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Frankenstein, Troll 2, and A House of Dynamite are just a few of the movies you should watch on Netflix this month.View the full article

Stranger Things, The Beast in Me, and Last Samurai Standing are just a few of the shows you need to watch on Netflix this month.View the full article

A sprawling academic cheating network turbocharged by Google Ads that has generated nearly $25 million in revenue has curious connections to a Kremlin-connected oligarch whose Russian university builds drones for Russia’s war against Ukraine. The Nerdify homepage. The link between essay mills and Russian attack drones might seem improbable, but understanding it begins with a simple question: How does a human-intensive academic cheating service stay relevant in an era when students can simply ask AI to write their term papers? The answer – recasting the business as an AI company – is just the latest chapter in a story of many rebrands that link the operation to Russia’s largest private university. Search in Google for any terms related to academic cheating services — e.g., “help with exam online” or “term paper online” — and you’re likely to encounter websites with the words “nerd” or “geek” in them, such as thenerdify[.]com and geekly-hub[.]com. With a simple request sent via text message, you can hire their tutors to help with any assignment. These nerdy and geeky-branded websites frequently cite their “honor code,” which emphasizes they do not condone academic cheating, will not write your term papers for you, and will only offer support and advice for customers. But according to This Isn’t Fine, a Substack blog about contract cheating and essay mills, the Nerdify brand of websites will happily ignore that mantra. “We tested the quick SMS for a price quote,” wrote This Isn’t Fine author Joseph Thibault. “The honor code references and platitudes apparently stop at the website. Within three minutes, we confirmed that a full three-page, plagiarism- and AI-free MLA formatted Argumentative essay could be ours for the low price of $141.” A screenshot from Joseph Thibault’s Substack post shows him purchasing a 3-page paper with the Nerdify service. Google prohibits ads that “enable dishonest behavior.” Yet, a sprawling global essay and homework cheating network run under the Nerdy brands has quietly bought its way to the top of Google searches – booking revenues of almost $25 million through a maze of companies in Cyprus, Malta and Hong Kong, while pitching “tutoring” that delivers finished work that students can turn in. When one Nerdy-related Google Ads account got shut down, the group behind the company would form a new entity with a front-person (typically a young Ukrainian woman), start a new ads account along with a new website and domain name (usually with “nerdy” in the brand), and resume running Google ads for the same set of keywords. UK companies belonging to the group that have been shut down by Google Ads since Jan 2025 include: –Proglobal Solutions LTD (advertised nerdifyit[.]com); –AW Tech Limited (advertised thenerdify[.]com); –Geekly Solutions Ltd (advertised geekly-hub[.]com). Currently active Google Ads accounts for the Nerdify brands include: -OK Marketing LTD (advertising geekly-hub[.]net⁩), formed in the name of the Ukrainian national Alexander (Oleksandr) Korsukov; –Two Sigma Solutions LTD (advertising litero[.]ai), formed in the name of Olekszij Pokatilo. Google’s Ads Transparency page for current Nerdify advertiser OK Marketing LTD. Messrs. Korsukov and Pokatilo have been in the essay-writing business since at least 2009, operating a paper-mill enterprise called Livingston Research. According to a lengthy account from a former employee, Livingston Research mainly farmed its writing tasks out to low-cost workers from Kenya, Philippines, Pakistan, Russia and Ukraine. In 2011, the two men set up a Cyprus corporation called VLS Research Ltd, which would later change its name to CLS Research Ltd. Pokatilo moved from Ukraine to the United Kingdom in Sept. 2015 and co-founded a company called Awesome Technologies, which pitched itself as a way for people to outsource tasks by sending a text message to the service’s assistants. The other co-founder of Awesome Technologies is 36-year-old Filip Perkon, a Swedish man living in London who touts himself as a serial entrepreneur and investor. Years before starting Awesome together, Perkon and Pokatilo co-founded a student group called Russian Business Week while the two were classmates at the London School of Economics. According to the Bulgarian investigative journalist Christo Grozev, Perkon’s birth certificate was issued by the Soviet Embassy in Sweden. Alexey Pokatilo (left) and Filip Perkon at a Facebook event for startups in San Francisco in mid-2015. Around the time Perkon and Pokatilo launched Awesome Technologies, Perkon was building a social media propaganda tool called the Russian Diplomatic Online Club, which Perkon said would “turbo-charge” Russian messaging online. The club’s newsletter urged subscribers to install in their Twitter accounts a third-party app called Tweetsquad that would retweet Kremlin messaging on the social media platform. Perkon was praised by the Russian Embassy in London for his efforts: During the contentious Brexit vote that ultimately led to the United Kingdom leaving the European Union, the Russian embassy in London used this spam tweeting tool to auto-retweet the Russian ambassador’s posts from