#cloud computing for data science

[mostlysignssomeportents]

Cloudburst

Enshittification isn’t inevitable: under different conditions and constraints, the old, good internet could have given way to a new, good internet. Enshittification is the result of specific policy choices: encouraging monopolies; enabling high-speed, digital shell games; and blocking interoperability.

First we allowed companies to buy up their competitors. Google is the shining example here: having made one good product (search), they then fielded an essentially unbroken string of in-house flops, but it didn’t matter, because they were able to buy their way to glory: video, mobile, ad-tech, server management, docs, navigation…They’re not Willy Wonka’s idea factory, they’re Rich Uncle Pennybags, making up for their lack of invention by buying out everyone else:

https://locusmag.com/2022/03/cory-doctorow-vertically-challenged/

But this acquisition-fueled growth isn’t unique to tech. Every administration since Reagan (but not Biden! more on this later) has chipped away at antitrust enforcement, so that every sector has undergone an orgy of mergers, from athletic shoes to sea freight, eyeglasses to pro wrestling:

https://www.whitehouse.gov/cea/written-materials/2021/07/09/the-importance-of-competition-for-the-american-economy/

But tech is different, because digital is flexible in a way that analog can never be. Tech companies can “twiddle” the back-ends of their clouds to change the rules of the business from moment to moment, in a high-speed shell-game that can make it impossible to know what kind of deal you’re getting:

https://pluralistic.net/2023/02/27/knob-jockeys/#bros-be-twiddlin

To make things worse, users are banned from twiddling. The thicket of rules we call IP ensure that twiddling is only done against users, never for them. Reverse-engineering, scraping, bots — these can all be blocked with legal threats and suits and even criminal sanctions, even if they’re being done for legitimate purposes:

https://locusmag.com/2020/09/cory-doctorow-ip/

Enhittification isn’t inevitable but if we let companies buy all their competitors, if we let them twiddle us with every hour that God sends, if we make it illegal to twiddle back in self-defense, we will get twiddled to death. When a company can operate without the discipline of competition, nor of privacy law, nor of labor law, nor of fair trading law, with the US government standing by to punish any rival who alters the logic of their service, then enshittification is the utterly foreseeable outcome.

To understand how our technology gets distorted by these policy choices, consider “The Cloud.” Once, “the cloud” was just a white-board glyph, a way to show that some part of a software’s logic would touch some commodified, fungible, interchangeable appendage of the internet. Today, “The Cloud” is a flashing warning sign, the harbinger of enshittification.

When your image-editing tools live on your computer, your files are yours. But once Adobe moves your software to The Cloud, your critical, labor-intensive, unrecreatable images are purely contingent. At at time, without notice, Adobe can twiddle the back end and literally steal the colors out of your own files:

https://pluralistic.net/2022/10/28/fade-to-black/#trust-the-process

The finance sector loves The Cloud. Add “The Cloud” to a product and profits (money you get for selling something) can turn into rents (money you get for owning something). Profits can be eroded by competition, but rents are evergreen:

https://pluralistic.net/2023/07/24/rent-to-pwn/#kitt-is-a-demon

No wonder The Cloud has seeped into every corner of our lives. Remember your first iPod? Adding music to it was trivial: double click any music file to import it into iTunes, then plug in your iPod and presto, synched! Today, even sophisticated technology users struggle to “side load” files onto their mobile devices. Instead, the mobile duopoly — Apple and Google, who bought their way to mobile glory and have converged on the same rent-seeking business practices, down to the percentages they charge — want you to get your files from The Cloud, via their apps. This isn’t for technological reasons, it’s a business imperative: 30% of every transaction that involves an app gets creamed off by either Apple or Google in pure rents:

https://www.kickstarter.com/projects/doctorow/red-team-blues-another-audiobook-that-amazon-wont-sell/posts/3788112

And yet, The Cloud is undeniably useful. Having your files synch across multiple devices, including your collaborators’ devices, with built-in tools for resolving conflicting changes, is amazing. Indeed, this feat is the holy grail of networked tools, because it’s how programmers write all the software we use, including software in The Cloud.

If you want to know how good a tool can be, just look at the tools that toolsmiths use. With “source control” — the software programmers use to collaboratively write software — we get a very different vision of how The Cloud could operate. Indeed, modern source control doesn’t use The Cloud at all. Programmers’ workflow doesn’t break if they can’t access the internet, and if the company that provides their source control servers goes away, it’s simplicity itself to move onto another server provider.

This isn’t The Cloud, it’s just “the cloud” — that whiteboard glyph from the days of the old, good internet — freely interchangeable, eminently fungible, disposable and replaceable. For a tool like git, Github is just one possible synchronization point among many, all of which have a workflow whereby programmers’ computers automatically make local copies of all relevant data and periodically lob it back up to one or more servers, resolving conflicting edits through a process that is also largely automated.

There’s a name for this model: it’s called “Local First” computing, which is computing that starts from the presumption that the user and their device is the most important element of the system. Networked servers are dumb pipes and dumb storage, a nice-to-have that fails gracefully when it’s not available.

The data structures of source-code are among the most complicated formats we have; if we can do this for code, we can do it for spreadsheets, word-processing files, slide-decks, even edit-decision-lists for video and audio projects. If local-first computing can work for programmers writing code, it can work for the programs those programmers write.

