real augmentation. 🧪 𝑻𝒆𝒔𝒕 𝒐𝒃𝒔𝒆𝒔𝒔𝒊𝒗𝒆𝒍𝒚. 𝑹𝒆𝒃𝒖𝒊𝒍𝒅 𝒎𝒆𝒓𝒄𝒊𝒍𝒆𝒔𝒔𝒍𝒚. You'll break things, and your results will be weird. But with every mistake, your mental model sharpens. • Use relevant Metrics like Context Precision or Context Recall • Monitor your RAG pipeline with Langsmith or Opik I'm not learning RAG to build flashy demos. I’m learning it to build systems that know things I care about. Here are a few Free Courses you can use to boost your RAG learning: 👉𝐋𝐚𝐧𝐠𝐂𝐡𝐚𝐢𝐧 𝐟𝐨𝐫 𝐋𝐋𝐌 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: https://lnkd.in/ddyyTcJU 👉𝐋𝐞𝐚𝐫𝐧 𝐑𝐀𝐆 𝐅𝐫𝐨𝐦 𝐒𝐜𝐫𝐚𝐭𝐜𝐡 (𝐟𝐫𝐞𝐞𝐂𝐨𝐝𝐞𝐂𝐚𝐦𝐩.𝐨𝐫𝐠 – 𝐘𝐨𝐮𝐓𝐮𝐛𝐞 𝐯𝐢𝐝𝐞𝐨): https://lnkd.in/diWyhtRQ 👉𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐭𝐨 𝐑𝐞𝐭𝐫𝐢𝐞𝐯𝐚𝐥 𝐀𝐮𝐠𝐦𝐞𝐧𝐭𝐞𝐝 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐨𝐧 (𝐑𝐀𝐆): https://lnkd.in/d-TMR2kf 👉𝐊𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐆𝐫𝐚𝐩𝐡𝐬 𝐟𝐨𝐫 𝐑𝐀𝐆: https://lnkd.in/dREckUmB 👉𝐑𝐀𝐆++ : 𝐅𝐫𝐨𝐦 𝐏𝐎𝐂 𝐭𝐨 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧: https://lnkd.in/gK6nBp8M 👉𝐋𝐚𝐧𝐠𝐂𝐡𝐚𝐢𝐧 𝐀𝐜𝐚𝐝𝐞𝐦𝐲: https://lnkd.in/d5wwsJPK 👉𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫 𝐌𝐨𝐝𝐞𝐥𝐬 𝐚𝐧𝐝 𝐁𝐄𝐑𝐓 𝐌𝐨𝐝𝐞𝐥: https://lnkd.in/dHP2kUrK 👉𝐑𝐀𝐆-𝐓𝐨-𝐊𝐧𝐨𝐰: https://lnkd.in/gQqqQd2a I hope it has helped!

Steps to Set Up a RAG (Retrieval-Augmented Generation) Pipeline A RAG pipeline enhances the capabilities of large language models (LLMs) by integrating external knowledge sources into the response generation process. Here’s an overview of the traditional RAG pipeline and its key steps: --- 1️⃣ Data Indexing Organize and store your data in a structure optimized for fast and efficient retrieval. - Tools: Vector databases (e.g., Pinecone, Weaviate, FAISS) or traditional databases. - Process: - Convert documents into embeddings using a model like BERT or Sentence Transformers. - Index these embeddings in the database for rapid similarity-based searches. --- 2️⃣ Query Processing Transform and refine the user’s query to align it with the indexed data structure. - Tasks: - Clean and preprocess the query. - Generate an embedding of the query using the same model used for data indexing. --- 3️⃣ Searching and Ranking Retrieve and rank the most relevant data points based on the query. - Algorithms: - TF-IDF or BM25 for traditional keyword-based retrieval. - Dense Vector Search using cosine similarity for semantic matching (e.g., with embeddings). - Advanced models like BERT for contextual ranking. --- 4️⃣ Prompt Augmentation Integrate the retrieved information with the original query to provide additional context to the LLM. - Process: - Combine the query with top-ranked results in a structured format (e.g., "Query: X; Retrieved Data: Y"). - Ensure the augmented prompt remains concise and relevant to avoid overwhelming the model. --- 5️⃣ Response Generation Generate a final response by feeding the enriched query into the LLM. - Output: - Combines the LLM’s pre-trained knowledge with up-to-date, context-specific information. - Produces accurate, contextual responses tailored to the query. --- Summary of RAG Pipeline Benefits By integrating external data into the query-response process, RAG pipelines ensure: - Improved accuracy with domain-specific or real-time information. - Adaptability across industries like customer support, research, and e-commerce. - Better performance in scenarios where pre-trained knowledge alone is insufficient. Setting up a RAG pipeline effectively bridges the gap between general LLM capabilities and specialized data needs! 🚀