supporters’ accounts. Neither Mr. Perkon nor Mr. Pokatilo replied to requests for comment. A review of corporations tied to Mr. Perkon as indexed by the business research service North Data finds he holds or held director positions in several U.K. subsidiaries of Synergy, Russia’s largest private education provider. Synergy has more than 35,000 students, and sells T-shirts with patriotic slogans such as “Crimea is Ours,” and The Russian Empire — Reloaded.” The president of Synergy is Vadim Lobov, a Kremlin insider whose headquarters on the outskirts of Moscow reportedly features a wall-sized portrait of Russian President Vladimir Putin in the pop-art style of Andy Warhol. For a number of years, Lobov and Perkon co-produced a cross-cultural event in the U.K. called Russian Film Week. Synergy President Vadim Lobov and Filip Perkon, speaking at a press conference for Russian Film Week, a cross-cultural event in the U.K. co-produced by both men. Mr. Lobov was one of 11 individuals reportedly hand-picked by the convicted Russian spy Marina Butina to attend the 2017 National Prayer Breakfast held in Washington D.C. just two weeks after President Trump’s first inauguration. While Synergy University promotes itself as Russia’s largest private educational institution, hundreds of international students tell a different story. Online reviews from students paint a picture of unkept promises: Prospective students from Nigeria, Kenya, Ghana, and other nations paying thousands in advance fees for promised study visas to Russia, only to have their applications denied with no refunds offered. “My experience with Synergy University has been nothing short of heartbreaking,” reads one such account. “When I first discovered the school, their representative was extremely responsive and eager to assist. He communicated frequently and made me believe I was in safe hands. However, after paying my hard-earned tuition fees, my visa was denied. It’s been over 9 months since that denial, and despite their promises, I have received no refund whatsoever. My messages are now ignored, and the same representative who once replied instantly no longer responds at all. Synergy University, how can an institution in Europe feel comfortable exploiting the hopes of Africans who trust you with their life savings? This is not just unethical — it’s predatory.” This pattern repeats across reviews by multilingual students from Pakistan, Nepal, India, and various African nations — all describing the same scheme: Attractive online marketing, promises of easy visa approval, upfront payment requirements, and then silence after visa denials. Reddit discussions in r/Moscow and r/AskARussian are filled with warnings. “It’s a scam, a diploma mill,” writes one user. “They literally sell exams. There was an investigation on Rossiya-1 television showing students paying to pass tests.” The Nerdify website’s “About Us” page says the company was co-founded by Pokatilo and an American named Brian Mellor. The latter identity seems to have been fabricated, or at least there is no evidence that a person with this name ever worked at Nerdify. Rather, it appears that the SMS assistance company co-founded by Messrs. Pokatilo and Perkon (Awesome Technologies) fizzled out shortly after its creation, and that Nerdify soon adopted the process of accepting assignment requests via text message and routing them to freelance writers. A closer look at an early “About Us” page for Nerdify in The Wayback Machine suggests that Mr. Perkon was the real co-founder of the company: The photo at the top of the page shows four people wearing Nerdify T-shirts seated around a table on a rooftop deck in San Francisco, and the man facing the camera is Perkon. Filip Perkon, top right, is pictured wearing a Nerdify T-shirt in an archived copy of the company’s About Us page. Image: archive.org. Where are they now? Pokatilo is currently running a startup called Litero.Ai, which appears to be an AI-based essay writing service. In July 2025, Mr. Pokatilo received pre-seed funding of $800,000 for Litero from an investment program backed by the venture capital firms AltaIR Capital, Yellow Rocks, Smart Partnership Capital, and I2BF Global Ventures. Meanwhile, Filip Perkon is busy setting up toy rubber duck stores in Miami and in at least three locations in the United Kingdom. These “Duck World” shops market themselves as “the world’s largest duck store.” This past week, Mr. Lobov was in India with Putin’s entourage on a charm tour with India’s Prime Minister Narendra Modi. Although Synergy is billed as an educational institution, a review of the company’s sprawling corporate footprint (via DNS) shows it also is assisting the Russian government in its war against Ukraine. Synergy University President Vadim Lobov (right) pictured this week in India next to Natalia Popova, a Russian TV presenter known for her close ties to Putin’s family, particularly Putin’s daughter, who works with Popova at the education and culture-focused Innopraktika Foundation. The website bpla.synergy[.]bot, for instance, says the company is involved in developing combat drones to aid Russian forces and to evade international sanctions on the supply and re-export of high-tech products. A screenshot from the website of synergy,bot shows the company is actively engaged in building armed drones for the war in Ukraine. KrebsOnSecurity would like to thank the anonymous researcher NatInfoSec for their assistance in this investigation. View the full article