Local-first computing is experiencing a renaissance. Writing for Wired, Gregory Barber traces the history of the movement, starting with the French computer scientist Marc Shapiro, who helped develop the theory of “Conflict-Free Replicated Data” — a way to synchronize data after multiple people edit it — two decades ago:

https://www.wired.com/story/the-cloud-is-a-prison-can-the-local-first-software-movement-set-us-free/

Shapiro and his co-author Nuno Preguiça envisioned CFRD as the building block of a new generation of P2P collaboration tools that weren’t exactly serverless, but which also didn’t rely on servers as the lynchpin of their operation. They published a technical paper that, while exiting, was largely drowned out by the release of GoogleDocs (based on technology built by a company that Google bought, not something Google made in-house).

Shapiro and Preguiça’s work got fresh interest with the 2019 publication of “Local-First Software: You Own Your Data, in spite of the Cloud,” a viral whitepaper-cum-manifesto from a quartet of computer scientists associated with Cambridge University and Ink and Switch, a self-described “industrial research lab”:

https://www.inkandswitch.com/local-first/static/local-first.pdf

The paper describes how its authors — Martin Kleppmann, Adam Wiggins, Peter van Hardenberg and Mark McGranaghan — prototyped and tested a bunch of simple local-first collaboration tools built on CFRD algorithms, with the goal of “network optional…seamless collaboration.” The results are impressive, if nascent. Conflicting edits were simpler to resolve than the authors anticipated, and users found URLs to be a good, intuitive way of sharing documents. The biggest hurdles are relatively minor, like managing large amounts of change-data associated with shared files.

Just as importantly, the paper makes the case for why you’d want to switch to local-first computing. The Cloud is not reliable. Companies like Evernote don’t last forever — they can disappear in an eyeblink, and take your data with them:

https://www.theverge.com/2023/7/9/23789012/evernote-layoff-us-staff-bending-spoons-note-taking-app

Google isn’t likely to disappear any time soon, but Google is a graduate of the Darth Vader MBA program (“I have altered the deal, pray I don’t alter it any further”) and notorious for shuttering its products, even beloved ones like Google Reader:

https://www.theverge.com/23778253/google-reader-death-2013-rss-social

And while the authors don’t mention it, Google is also prone to simply kicking people off all its services, costing them their phone numbers, email addresses, photos, document archives and more:

https://pluralistic.net/2022/08/22/allopathic-risk/#snitches-get-stitches

There is enormous enthusiasm among developers for local-first application design, which is only natural. After all, companies that use The Cloud go to great lengths to make it just “the cloud,” using containerization to simplify hopping from one cloud provider to another in a bid to stave off lock-in from their cloud providers and the enshittification that inevitably follows.

The nimbleness of containerization acts as a disciplining force on cloud providers when they deal with their business customers: disciplined by the threat of losing money, cloud companies are incentivized to treat those customers better. The companies we deal with as end-users know exactly how bad it gets when a tech company can impose high switching costs on you and then turn the screws until things are almost-but-not-quite so bad that you bolt for the doors. They devote fantastic effort to making sure that never happens to them — and that they can always do that to you.

Interoperability — the ability to leave one service for another — is technology’s secret weapon, the thing that ensures that users can turn The Cloud into “the cloud,” a humble whiteboard glyph that you can erase and redraw whenever it suits you. It’s the greatest hedge we have against enshittification, so small wonder that Big Tech has spent decades using interop to clobber their competitors, and lobbying to make it illegal to use interop against them:

https://locusmag.com/2019/01/cory-doctorow-disruption-for-thee-but-not-for-me/

Getting interop back is a hard slog, but it’s also our best shot at creating a new, good internet that lives up the promise of the old, good internet. In my next book, The Internet Con: How to Seize the Means of Computation (Verso Books, Sept 5), I set out a program fro disenshittifying the internet:

https://www.versobooks.com/products/3035-the-internet-con

The book is up for pre-order on Kickstarter now, along with an independent, DRM-free audiobooks (DRM-free media is the content-layer equivalent of containerized services — you can move them into or out of any app you want):

http://seizethemeansofcomputation.org

Meanwhile, Lina Khan, the FTC and the DoJ Antitrust Division are taking steps to halt the economic side of enshittification, publishing new merger guidelines that will ban the kind of anticompetitive merger that let Big Tech buy its way to glory:

https://www.theatlantic.com/ideas/archive/2023/07/biden-administration-corporate-merger-antitrust-guidelines/674779/

The internet doesn’t have to be enshittified, and it’s not too late to disenshittify it. Indeed — the same forces that enshittified the internet — monopoly mergers, a privacy and labor free-for-all, prohibitions on user-side twiddling — have enshittified everything from cars to powered wheelchairs. Not only should we fight enshittification — we must.

Back my anti-enshittification Kickstarter here!

If you’d like an essay-formatted version of this post to read or share, here’s a link to it on pluralistic.net, my surveillance-free, ad- free, tracker-free blog:

https://pluralistic.net/2023/08/03/there-is-no-cloud/#only-other-peoples-computers

Image: Drahtlos (modified) https://commons.wikimedia.org/wiki/File:Motherboard_Intel_386.jpg

CC BY-SA 4.0 https://creativecommons.org/licenses/by-sa/4.0/deed.en

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cdsessums (modified) https://commons.wikimedia.org/wiki/File:Monsoon_Season_Flagstaff_AZ_clouds_storm.jpg

CC BY-SA 2.0 https://creativecommons.org/licenses/by-sa/2.0/deed.en

[bigleapblog]

Your Guide to B.Tech in Computer Science & Engineering Colleges

In today's technology-driven world, pursuing a B.Tech in Computer Science and Engineering (CSE) has become a popular choice among students aspiring for a bright future. The demand for skilled professionals in areas like Artificial Intelligence, Machine Learning, Data Science, and Cloud Computing has made computer science engineering colleges crucial in shaping tomorrow's innovators. Saraswati College of Engineering (SCOE), a leader in engineering education, provides students with a perfect platform to build a successful career in this evolving field.