the best cybersecurity training i ever got? didn’t come with a cert. theory gets you in the door. hands-on learning makes you dangerous. platforms like TryHackMe = game-changers. they let you: • get your hands dirty with real tools (splunk, wireshark, etc.) • practice real-world attack/defense • build muscle memory (not just head knowledge) • learn at your own pace—without spending $$$ these platforms don’t shine on a resume. hr won’t care how many rooms you’ve cleared. but that’s not the point. turn what you learn into proof. • write blog posts breaking down boxes • build home labs + replicate attacks • document your process • share insights on linkedin or github certs check boxes. hands-on learning builds experience and confidence.

Attention all my #TransitioningServiceMembers, #Veterans, & #MilSpouses looking that are #Aspiring to #Pivot into #Cybersecurity! Resource time! I'm often asked the value of certain resources, and today I want to give you a breakdown of three of the most common platforms that I get asked about: Hack The Box TryHackMe SANS Skills Quest by NetWars (DISCLAIMER: THESE ARE IN NO PARTICULAR ORDER, I'M NOT RANKING THEM OR ENDORSING THEM, I'M GIVING YOU INSIGHT INTO EACH) Are they worth it? Which one’s the right fit for your next mission? Here's my breakdown: SANS Skills Quest by NetWars The Cadillac of cyber upskilling. Think of it as the Special Forces Q Course for your keyboard. Real-world scenarios, up-to-date challenges, and analytics that would make your old S3 jealous. But it’s pricey—so unless you’re ready to invest in your career, it might feel like buying a Humvee for your daily commute. Why pick it? You want hands-on, real-world training You love analytics and tracking progress You’re aiming for CPE credits and serious street cred Regularly updated content Personalized feedback Cons: Expensive Less social/gamified Not for the casual hobbyist Hack The Box (HTB): This is the “ruck march in the rain” of cyber platforms. Realistic, challenging, and sometimes a little painful—but you’ll come out tougher. Minimal hand-holding, maximum realism. If you’re prepping for the OSCP or want to flex those red team muscles, HTB is your proving ground. The community is massive, the machines are tough, and the bragging rights are real. Why pick it? You want to be challenged You’re prepping for advanced certs You like to learn by doing (and sometimes failing) You thrive in a competitive, community-driven space Cons: Steep learning curve Not beginner-friendly Some content paywalled TryHackMe (THM): The “basic training” of cyber. If you’re new to the field, this is your safe landing zone. Guided learning paths, step-by-step walkthroughs, and a gamified experience that keeps things fun. If you like earning badges and want to go from zero to hero without getting lost in the weeds, THM is your battle buddy. Why pick it? You’re a beginner You want structure and support Super accessible for newcomers Guided content Active, supportive community Cons: Less depth for advanced users Some labs can be buggy Walkthroughs can make it easy to “follow the recipe” instead of learning to cook So, there's my two cents! Now go forth and do great things! Still not sure where to start? #FindAMentorFindTen Found this helpful? Smash that “like” button as if it were Jody’s face after stealing your sweetheart, and share with your fellow job seekers like you’re firing for effect. 👀 For more insights on transition, networking, and career, stay tuned by following my profile for updates. #GettingBackToMyRoots #BeardedWonderOfTruthBombs #StillServing #ServiceOverSpotlight #iSwearTheyDontPayMeToDoThis #iJustHaveAHeartForHelpingVets #ImpactWithoutEgo

Data privacy might seem like a box to tick, but it’s much more than that. It’s the backbone of trust between you and your users. Here are a few ways to stay on top of it: + Encrypt sensitive data from day one to prevent unauthorized access. + Regular audits of your data storage and access systems are crucial to catch vulnerabilities before they become issues. + Be transparent about how you collect, store, and use data. Clear privacy policies go a long way in building user confidence. + Stay compliant with regulations like GDPR and CCPA. It’s not optional - it’s mandatory. + Train your team on the importance of data security, ensuring everyone from developers to support staff understands their role in safeguarding information. It’s easy to overlook these tasks when you're focused on growth. But staying proactive with data privacy isn’t just about following laws - it’s about protecting your reputation and building long-term relationships with your users. Don’t let what seems monotonous now turn into a crisis later. Stay ahead. #DataPrivacy #AppSecurity #GDPR #Trust #DataProtection #StartupTips #TechLeaders #CyberSecurity #UserTrust #AppDevelopment