Can Daniel Farke's Peacocks pull off another upset at Elland Road?View the full article

You'd expect things to be starting to wind down for the holidays by now, but that doesn't seem to be the case yet in the world of Apple news, with Apple just about ready to release iOS 26.2 and other operating system updates to the public. There was also a flurry of news this week about Apple executive departures, some expected and some not so expected, while we also learned that Apple and Intel may be developing a new chipmaking partnership, so read on below for all the details on these stories and more! Top Stories Apple Seeds iOS 26.2 Release Candidate Ahead of Public Launch With the Thanksgiving holiday in the rear-view mirror and the calendar turned to December, Apple is putting the final touches on iOS 26.2, iPadOS 26.2, macOS Tahoe 26.2, and related updates, with several new features and tweaks. Apple this week seeded release candidate versions of the updates to developers and public beta testers, suggesting an official release for everyone will come next week. The imminent iOS 26.2 update arrives as Apple has started to more aggressively push users still on iOS 18 to upgrade to iOS 26. Since ‌iOS 26‌ launched in September, it has been displayed as an optional upgrade at the bottom of the Software Update interface in the Settings app, with iOS 18 updates displayed more prominently. Starting this week, that's changed. iOS 18 users who have not upgraded to ‌iOS 26 now see iOS 26.1 (and soon iOS 26.2) as the recommended iOS update in the Settings app. iOS 18 updates are still an option, but are now displayed at the bottom of the app. Apple UI Design Chief Alan Dye Leaving for Meta In a move that came as a surprise to most observers, Apple design chief Alan Dye has decided to leave the company after 19 years and take a role as chief design officer at Meta. Dye oversaw the major Liquid Glass design update that debuted this year, which has not arrived without controversy, and some both inside and outside of Apple are not exactly sorry to see Dye go. Dye's departure follows closely on the heels of Apple announcing that AI chief John Giannandrea has stepped down from his position and will serve as an advisor until he retires early next year. Giannandrea has been under pressure as Apple has fallen behind in the race to develop and deploy AI capabilities, and some of his responsibilities had already been shifted to other executives. As if that wasn't enough, Apple also announced this week that general counsel Kate Adams and environment chief Lisa Jackson will both be retiring in 2026, with the company working to transition their responsibilities to other executives. Apple and Intel Rumored to Partner on Mac and iPhone Chips in a New Way While all Macs are now powered by Apple's custom-designed chips, a new rumor claims that Apple may rekindle its partnership with Intel, albeit in a new and limited way. Apple supply chain analyst Ming-Chi Kuo this week said Intel is expected to begin shipping Apple's lowest-end M-series chip as early as mid-2027. If this rumor proves accurate, Intel could supply Apple with M6 or M7 chips for future MacBook Air, iPad Air, and iPad Pro models at a minimum. However, while previous Intel chips for Macs were designed by Intel and based on x86 architecture, M-series chips are designed by Apple and use Arm architecture. Intel would only assist with manufacturing. The partnership may also extend to the iPhone with Intel producing future chips for non-pro iPhone models starting in 2028, which could perhaps mean the A22 chip for devices like the iPhone 20 and iPhone 20e. iPhone Fold: Launch, Pricing, and What to Expect From Apple's Foldable Apple is expected to launch a new foldable iPhone next year, based on multiple rumors and credible sources. The long-awaited device has been rumored for years now, but signs increasingly suggest that 2026 could indeed be the year that Apple releases its first foldable device. As rumors continue to surface, we've collated an updated set of key details that have been leaked about Apple's foldable iPhone so far. Apple will allegedly call the device the "‌iPhone‌ Fold," which is the name the media has already adopted when sharing rumors about the product. Apple Music Replay 2025 Now Fully Available The full Replay 2025 experience is now available in the Apple Music app, allowing you to reflect on your listening habits over the past year. There are two main components of the Replay 2025 experience. First, there is a full year-end playlist containing the Apple Music songs that you listened to the most over the past year, and second, there is a Highlight Reel with images and a video that are designed to be shared on social media platforms like Instagram and TikTok. iPhone 17 Demand Is Breaking Apple's Sales Records Apple's iPhone 17 lineup is selling well enough that Apple is on track to ship more than 247.4 million total iPhones in 2025, according to a new report from IDC. Total 2025 shipments are forecast to grow 6.1 percent year over year due to ‌iPhone 17‌ demand and increased sales in China, a major market for Apple. Overall worldwide smartphone shipments across Android and iOS are forecast to grow 1.5 percent, primarily because of the success of the iPhone. MacRumors Newsletter Each week, we publish an email newsletter like this highlighting the top Apple stories, making it a great way to get a bite-sized recap of the week hitting all of the major topics we've covered and tying together related stories for a big-picture view. So if you want to have top stories like the above recap delivered to your email inbox each week, subscribe to our newsletter!Tag: Top Stories This article, "Top Stories: iOS 26.2 Coming Soon, Apple Execs Depart, and More" first appeared on MacRumors.com Discuss this article in our forums View the full article