Whether you're passionate about coding, software development, or the latest advancements in AI, pursuing a B.Tech in Computer Science and Engineering at SCOE can open doors to endless opportunities.

Why Choose B.Tech in Computer Science and Engineering?

Choosing a B.Tech in Computer Science and Engineering isn't just about learning to code; it's about mastering problem-solving, logical thinking, and the ability to work with cutting-edge technologies. The course offers a robust foundation that combines theoretical knowledge with practical skills, enabling students to excel in the tech industry.

At SCOE, the computer science engineering courses are designed to meet industry standards and keep up with the rapidly evolving tech landscape. With its AICTE Approved, NAAC Accredited With Grade-"A+" credentials, the college provides quality education in a nurturing environment. SCOE's curriculum goes beyond textbooks, focusing on hands-on learning through projects, labs, workshops, and internships. This approach ensures that students graduate not only with a degree but with the skills needed to thrive in their careers.

The Role of Computer Science Engineering Colleges in Career Development

The role of computer science engineering colleges like SCOE is not limited to classroom teaching. These institutions play a crucial role in shaping students' futures by providing the necessary infrastructure, faculty expertise, and placement opportunities. SCOE, established in 2004, is recognized as one of the top engineering colleges in Navi Mumbai. It boasts a strong placement record, with companies like Goldman Sachs, Cisco, and Microsoft offering lucrative job opportunities to its graduates.

The computer science engineering courses at SCOE are structured to provide a blend of technical and soft skills. From the basics of computer programming to advanced topics like Artificial Intelligence and Data Science, students at SCOE are trained to be industry-ready. The faculty at SCOE comprises experienced professionals who not only impart theoretical knowledge but also mentor students for real-world challenges.

Highlights of the B.Tech in Computer Science and Engineering Program at SCOE

Comprehensive Curriculum: The B.Tech in Computer Science and Engineering program at SCOE covers all major areas, including programming languages, algorithms, data structures, computer networks, operating systems, AI, and Machine Learning. This ensures that students receive a well-rounded education, preparing them for various roles in the tech industry.

Industry-Relevant Learning: SCOE’s focus is on creating professionals who can immediately contribute to the tech industry. The college regularly collaborates with industry leaders to update its curriculum, ensuring students learn the latest technologies and trends in computer science engineering.

State-of-the-Art Infrastructure: SCOE is equipped with modern laboratories, computer centers, and research facilities, providing students with the tools they need to gain practical experience. The institution’s infrastructure fosters innovation, helping students work on cutting-edge projects and ideas during their B.Tech in Computer Science and Engineering.

Practical Exposure: One of the key benefits of studying at SCOE is the emphasis on practical learning. Students participate in hands-on projects, internships, and industry visits, giving them real-world exposure to how technology is applied in various sectors.

Placement Support: SCOE has a dedicated placement cell that works tirelessly to ensure students secure internships and job offers from top companies. The B.Tech in Computer Science and Engineering program boasts a strong placement record, with top tech companies visiting the campus every year. The highest on-campus placement offer for the academic year 2022-23 was an impressive 22 LPA from Goldman Sachs, reflecting the college’s commitment to student success.

Personal Growth: Beyond academics, SCOE encourages students to participate in extracurricular activities, coding competitions, and tech fests. These activities enhance their learning experience, promote teamwork, and help students build a well-rounded personality that is essential in today’s competitive job market.

What Makes SCOE Stand Out?

With so many computer science engineering colleges to choose from, why should you consider SCOE for your B.Tech in Computer Science and Engineering? Here are a few factors that make SCOE a top choice for students:

Experienced Faculty: SCOE prides itself on having a team of highly qualified and experienced faculty members. The faculty’s approach to teaching is both theoretical and practical, ensuring students are equipped to tackle real-world challenges.

Strong Industry Connections: The college maintains strong relationships with leading tech companies, ensuring that students have access to internship opportunities and campus recruitment drives. This gives SCOE graduates a competitive edge in the job market.

Holistic Development: SCOE believes in the holistic development of students. In addition to academic learning, the college offers opportunities for personal growth through various student clubs, sports activities, and cultural events.

Supportive Learning Environment: SCOE provides a nurturing environment where students can focus on their academic and personal growth. The campus is equipped with modern facilities, including spacious classrooms, labs, a library, and a recreation center.

Career Opportunities After B.Tech in Computer Science and Engineering from SCOE

Graduates with a B.Tech in Computer Science and Engineering from SCOE are well-prepared to take on various roles in the tech industry. Some of the most common career paths for CSE graduates include:

Software Engineer: Developing software applications, web development, and mobile app development are some of the key responsibilities of software engineers. This role requires strong programming skills and a deep understanding of software design.

Data Scientist: With the rise of big data, data scientists are in high demand. CSE graduates with knowledge of data science can work on data analysis, machine learning models, and predictive analytics.

AI Engineer: Artificial Intelligence is revolutionizing various industries, and AI engineers are at the forefront of this change. SCOE’s curriculum includes AI and Machine Learning, preparing students for roles in this cutting-edge field.

System Administrator: Maintaining and managing computer systems and networks is a crucial role in any organization. CSE graduates can work as system administrators, ensuring the smooth functioning of IT infrastructure.

Cybersecurity Specialist: With the growing threat of cyberattacks, cybersecurity specialists are essential in protecting an organization’s digital assets. CSE graduates can pursue careers in cybersecurity, safeguarding sensitive information from hackers.