Unveiling 𝗜𝗱𝗲𝗻𝘁𝗶𝗳𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆: Ever encounter the LINDDUN framework? It's privacy threat modeling's gold standard, with 'I' signifying Identifiability - a threat that can strip away the veil of anonymity, laying bare our private lives. A real-life instance: Latanya Sweeney re-identified a state governor's 'anonymous' medical records using public data and de-identified health records. Here, the supposed privacy fortress crumbled. Identifiability can compromise privacy, anonymity, and pseudonymity. A mere link between a name, face, or tag, and data can divulge a trove of personal info. So, what can go wrong? Almost everything. Designing a system or sharing dataset? Embed privacy into the core. Being a Data Privacy Engineer, consider these strategies: 1. Limit data collection. 2. Apply strong anonymization techniques. 3. Release pseudonymized datasets with legal protections. 4. Generate a synthetic dataset where applicable. 5. Audit regularly for re-identification vectors. 6. Educate stakeholders about risks and mitigation roles. Striking a balance between data utility and privacy protection is tricky but crucial for maintaining trust in our digitized realm. Reflect on how you're handling 'Identifiability'. Are your strategies sufficient? Bolster your data privacy defenses now.

As organizational effectiveness increasingly depends on how knowledge is captured, shared, and applied, this document emerges as a comprehensive roadmap for managing knowledge as a core asset. It does not simply define knowledge—it builds a detailed framework for turning experience into competitive advantage through structured processes, systems, and leadership. M&E professionals, knowledge officers, and institutional decision-makers are invited to elevate information into strategy, bridging people, culture, and tools. Here, knowledge management is not a technical system—it is an organizational philosophy anchored in purpose and performance. – It defines the differences between data, information, explicit knowledge, tacit knowledge, and embedded knowledge – It outlines how organizational knowledge exists across individual, group, structural, and extra-organizational levels – It presents leading KM models including SECI, knowledge process frameworks, and integrated KM architectures – It explores key enablers such as organizational culture, leadership, learning, memory, and communities of practice – It details KM strategies and tools including retention systems, groupware, mentoring, storytelling, and IT platforms – It includes operational guidance for building KM frameworks, managing cultural change, and measuring KM impact – It distinguishes between information management and true KM centered on human interaction and learning – It emphasizes the value of KM in fostering innovation, avoiding redundancy, and preserving institutional memory Combining theoretical foundation with operational guidance, this guide empowers professionals to treat knowledge as a tangible, evolving asset. Each section sharpens understanding of systems, structures, and behavior that enable sustainable knowledge flows. More than a textbook, it is a strategic instrument for institutional intelligence, resilience, and long-term value creation.