Spotify’s annual Wrapped feature just dropped, giving listeners a fun, personalized summary of their listening habits. It has gained immense popularity over the years, and as a result, many companies have seized the opportunity to create similar year-in-review experiences, offering users a recap of their habits, preferences, or interactions from the past year. Here are […]View the full article

This premium gaming handheld loads up with features, but Windows still holds it back from being the easy option.View the full article

Check out these expert recommendations and when you should be hopping on the scale.View the full article

If you're on the hunt for a toy that won't get forgotten the minute it's unwrapped, check out this expert-curated list. It's got toys designed for every age and interest.View the full article

Pep Guardiola's Cityzens welcome the high-flying Black Cats to the Etihad Stadium.View the full article

Two teams looking to bounce back from midweek defeats meet at the Vitality Stadium.View the full article

Both phones are amazing, but which one takes better photos? As a professional photographer, I wanted to find out.View the full article

Because of shifting storms and sweltering summers, Iran’s capital faces a future “Day Zero” when the taps run dry.View the full article

If you work with artificial intelligence anywhere in the United States—in cities like California, San Francisco, Boston, or Seattle—you understand the challenge: building an impressive AI model is an achievement, but making it work consistently in real-world applications is an entirely different story. That critical gap between AI development and practical implementation is exactly where MLOps proves essential. To gain mastery of these vital skills, consider exploring MLOps Training in the United States, California, San Francisco, Boston & Seattle. Understanding MLOps in Simple Terms MLOps stands for Machine Learning Operations. It is the discipline of applying proven DevOps methodologies to the complete lifecycle of machine learning projects. Imagine it as the essential framework that transforms promising AI prototypes into robust, scalable, and maintainable production systems. Without MLOps, even the most sophisticated AI models encounter significant hurdles: they may excel in controlled testing environments but fail under real-world conditions, or their performance may degrade silently over time due to data drift, all while manual processes create bottlenecks and hinder team collaboration. The Growing Need for MLOps Across U.S. Industries Organizations nationwide, from Silicon Valley startups to established enterprises in Boston and Seattle, are accelerating their AI adoption. A common realization is that model development is merely the first step. The greater challenge lies in operationalization: ensuring reliable daily performance, maintaining models over time, scaling solutions effectively, enforcing governance, and fostering seamless teamwork between data scientists and engineers. This operational challenge is precisely why comprehensive MLOps training has transitioned from a niche advantage to a business necessity. It provides the methodology and tools to ensure AI investments deliver tangible, sustainable value. The MLOps Transformation: A Clear Comparison Adopting MLOps fundamentally reshapes how an organization manages its AI initiatives. The contrast between traditional approaches and the MLOps methodology is stark and telling: Traditional AI DevelopmentThe MLOps MethodologySiloed work by data scientistsCross-functional MLOps teams in