Conclusion: Why B.Tech in Computer Science and Engineering at SCOE is the Right Choice

Choosing the right college is crucial for a successful career in B.Tech in Computer Science and Engineering. Saraswati College of Engineering (SCOE) stands out as one of the best computer science engineering colleges in Navi Mumbai. With its industry-aligned curriculum, state-of-the-art infrastructure, and excellent placement record, SCOE offers students the perfect environment to build a successful career in computer science.

Whether you're interested in AI, data science, software development, or any other field in computer science, SCOE provides the knowledge, skills, and opportunities you need to succeed. With a strong focus on hands-on learning and personal growth, SCOE ensures that students graduate not only as engineers but as professionals ready to take on the challenges of the tech world.

If you're ready to embark on an exciting journey in the world of technology, consider pursuing your B.Tech in Computer Science and Engineering at SCOE—a college where your future takes shape.

[aarvyedutech]

TOP 10 courses that have generally been in high demand in 2024-

Data Science and Machine Learning: Skills in data analysis, machine learning, and artificial intelligence are highly sought after in various industries.

Cybersecurity: With the increasing frequency of cyber threats, cybersecurity skills are crucial to protect sensitive information.

Cloud Computing: As businesses transition to cloud-based solutions, professionals with expertise in cloud computing, like AWS or Azure, are in high demand.

Digital Marketing: In the age of online businesses, digital marketing skills, including SEO, social media marketing, and content marketing, are highly valued.

Programming and Software Development: Proficiency in programming languages and software development skills continue to be in high demand across industries.

Healthcare and Nursing: Courses related to healthcare and nursing, especially those addressing specific needs like telemedicine, have seen increased demand.

Project Management: Project management skills are crucial in various sectors, and certifications like PMP (Project Management Professional) are highly valued.

Artificial Intelligence (AI) and Robotics: AI and robotics courses are sought after as businesses explore automation and intelligent technologies.

Blockchain Technology: With applications beyond cryptocurrencies, blockchain technology courses are gaining popularity in various sectors, including finance and supply chain.

Environmental Science and Sustainability: Courses focusing on environmental sustainability and green technologies are increasingly relevant in addressing global challenges.

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learn more -

[jcmarchi]

New AI noise-canceling headphone technology lets wearers pick which sounds they hear - Technology Org

New Post has been published on https://thedigitalinsider.com/new-ai-noise-canceling-headphone-technology-lets-wearers-pick-which-sounds-they-hear-technology-org/

New AI noise-canceling headphone technology lets wearers pick which sounds they hear - Technology Org

Most anyone who’s used noise-canceling headphones knows that hearing the right noise at the right time can be vital. Someone might want to erase car horns when working indoors but not when walking along busy streets. Yet people can’t choose what sounds their headphones cancel.

A team led by researchers at the University of Washington has developed deep-learning algorithms that let users pick which sounds filter through their headphones in real time. Pictured is co-author Malek Itani demonstrating the system. Image credit: University of Washington

Now, a team led by researchers at the University of Washington has developed deep-learning algorithms that let users pick which sounds filter through their headphones in real time. The team is calling the system “semantic hearing.” Headphones stream captured audio to a connected smartphone, which cancels all environmental sounds. Through voice commands or a smartphone app, headphone wearers can select which sounds they want to include from 20 classes, such as sirens, baby cries, speech, vacuum cleaners and bird chirps. Only the selected sounds will be played through the headphones.

The team presented its findings at UIST ’23 in San Francisco. In the future, the researchers plan to release a commercial version of the system.

[embedded content]

“Understanding what a bird sounds like and extracting it from all other sounds in an environment requires real-time intelligence that today’s noise canceling headphones haven’t achieved,” said senior author Shyam Gollakota, a UW professor in the Paul G. Allen School of Computer Science & Engineering. “The challenge is that the sounds headphone wearers hear need to sync with their visual senses. You can’t be hearing someone’s voice two seconds after they talk to you. This means the neural algorithms must process sounds in under a hundredth of a second.”

Because of this time crunch, the semantic hearing system must process sounds on a device such as a connected smartphone, instead of on more robust cloud servers. Additionally, because sounds from different directions arrive in people’s ears at different times, the system must preserve these delays and other spatial cues so people can still meaningfully perceive sounds in their environment.

Tested in environments such as offices, streets and parks, the system was able to extract sirens, bird chirps, alarms and other target sounds, while removing all other real-world noise. When 22 participants rated the system’s audio output for the target sound, they said that on average the quality improved compared to the original recording.

In some cases, the system struggled to distinguish between sounds that share many properties, such as vocal music and human speech. The researchers note that training the models on more real-world data might improve these outcomes.

Source: University of Washington

You can offer your link to a page which is relevant to the topic of this post.

[classroomlearning]

BTech CSE: Your Gateway to High-Demand Tech Careers

Apply now for admission and avail the Early Bird Offer

In the digital age, a BTech in Computer Science & Engineering (CSE) is one of the most sought-after degrees, offering unmatched career opportunities across industries. From software development to artificial intelligence, the possibilities are endless for CSE graduates.

Top Job Opportunities for BTech CSE Graduates

Software Developer: Design and develop innovative applications and systems.

Data Scientist: Analyze big data to drive business decisions.

Cybersecurity Analyst: Safeguard organizations from digital threats.

AI/ML Engineer: Lead the way in artificial intelligence and machine learning.

Cloud Architect: Build and maintain cloud-based infrastructure for global organizations.

Why Choose Brainware University for BTech CSE?