🚨 After receiving numerous DMs about starting a career in cybersecurity, I wanted to share some free resources that helped me in my journey to becoming a Sr. Threat Detection & Response Engineer. I remember how overwhelming it felt when I first started. But you truly don't need expensive bootcamps to begin. Here are some incredible free platforms that I still use today: 💡 𝐏𝐨𝐫𝐭𝐒𝐰𝐢𝐠𝐠𝐞𝐫 𝐖𝐞𝐛 𝐒𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐀𝐜𝐚𝐝𝐞𝐦𝐲: This has been my go-to for web security fundamentals. What makes it exceptional is how it progresses from basic SQL injection to complex authentication vulnerabilities using real-world scenarios. I started here as a beginner, and even now, I return to brush up on specific techniques or learn about emerging web vulnerabilities. 💡 𝐇𝐚𝐜𝐤𝐓𝐡𝐞𝐁𝐨𝐱: The platform that taught me practical skills I use daily in threat detection. Their guided approach to teaching enumeration, exploitation, and post-exploitation mirrors real-world attack chains we see in incidents. Even if you're just starting, their step-by-step walkthroughs make complex concepts digestible. 💡 𝐏𝐢𝐜𝐨𝐂𝐓𝐅 𝐛𝐲 𝐂𝐚𝐫𝐧𝐞𝐠𝐢𝐞 𝐌𝐞𝐥𝐥𝐨𝐧: Don't let the gamified approach fool you - this platform builds serious skills. From basic cryptography to advanced binary exploitation, it taught me to think like both an attacker and defender. The progressive difficulty helped me build confidence without feeling overwhelmed. 💡 𝐕𝐮𝐥𝐧𝐡𝐮𝐛: Want to understand how attackers think? Vulnhub's vulnerable VMs were crucial in developing my threat detection skills. Each VM is like a puzzle that teaches you different aspects of system compromise - skills that directly translate to identifying and responding to real threats. 🚨𝐀 𝐩𝐢𝐞𝐜𝐞 𝐨𝐟 𝐚𝐝𝐯𝐢𝐜𝐞: While learning, always reference the OWASP Top 10 and align your practice with industry frameworks. It helps build a solid foundation that employers value. 💙 I credit a large part of my current role to the fundamentals I learned on these platforms and I am down to helping others break into cybersecurity, which is why 𝗜'𝗹𝗹 𝗯𝗲 𝗿𝗲𝗴𝘂𝗹𝗮𝗿𝗹𝘆 𝘀𝗵𝗮𝗿𝗶𝗻𝗴 𝘁𝗼𝗼𝗹𝘀, 𝘁𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀, 𝗮𝗻𝗱 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝘁𝗵𝗮𝘁 𝗵𝗮𝘃𝗲 𝗽𝗿𝗼𝘃𝗲𝗻 𝘃𝗮𝗹𝘂𝗮𝗯𝗹𝗲 𝘁𝗵𝗿𝗼𝘂𝗴𝗵𝗼𝘂𝘁 𝗺𝘆 𝗷𝗼𝘂𝗿𝗻𝗲𝘆. 𝗦𝗼 𝗺𝗮𝗸𝗲 𝘀𝘂𝗿𝗲 𝘁𝗼 𝗳𝗼𝗹𝗹𝗼𝘄 𝗺𝗲 @𝗰𝘆𝗯𝗲𝗿𝘄𝗶𝘁𝗵𝗿𝘂 across LinkedIn, TikTok, Instagram, and YouTube for practical insights and guidance as we build this knowledge base together. ❓ 𝐖𝐡𝐚𝐭 𝐨𝐭𝐡𝐞𝐫 𝐟𝐫𝐞𝐞 𝐫𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬 𝐡𝐚𝐯𝐞 𝐡𝐞𝐥𝐩𝐞𝐝 𝐲𝐨𝐮 𝐢𝐧 𝐲𝐨𝐮𝐫 𝐜𝐲𝐛𝐞𝐫𝐬𝐞𝐜𝐮𝐫𝐢𝐭𝐲 𝐣𝐨𝐮𝐫𝐧𝐞𝐲? 𝐋𝐞𝐭'𝐬 𝐛𝐮𝐢𝐥𝐝 𝐚 𝐫𝐞𝐬𝐨𝐮𝐫𝐜𝐞 𝐥𝐢𝐬𝐭 𝐭𝐨𝐠𝐞𝐭𝐡𝐞𝐫 𝐭𝐨 𝐡𝐞𝐥𝐩 𝐦𝐨𝐫𝐞 𝐩𝐞𝐨𝐩𝐥𝐞 𝐛𝐫𝐞𝐚𝐤 𝐢𝐧𝐭𝐨 𝐭𝐡𝐢𝐬 𝐟𝐢𝐞𝐥𝐝. #CyberSecurity #ThreatDetection #GivingBack #InfoSec #CyberCommunity #hacking #breakintocyber #womenincybersecurity

What if instead of having learning just slowly dieing on an LMS, we create an environment where it can thrive? This is why communities are becoming the quiet superpower in learning. Across the L&D space, we are watching a shift. Leaders are realising that the real engine of capability is not just content libraries or platforms. It is the communities that sit around them. The people who challenge each other, support each other, and pull each other forward. It mirrors one of my favourite books, Tribes by Seth Godin. His message is simple. People want connection. They want direction. They want to feel part of something bigger than themselves. When that happens, energy moves. Ideas spread. Change sticks. Yet many organisations still treat learning as a broadcast channel. Push the content. Track the completion. Move on. This is where we hit the wall. Because the world we are operating in does not reward passive acceptance. It rewards shared momentum. Issue 10 of the newsletter focuses on this exact challenge. How do we turn our workforce into an active learning tribe rather than a passive audience? There are some practical ways forward: 1. Create intentional spaces for people to gather Internal communities of practice, peer circles, skill-based cohorts. When people shape the learning with you, the engagement becomes organic. 2. Make learning social by design Campaigns that spark conversation. Playlists people co-curate. Spotlights that celebrate real stories and lived experiences. 3. Empower your early adopters Every organisation has people who naturally unite others. Give them the tools and permission to lead. They become the heartbeat of your learning movement. 4. Shift from ownership to stewardship L&D no longer needs to be the controller. Our value grows when we become the guide. The connector. The person who helps the tribe find its own voice. The future of learning belongs to organisations that understand that knowledge grows stronger when shared, not siloed. And when people feel part of a tribe, they do not just consume learning. They champion it. If we want scalable, sustainable learning cultures, then building community is no longer a nice to have. It is a strategic choice. And just like in Tribes, the real question is not whether people are ready. It is whether we are willing to lead them.