collaborationManual, inconsistent deploymentsAutomated, reproducible CI/CD pipelinesMinimal monitoring post-launchProactive, continuous model monitoringArchitectures difficult to scaleSystems designed for efficient model serving at scaleLimited traceability and governanceComprehensive model versioning and experiment tracking Core Competencies from Quality MLOps Training A well-structured training program should equip you with both foundational knowledge and hands-on skills. Key learning areas typically include: Foundations & Lifecycle: Grasping the core principles of MLOps and understanding the end-to-end machine learning lifecycle, from data and experimentation to deployment, monitoring, and retirement. Pipeline Engineering: Learning to build automated, reproducible pipelines for data, training, and validation using modern orchestration tools. Deployment & Serving: Mastering patterns for deploying models as APIs or batch processes, often leveraging containerization and orchestration platforms like Kubernetes. Monitoring, Governance & Ethics: Implementing systems to track model performance, detect data drift, and ensure robust model governance and fairness. Cloud-Native MLOps: Effectively utilizing cloud platforms for scalable, managed infrastructure tailored for machine learning workloads. Accelerating Learning with Expert Guidance The MLOps landscape is dynamic and complex. Navigating its evolving tools and best practices alone can be inefficient. This is where learning from an established, practical source provides significant advantage. For those seeking to build these competencies, DevOpsSchool offers a structured, practical approach to mastering in-demand technologies. Their training focuses on real-world application, connecting theoretical concepts directly to workplace scenarios. The Advantage of Learning from an Industry Veteran The depth and applicability of any MLOps training are profoundly influenced by the expertise of its instructors. Guidance from a practitioner with extensive real-world experience transforms theoretical knowledge into actionable skill. The curriculum is guided by Rajesh Kumar, whose expertise is grounded in over two decades of hands-on experience across the spectrum of modern IT practices—from DevOps and DevSecOps to SRE, DataOps, AIOps, and MLOps. His deep practical knowledge of Kubernetes and cloud architectures provides learners with a holistic, strategic understanding of implementing MLOps within a broader technology ecosystem. Identifying the Right Path for Your Career For data scientists, ML engineers, DevOps professionals, software developers, and technology leaders in the United States, proficiency in MLOps is a powerful career differentiator. It represents the ability to bridge the gap between AI innovation and production-grade delivery, a skill set in high demand across the competitive markets of California, Boston, Seattle, and beyond. Taking the First Step Embarking on the journey to MLOps mastery begins with a commitment to structured learning. Assess your current knowledge, define your learning objectives, and explore training pathways that offer a blend of theory, hands-on practice, and expert mentorship. Ready to translate AI potential into production reality? Building genuine MLOps competency is an investment that yields substantial returns in capability and career advancement. To explore how you can develop these critical skills: Email: [email protected] Phone & WhatsApp (India): +91 84094 92687 Phone & WhatsApp (USA): +1 (469) 756-6329 Website: https://www.devopsschool.com/ View the full article