Brainware University provides a cutting-edge curriculum, hands-on training, and access to industry-leading tools. Our dedicated placement cell ensures you’re job-ready, connecting you with top recruiters in tech.

👉 Early Bird Offer: Don’t wait! Enroll now and take the first step toward a high-paying, future-ready career in CSE.

Your journey to becoming a tech leader starts here!

[integraluniversity]

List of Best Btech in Artificial Intelligence colleges

The future of a B. Tech in artificial intelligence is promising because the technology is currently transforming all industries. Experts in AI who fulfill the qualifications are highly sought for. Students can pursue careers in artificial intelligence, data science, machine learning, and other fields after completing this course. Students can pursue postgraduate courses, such as the M. Tech in related disciplines, to further their education after earning their B. Tech in Artificial Intelligence. Additionally, they might enroll in a PG certification course or get a PG diploma. One can pursue a lucrative and impactful career with a B. Tech in Artificial Intelligence.

[aiinsight47]

Build AI Tools for Money: Simple Developers Guide

Learn how developers can create and sell AI tools or APIs for profit. Discover steps to identify problems, build solutions, monetize effectively, and grow your AI business.

The world of artificial intelligence (AI) is booming, and developers are uniquely positioned to take advantage of this trend. Creating and selling AI tools or APIs is one of the most lucrative ways to turn your coding skills into a business. Whether you’re solving a niche problem or building tools for broader use, there are endless opportunities in this space. Table of Contents What Are AI Tools…

[codedusoftware]

Empowering Learners with CodEdu’s Industry-Ready Courses

In the ever-evolving world of technology, staying ahead requires continuous learning and skill development. CodEdu Software Technologies, known for its innovative solutions, is also a premier destination for professional training. With courses designed to meet industry demands, CodEdu equips learners with the skills needed to excel in today’s competitive tech landscape.

Explore Our Courses

CodEdu offers a variety of training programs in trending fields, ensuring learners stay ahead in their careers:

Python Full Stack Development Python is one of the most versatile programming languages, and our course covers everything from front-end development (HTML, CSS, JavaScript) to back-end technologies (Django, Flask, and REST APIs). Students work on real-world projects, gaining hands-on experience in building robust applications.

Data Science and Machine Learning Data is the new oil, and CodEdu’s Data Science course ensures learners can extract meaningful insights. Covering tools like Python, R, and Tableau, and concepts like machine learning and data visualization, this program prepares students for high-demand roles in analytics and AI.

Artificial Intelligence Our AI course dives deep into the world of neural networks, natural language processing (NLP), and computer vision. With hands-on training, students learn to build intelligent systems and applications that are shaping the future.

Key Features of CodEdu’s Training Programs

Hands-On Learning We focus on practical training, ensuring students gain real-world experience through live projects and case studies.

Internship Opportunities Every course includes internships, providing learners with valuable industry exposure and the chance to apply their knowledge in real scenarios.

Certification CodEdu offers industry-recognized certificates that validate learners’ expertise and make them stand out in competitive job markets.

Placement Assistance Our dedicated placement team helps students secure jobs in top companies, offering guidance on resume building, interview preparation, and job applications.

Who Can Benefit from CodEdu’s Courses?

Students: Build a strong foundation and gain a competitive edge.

Professionals: Upskill and advance your career in the tech industry.

Career Changers: Transition into high-demand fields like data science, AI, or digital marketing.

Visa Applicants: Utilize gap-filling courses to enhance your resume while awaiting visa approval.

Success Stories

CodEdu has trained over 300+ students, many of whom have gone on to secure lucrative roles in renowned companies. From budding developers to experienced marketers, our programs have transformed countless careers.

Why CodEdu Academy?

Expert Trainers: Learn from industry professionals with years of experience.

Modern Curriculum: Courses designed to meet the latest industry trends and demands.

Flexible Learning: Online and offline classes for your convenience.

Holistic Support: Internship, certification, and placement assistance under one roof.

Whether you’re starting your tech journey or looking to upgrade your skills, CodEdu Software Technologies is your trusted partner in education. Explore our courses and unlock a world of opportunities today!

[dtc-infotech]

From Legacy to Leader: Modernize Your Apps and Drive Business Growth

At DTC Infotech, we understand the challenges businesses face with legacy applications. These systems, while once reliable, can struggle to keep pace with the ever-evolving digital landscape. Here’s where application modernization comes in — a strategic approach to revitalizing your existing applications to unlock their full potential and empower your business for future success.

Why Modernize Your Applications?

The benefits of application modernization are numerous:

Enhanced Agility and Scalability

Modern cloud-based solutions provide the flexibility to easily scale your applications up or down to meet fluctuating demands. This agility allows you to respond quickly to market changes and seize new opportunities.

Improved Performance and Security

Leverage the latest technologies to optimize application performance and strengthen security measures. This translates to a more reliable and secure user experience.

Reduced Costs

Modernization can lead to significant cost savings by eliminating the need to maintain outdated infrastructure and reducing ongoing support expenses.

Increased Innovation

Modern applications provide a robust foundation for further innovation. By integrating cutting-edge technologies like AI and ML, you can unlock new functionalities and create a more competitive edge.

Our 5-Step Application Modernization Strategy

DTC Infotech offers a comprehensive, yet streamlined, approach to application modernization:

Discovery and Assessment

We begin by collaborating with you to understand your business goals and the specific challenges your legacy applications present. Our team will then conduct a thorough assessment of your applications, identifying areas for improvement and compatibility with modern technologies.

2. Modernization Planning

Based on the assessment findings, we’ll develop a customized modernization plan tailored to your unique needs. This plan will outline the specific modernization approach (rehosting, replat forming, or refactoring) that will deliver the most significant benefits.

3. Remediation and Optimization

Our skilled developers will address any compatibility issues or code inefficiencies identified during the assessment. This remediation ensures a smooth transition to the cloud and optimizes your application for peak performance.

4. Cloud Migration

We leverage the power of Microsoft Azure, a leading cloud platform, to seamlessly migrate your applications. Azure offers a robust set of tools and services that ensure a secure and efficient migration process.

5. Continuous Management and Support

Our commitment extends beyond migration. We provide ongoing support and maintenance to ensure your modernized applications remain secure, optimized, and aligned with your evolving business needs.

Why Choose DTC Infotech for Your Application Modernization?

At DTC Infotech, we combine our deep technical expertise with a passion for understanding your business objectives. We believe in a collaborative approach, working closely with you every step of the way to ensure a successful and value-driven modernization journey.

Ready to Modernize?

Don’t let legacy applications hold your business back. Contact DTC Infotech today for a free consultation and unlock the full potential of your applications. Let’s work together to transform your business for the future!

[veridical-technologies]

Cloud Computing simply refers to providing computing services, over the internet when the client demands. In this, client often asks for computing services like- databases, networking, servers, analytics, and storage on the internet. All the data is stored on the servers, which are maintained by the cloud service provider. It is also called Internet-based computing and it is stored files, images, and documents or any other storable files. It delivers the software demanded by the client when it is required and also helps users in easily accessing computing services on the cloud or Internet. Cloud Computing Infrastructure depends on remote network servers hosted on Internet for managing the data and processing the data. Cloud Computing helps in offering various services such as reducing costs, reliability and accessibility, low capital expenditure and increasing efficiency.  In order to access cloud computing service users or clients have to pay. When users or clients save the data on cloud, they can easily access this data anywhere, whenever required.

Cloud provided the Based-on services are divided into: Software-as-a service (SaaS), Platform-as-a service (PaaS), Infrastructure-as-a service (IaaS) and Based on the Deployment cloud divided into: Private Cloud, Public Cloud, and Hybrid Cloud.  Private Cloud computing services are provided on the private network to the particular client, enterprise or organization and is not accessible to everyone.  It provides higher level of security to the company or the organization.   Public Cloud, offers computing services to anyone who wants to purchase or use them over the Internet.  Public Cloud is responsible for managing the files and the data of the client or the enterprise over the Internet. It provides less security because in this everyone can access or use it.  Hybrid Cloud is the combination of both - Public Cloud and Private Cloud. It helps to stop accessing the data or files by the third party or anyone over the Internet and it also provides more security to data management on the cloud.  Infrastructure as a Service is a type of the Cloud Computing, where service provider is responsible for providing computing services. Platform as a Service is also a type of cloud computing, which provides the development and deployment in the cloud and allows users to develop and run the applications without managing the infrastructure. Software as a Service (SaaS) allows users to access Software on cloud on a Subscription basis and doesn’t need to download or install the software in the devices. The top leading Cloud Computing is Amazon Web Services which is the most successful cloud-based business that uses Infrastructure as a Service.

Why Cloud is important?

Cloud is very important because it increases the performance and efficiency of the software, reduces the cost, provides more security and improves quality. When the client wants to access computing service, they have paid less amount to use software on cloud. When an organization uses private cloud, computing services are provided over a private network to the specific client   providing more security as compared to the other types of cloud, and most of the organization uses the private cloud to protect their data. The top leading cloud computing is also using private cloud computing that is most leading cloud computing company and their data is managed on the privately on the cloud. When the client demanded for the service, server has the duty to provide those services to the client on the server or on the Internet. The main reason of the cloud computing is scalability, cost efficiency and accessible. Cloud Computing also provides automatic update facility. By using cloud computing, users can work from anywhere and deliver the products when client demands for the products on the server or on the internet.

Public Cloud Computing, allows everyone to access computing service who wants to purchase or use it over the cloud. This type of cloud computing is not used by the organization because it offers everyone to access cloud computing over the Internet and it provides more security as compared to Private Cloud Computing, but it is used in the small organizations and it is operated by the third party which providing the computing services like servers and storage over the internet. Here all software, hardware and other devices is managed and owned by the service provider. And another type of cloud computing is hybrid combine public and private together allows data to be shared between them and also ensure the security, not allowing everyone to access the data and this is also used by the organization to access computing services.

So, cloud computing helps to increase performance and efficiency along with providing security and helping to reduce the costs.

BY

JAIDEEP SINGH

Student of Veridical Technologies 9319593915 https://www.veridicaltechnologies.com/veritech.php

[infonixon-technologies-blog]

Become A Cloud Engineer - Best Online Training In Bareilly

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[jcmarchi]

The Future of AI for Business Infrastructure: Why Private, Bare-Metal Solutions Powered by Apple Silicon Are Ideal for IT Departments

New Post has been published on https://thedigitalinsider.com/the-future-of-ai-for-business-infrastructure-why-private-bare-metal-solutions-powered-by-apple-silicon-are-ideal-for-it-departments/

The Future of AI for Business Infrastructure: Why Private, Bare-Metal Solutions Powered by Apple Silicon Are Ideal for IT Departments

As businesses, particularly small to medium-sized IT departments, look to incorporate AI into their operations, they face a complex and evolving market. While the promises of AI are exciting, the landscape is filled with uncertainties. Public AI chatbots are widely available but raise significant concerns about data sovereignty and security. SaaS providers are rapidly integrating AI, with new solutions for model training, inference, and data processing emerging daily. Amid these options, private, bare-metal infrastructure powered by Apple Silicon offers a compelling alternative to the uncertainties of shared services and public cloud options as well as offering significant power consumption to traditional GPUs.