The U.S. Cybersecurity and Infrastructure Security Agency (CISA) on Friday formally added a critical security flaw impacting React Server Components (RSC) to its Known Exploited Vulnerabilities (KEV) catalog following reports of active exploitation in the wild. The vulnerability, CVE-2025-55182 (CVSS score: 10.0), relates to a case of remote code execution that could be triggered by anView the full article

If you work with AI in the UK, especially in London, you’ve likely felt this pattern: You build an impressive model in testing, but then struggle to make it work reliably in real business situations. That gap between building and using AI is exactly where MLOps makes all the difference. MLOps Training in the United Kingdom and London helps you turn experimental AI into dependable, everyday tools. It’s the practical system that makes AI work not just in the lab, but in the real world. Why UK Companies Need MLOps The UK, with London at the heart of its tech scene, is full of businesses wanting to use AI. But many face the same issues: Models that work perfectly in testing but fail in real use AI performance that slowly gets worse over time Slow, manual processes that waste time Confusion over which model version is being used Teams struggling to work together effectively Learning MLOps gives you clear, practical methods to solve these problems and build AI systems that actually work. MLOps in Practice: Before and After When companies start using MLOps, their approach to AI changes completely: Traditional ApproachWith MLOpsTeams work separatelyTeams collaborate betterManual, slow deploymentsAutomated, efficient processesNo monitoring after launchContinuous performance trackingDifficult to scaleEasy to grow successful modelsHard to repeat resultsClear records and reproducibility MLOps treats AI like a product that needs ongoing care, not just a one-time project. What You’ll Learn in Good MLOps Training Quality training should give you skills you can use right away: Core Understanding What MLOps really means and why it matters How it fits with other technical work The complete AI lifecycle Building Systems Creating automated workflows that save time Using tools to organize complex projects Making processes repeatable and reliable Deployment Skills How to safely launch models into use Different methods for making models available Modern tools for reliable service Monitoring and Maintenance Setting up systems to watch model performance Finding and fixing problems early Knowing when to update models Best Practices Industry standards that save time Common mistakes to avoid Practical tips from experienced professionals Finding the Right Learning Resources MLOps changes fast, with new tools appearing regularly. Trying to learn everything yourself can be overwhelming. This is where structured learning helps. A platform like DevOpsSchool focuses on making complex technical topics practical and accessible. They provide training that connects theory with real workplace situations. Learning from Real Experience The best training comes from people who have actually used these tools in real projects. That practical experience makes all the difference. The MLOps training program is guided by Rajesh Kumar, who brings over twenty years of hands-on experience with technology systems. His background includes practical work with: DevOps practices Cloud platforms Machine learning systems Learning from experienced professionals means you get: Real-world knowledge from actual projects Practical methods proven in business environments Clear explanations of complex concepts Current expertise with the latest tools Career Benefits of Learning MLOps If you work with AI, data, or technology in the UK, learning MLOps offers clear advantages: For Your Current Role Makes your work more efficient Helps solve complex problems better Increases your value to your team For Career Growth Builds skills that are in high demand Opens new job opportunities Prepares you for leadership roles For Your Organization Enables better AI development Increases project success rates Saves time and reduces errors Getting Started with MLOps Ready to begin? Here’s a simple path: Learn the basics of MLOps concepts Try small projects with real applications Connect with others using MLOps Consider formal training to accelerate learning Stay current with new developments Ready to build better AI systems? Developing MLOps skills requires focus, but the investment pays off in better results and career opportunities. Interested in structured training options? Get in touch to learn more: Email: [email protected] Phone & WhatsApp (India): +91 84094 92687 Phone & WhatsApp (USA): +1 (469) 756-6329 Website: https://www.devopsschool.com/ View the full article

This robot is designed to do your chores, but it might need help from a remote human operator.View the full article

Canyon’s latest off-road helmet is the first bike helmet in the United States to feature RLS’s game-changing safety tech.View the full article

Plus: The Trump administration declines to issue sanctions over Salt Typhoon’s hacking spree, officials warn of a disturbingly stealthy Chinese malware specimen, and more.View the full article

We tested dozens of Android phones and picked a handful that you should buy, like the Galaxy S25, Pixel 10 Pro, Galaxy Z Fold 7 and Motorola Razr Ultra.View the full article

This no-frills device is good, but chintzy accessories and a borderline dangerous frother keep it from being great.View the full article

Plus: Samsung’s tri-folding phone unfurls to the size of a tablet, and Kobo has a new remote page-turner.View the full article

The Epson Flex Plus projector could actually double as a lamp. A lamp that also streams Netflix.View the full article

If you work with machine learning or artificial intelligence in the Netherlands, especially in places like Amsterdam, you might have noticed a common problem. It’s easy to build a smart model in a testing environment, but much harder to get it working reliably in a real business. This gap between creating a model and using it in practice is exactly where MLOps Training in the Netherlands and Amsterdam becomes important. MLOps, or Machine Learning Operations, is a set of practices that helps manage machine learning projects from start to finish. Think of it as a system that turns AI experiments into reliable, working tools that businesses can use every day. Why MLOps Matters for Companies in the Netherlands The Netherlands has a growing tech industry, with Amsterdam at its center. Many companies here want to use AI to improve their work. But without a good system in place, they often run into problems: Models that work in testing but fail in real use AI performance that gets worse over time Manual processes that take too long and make errors Difficulty keeping track of different model versions This is where learning about MLOps can help. It provides clear methods to build better, more reliable AI systems. What Changes When You Use MLOps When companies start using MLOps practices, their approach to AI changes significantly: Traditional ApproachWith MLOpsTeams work separatelyTeams collaborate betterManual deploymentAutomated processesNo monitoring after launchContinuous performance trackingHard to scaleEasier to grow successful modelsDifficult to repeat resultsClear tracking of all work Using MLOps means treating AI projects like products that need regular care and improvement, rather than one-time experiments. What Good MLOps Training Should Teach You If you’re thinking about learning MLOps, look for training that covers practical skills you can use right away: Basic Concepts: Understanding what MLOps is and why it matters Building Workflows: Learning to create smooth, automated processes Deployment Skills: Knowing how to launch models reliably Monitoring Methods: Setting up systems to watch model performance Best Practices: Learning industry standards and common solutions This knowledge helps everyone involved in AI projects—from data scientists to IT managers—work together more effectively. Finding the Right Learning Resources The field of MLOps changes often, with new tools and methods appearing regularly. Finding your way through all this information can be challenging. This is where good learning resources make a big difference. A platform like DevOpsSchool focuses on making complex technical topics easier to understand and use. They provide practical training that connects theory with real workplace situations. Learning from Experienced Teachers The quality of any training depends greatly on who’s teaching it. Having instructors with real-world experience can help you understand not just what to do, but why certain approaches work best. The MLOps training program is guided by Rajesh Kumar, who has over twenty years of experience working with technology systems. His background includes practical work with DevOps, cloud technologies, and machine learning systems. Learning from someone with this experience provides valuable insights into how to implement solutions that work in real business situations. Is MLOps Training Right for Your Career? If you work with AI, data, or technology systems in the Netherlands, learning about MLOps could be a smart career move. These skills help you build AI solutions that aren’t just clever, but also reliable and practical—exactly what companies need. Ready to learn how to make AI systems work better in practice? Developing MLOps skills requires focused learning and practice. If you’re interested in learning more about structured training options: Email: [email protected] Phone & WhatsApp (India): +91 84094 92687 Phone & WhatsApp (USA): +1 (469) 756-6329 Website: https://www.devopsschool.com/ View the full article