The Data is Clear, AI in Enterprises is Rising and Apple Silicon is Poised to Lead

A McKinsey report from August 2023, “The State of AI in 2023: Generative AI’s Breakout Year,” reveals that many organizations are still in the early stages of AI integration and management. While 14-30% of survey respondents across industries use generative AI tools regularly, only about 6% claim their organizations are high-performing in AI. Mainstream organizations struggle with strategy, talent and data management, whereas high-performing AI organizations face challenges with models, talent, and scaling.

A key takeaway from the McKinsey report is that a significant portion of the industry seeks guidance on effectively leveraging AI in professional environments. Developing tailored offerings to meet this need can greatly expand market reach. Additionally, the report found that talent is a persistent challenge, with 20% of respondents identifying it as their primary obstacle. Hiring ML/AI engineers and data scientists is particularly difficult, but organizations are finding more success in recruiting general developers. This suggests that instead of establishing a dedicated AI department, a business analyst and a cross-functional IT team could suffice for testing AI strategies and evaluating their potential value.

Addressing the Core Challenges

One of the most pressing challenges is data security. Public AI chatbots make it too easy for employees to inadvertently share company-specific information, potentially leading to data leaks and a loss of control. Many companies are now seeking in-house, private AI solutions to ensure responsible use of these technologies without risking data exposure.

Furthermore, while SaaS AI features can be useful, they often come with hidden contractual complexities. Many solutions use company data to further train models, which can compromise data sovereignty. Even when data isn’t directly used for training, shared infrastructure across multiple customers poses a risk of data mingling and potential leaks. For businesses handling sensitive information, these risks are simply too high.

Additionally, there is a misconception that leveraging AI requires either extensive data science expertise or a significant investment in computing resources. This complexity can be a barrier for smaller IT teams looking to get started with AI.

By opting for private, bare-metal Apple Silicon-powered solutions, businesses can avoid these pitfalls. Apple Silicon’s unified memory architecture and integrated Neural Engine ensure high performance for AI workloads, including inference tasks, without the need for extensive expertise or overspending on hardware. It also offers predictable costs and energy efficiency, allowing businesses to implement AI solutions with more control and confidence in their infrastructure.

Value Proposition and Use Cases of Apple Silicon-Powered AI Infrastructure

Apple Silicon has quietly emerged as a preferred tech stack for running AI systems, as it can be more efficient than dedicated GPU and x86-backed hardware in several key areas. Its exceptional performance for AI inference tasks stems from the innovative unified memory architecture. This architecture allows the GPU, CPU, and memory to access the same memory pool, significantly reducing latency and improving efficiency when handling large datasets—critical for AI workloads. For example, the Mac Studio’s M2 Ultra chip supports up to 192GB of unified memory with 800GB/s bandwidth, making it ideal for running larger datasets and more complex AI models with ease.

Additionally, the integrated 32-core Neural Engine within Apple Silicon is designed for specific AI operations. By offloading complex AI tasks from the CPU and GPU, this engine accelerates inference times, allowing the system to execute workloads faster.

Beyond performance, Apple Silicon is also renowned for its energy efficiency. It delivers sustained high performance without the high power consumption and heat generation typically associated with traditional CPUs and GPUs. This efficiency makes it a cost-effective solution for businesses looking to integrate AI without overwhelming their infrastructure.

Apple Silicon-powered solutions seamlessly integrate into existing business operations, enabling teams to leverage AI without needing extensive technical expertise. These solutions work with open-source communities and leverage Apple’s unique APIs to streamline the integration process, making AI accessible to developers and businesses alike. Whether generating first drafts of documents, analyzing customer trends, or providing real-time customer service via AI-driven chatbots, Apple Silicon’s infrastructure empowers teams to harness the full potential of AI without compromising data security.

Looking to the Road Ahead

As the AI revolution continues to unfold, enterprises must carefully consider their infrastructure choices. Private, bare-metal solutions powered by Apple Silicon address critical concerns around data privacy, cost predictability and performance consistency while providing a secure and reliable environment for AI inference tasks. For businesses looking to navigate the complexities of AI, these solutions offer a compelling and forward-thinking solution.

[arunseodelhi]

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[mrrayantariq]

Top 10 Highest-Paying Skills in 2024 and How to Learn Them

As we move further into the digital age, certain skills are becoming more valuable and highly sought after in the job market. Here are the top 10 highest-paying skills in 2024 and some resources to help you learn them.

1. Artificial Intelligence (AI) and Machine Learning (ML)

Why It's High-Paying: AI and ML are transforming industries, leading to high demand for experts who can develop intelligent systems and algorithms.

How to Learn:

Coursera: AI For Everyone

edX: Introduction to Artificial Intelligence (AI)

Udacity: Machine Learning Engineer Nanodegree

2. Data Science and Analytics

Why It's High-Paying: Companies rely on data-driven decisions, making data scientists and analysts indispensable for interpreting complex datasets.

How to Learn:

Coursera: Data Science Specialization

Kaggle: Learn Data Science

DataCamp: Data Scientist with Python

3. Cybersecurity

Why It's High-Paying: With increasing cyber threats, cybersecurity experts are essential to protect sensitive information and systems.

How to Learn:

Cybrary: Cybersecurity Courses

Coursera: Introduction to Cyber Security Specialization

SANS: Cybersecurity Training

4. Cloud Computing

Why It's High-Paying: Cloud technologies are critical for modern business operations, driving demand for cloud computing professionals.