If you work with machine learning in cities like Bangalore, Hyderabad, or Chennai, you know it’s not just about building smart models. The real challenge starts when you try to use those models in real business situations. That moment—when a great model moves from the lab to the real world—is where MLOps Training in India, Bangalore, Hyderabad, and Chennai becomes essential. Think of MLOps (Machine Learning Operations) as the bridge between data science and real-world use. It’s like taking a brilliant idea and turning it into something that works reliably day after day. Without proper MLOps, even the smartest AI models can fail in practice. They might work perfectly in testing but struggle when people actually use them. The Real Problem MLOps Solves Across India’s tech centers—from the startups in Bangalore to the IT parks in Hyderabad and the growing tech scene in Chennai—teams face similar challenges: Models that work in the lab but fail in real use “Model drift” where AI performance gets worse over time Teams spending more time fixing problems than creating new solutions Difficulty scaling successful models across an organization MLOps addresses these issues by creating systems that manage the entire lifecycle of machine learning models. It’s what turns experimental AI into reliable business tools. Why Indian Companies Need MLOps Now India’s technology sector is growing fast, and AI is becoming crucial across industries. Whether you’re working at a tech company in Bangalore, a financial firm in Chennai, or a startup in Hyderabad, the pressure to deliver working AI solutions is real. Here’s what changes when you implement MLOps: Traditional ApproachWith MLOpsModels built in isolationComplete workflow automationManual deployment processesAutomated model deploymentNo system to track performanceContinuous model monitoringTeams work separatelyBetter team collaborationDifficult to scaleEfficient model scaling What Good MLOps Training Should Cover Learning MLOps isn’t just about understanding concepts—it’s about gaining practical skills you can use immediately. A comprehensive program for MLOps Training in India, Bangalore, Hyderabad, and Chennai should include: Core Concepts: Understanding what MLOps really means and why it matters Workflow Management: Learning to create smooth, automated processes Version Control: Mastering how to track and reproduce your work Deployment Skills: Learning to deploy models reliably and at scale Monitoring Systems: Setting up ways to watch model performance continuously Best Practices: Understanding industry standards and avoiding common mistakes For professionals in India, especially in tech hubs like Bangalore, Hyderabad, and Chennai, this training provides the fastest path to turning AI projects into real business value. Finding the Right Learning Path The field of MLOps is constantly evolving with new tools and techniques emerging regularly. Navigating this landscape alone can be challenging. This is where having the right guidance makes all the difference. Learning with DevOpsSchool For those seeking practical, effective MLOps training in India, there are structured programs designed specifically for Indian tech professionals. DevOpsSchool has established itself as a trusted platform for technology education, particularly for in-demand skills like MLOps. Their approach focuses on practical, hands-on learning that translates directly to workplace success. What makes DevOpsSchool particularly effective is their commitment to current industry practices. They regularly update their curriculum to reflect the latest tools and methodologies used in Indian tech companies, ensuring that what you learn is immediately applicable in your job. Their programs are designed with flexibility in mind, accommodating working professionals across different cities in India. Guidance from an Experienced Professional The value of any educational program depends greatly on the experience of those leading it. In the case of MLOps training, learning from someone with extensive real-world experience can make a significant difference in how well you understand and apply the concepts. The MLOps training is guided by Rajesh Kumar, a professional with over 20 years of experience across various technology domains. His background encompasses practical work with DevOps, DevSecOps, Kubernetes, and cloud technologies, giving him a comprehensive understanding of how MLOps fits within the broader technology landscape. Learning from Rajesh Kumar means gaining insights not just from theoretical knowledge, but from real implementation experience that has been tested and proven in actual business environments. Is MLOps Training Right for Your Career? If you’re a data scientist, machine learning engineer, DevOps professional, or technology leader in India looking to bridge the gap between AI development and practical implementation, MLOps Training in India, Bangalore, Hyderabad, and Chennai represents a valuable investment in your career. It equips you with the skills to build systems that are not just intelligent but also reliable, scalable, and manageable—exactly what businesses need as they adopt AI technologies. Taking the Next Step Moving from understanding AI concepts to implementing successful AI systems requires specific knowledge and skills. For professionals in Bangalore, Hyderabad, Chennai, and across India, acquiring these skills through structured learning can accelerate career growth and increase your value to employers. For those interested in exploring MLOps training options suitable for the Indian market: Email: [email protected] Phone & WhatsApp (India): +91 84094 92687 Phone & WhatsApp (USA): +1 (469) 756-6329 Website: https://www.devopsschool.com/ View the full article