How to Learn:

AWS: AWS Training and Certification

Coursera: Google Cloud Platform Fundamentals

Udacity: Cloud Developer Nanodegree

5. Blockchain Technology

Why It's High-Paying: Blockchain's decentralized nature is revolutionizing industries, leading to high demand for blockchain developers and experts.

How to Learn:

Coursera: Blockchain Specialization

edX: Blockchain for Business

Udacity: Blockchain Developer Nanodegree

6. Internet of Things (IoT)

Why It's High-Paying: IoT connects devices and systems, creating a demand for experts who can develop and manage these interconnected systems.

How to Learn:

Coursera: Internet of Things Specialization

edX: IoT for Beginners

Udemy: Internet of Things (IoT) - The Mega Course

7. Software Development

Why It's High-Paying: As the backbone of technological advancements, software developers are in high demand across all industries.

How to Learn:

Coursera: Software Development Lifecycle Specialization

Codecademy: Full-Stack Engineer

Udacity: Full Stack Web Developer Nanodegree

8. Digital Marketing

Why It's High-Paying: Companies need to reach their audience effectively, making digital marketing skills crucial for success.

How to Learn:

Coursera: Digital Marketing Specialization

HubSpot Academy: Digital Marketing Courses

Google Digital Garage: Fundamentals of Digital Marketing

9. Project Management

Why It's High-Paying: Efficient project management ensures that projects are completed on time and within budget, making it a highly valued skill.

How to Learn:

Coursera: Project Management Principles and Practices Specialization

PMI: Project Management Professional (PMP)

Udemy: Project Management Courses

10. Financial Management

Why It's High-Paying: Sound financial management is critical for business success, making financial managers and analysts highly sought after.

How to Learn:

Coursera: Financial Management Specialization

edX: Corporate Finance

Khan Academy: Finance and Capital Markets

Conclusion

Mastering these high-paying skills can significantly enhance your career prospects in 2024 and beyond. Utilize the recommended resources to gain proficiency and stay ahead in the competitive job market. Happy learning!

[tech-insides]

Is there a possibility that machine learning will replace software developers in the next five years?

The rapid advancements in machine learning (ML) have sparked debates about the future of various professions, including software development. Will machine learning technologies evolve to a point where they can replace software developers within the next five years? Let's explore the current landscape, the capabilities of ML, and the potential future impact on software development.

Understanding Machine Learning and Its Capabilities

Machine learning, a subset of artificial intelligence (AI), involves algorithms that enable computers to learn from and make predictions or decisions based on data. ML has revolutionized many fields by automating complex tasks, improving efficiencies, and uncovering insights from large datasets. Notable applications include:

Natural Language Processing (NLP): Enabling computers to understand and generate human language.

Computer Vision: Allowing machines to interpret and process visual information from the world.

Predictive Analytics: Helping businesses forecast trends and make data-driven decisions.

While ML has made significant strides, it's crucial to recognize the current limitations. ML systems are typically narrow in scope, excelling in specific tasks but lacking general intelligence. They require large amounts of data and computational resources and often need human oversight to ensure accuracy and relevance.

The Role of Software Developers

Software developers design, write, test, and maintain software applications. Their work involves problem-solving, creativity, and collaboration. Key aspects of software development include:

Requirement Analysis: Understanding user needs and translating them into technical specifications.

Design and Architecture: Creating scalable and efficient software architectures.

Coding: Writing clean, maintainable, and efficient code.

Testing and Debugging: Ensuring software functions correctly and efficiently.

Maintenance and Updates: Continuously improving software based on user feedback and technological advancements.

Can Machine Learning Replace Software Developers?

Automating Coding Tasks: Machine learning can automate certain aspects of coding, such as code generation, bug detection, and optimization. Tools like GitHub Copilot, powered by OpenAI's Codex, can assist developers by suggesting code snippets and completing code blocks. However, these tools are currently augmenting rather than replacing human developers.

Complex Problem-Solving and Creativity: Software development often requires understanding complex systems, creative problem-solving, and adapting to new challenges. Machine learning models lack the cognitive flexibility and creativity that human developers bring to the table.

Human Interaction and Collaboration: Developing software is a collaborative effort involving communication with stakeholders, understanding user needs, and working within teams. Machine learning lacks the social and emotional intelligence required for effective collaboration.

Ethics and Accountability: Developers are responsible for ensuring that software is ethical, secure, and compliant with regulations. Accountability and ethical considerations are critical aspects where human judgment is indispensable.

The Future of Software Development

While machine learning is unlikely to replace software developers entirely within the next five years, it will undoubtedly transform the field. Developers will increasingly use ML-powered tools to enhance their productivity, automate repetitive tasks, and improve code quality. The role of software developers will evolve, focusing more on higher-level problem-solving, design, and oversight of ML systems.

Preparing for the Future

As the software development landscape evolves, continuous learning and adaptation are essential. Developers should:

Stay Updated: Keep abreast of the latest advancements in machine learning and software development.

Enhance Skills: Develop expertise in using ML tools and frameworks.

Focus on Higher-Level Skills: Emphasize problem-solving, design, and collaboration skills.

For those looking to enhance their expertise in machine learning and prepare for future opportunities, consider taking a comprehensive Machine Learning Interview Prep course to boost your readiness and improve your career prospects.

Conclusion

Machine learning is poised to revolutionize software development, automating certain tasks and augmenting developers' capabilities. However, the unique skills and human qualities that software developers bring to the table make it unlikely that ML will fully replace them in the next five years. Instead, developers who embrace these technologies and adapt to the evolving landscape will thrive in the future of software development. Source : Frobyn