#machine learning engineer salary

[bi-writes]

whats wrong with ai?? genuinely curious <3

okay let's break it down. i'm an engineer, so i'm going to come at you from a perspective that may be different than someone else's.

i don't hate ai in every aspect. in theory, there are a lot of instances where, in fact, ai can help us do things a lot better without. here's a few examples:

ai detecting cancer

ai sorting recycling

some practical housekeeping that gemini (google ai) can do

all of the above examples are ways in which ai works with humans to do things in parallel with us. it's not overstepping--it's sorting, using pixels at a micro-level to detect abnormalities that we as humans can not, fixing a list. these are all really small, helpful ways that ai can work with us.

everything else about ai works against us. in general, ai is a huge consumer of natural resources. every prompt that you put into character.ai, chatgpt? this wastes water + energy. it's not free. a machine somewhere in the world has to swallow your prompt, call on a model to feed data into it and process more data, and then has to generate an answer for you all in a relatively short amount of time.

that is crazy expensive. someone is paying for that, and if it isn't you with your own money, it's the strain on the power grid, the water that cools the computers, the A/C that cools the data centers. and you aren't the only person using ai. chatgpt alone gets millions of users every single day, with probably thousands of prompts per second, so multiply your personal consumption by millions, and you can start to see how the picture is becoming overwhelming.

that is energy consumption alone. we haven't even talked about how problematic ai is ethically. there is currently no regulation in the united states about how ai should be developed, deployed, or used.

what does this mean for you?

it means that anything you post online is subject to data mining by an ai model (because why would they need to ask if there's no laws to stop them? wtf does it matter what it means to you to some idiot software engineer in the back room of an office making 3x your salary?). oh, that little fic you posted to wattpad that got a lot of attention? well now it's being used to teach ai how to write. oh, that sketch you made using adobe that you want to sell? adobe didn't tell you that anything you save to the cloud is now subject to being used for their ai models, so now your art is being replicated to generate ai images in photoshop, without crediting you (they have since said they don't do this...but privacy policies were never made to be human-readable, and i can't imagine they are the only company to sneakily try this). oh, your apartment just installed a new system that will use facial recognition to let their residents inside? oh, they didn't train their model with anyone but white people, so now all the black people living in that apartment building can't get into their homes. oh, you want to apply for a new job? the ai model that scans resumes learned from historical data that more men work that role than women (so the model basically thinks men are better than women), so now your resume is getting thrown out because you're a woman.

ai learns from data. and data is flawed. data is human. and as humans, we are racist, homophobic, misogynistic, transphobic, divided. so the ai models we train will learn from this. ai learns from people's creative works--their personal and artistic property. and now it's scrambling them all up to spit out generated images and written works that no one would ever want to read (because it's no longer a labor of love), and they're using that to make money. they're profiting off of people, and there's no one to stop them. they're also using generated images as marketing tools, to trick idiots on facebook, to make it so hard to be media literate that we have to question every single thing we see because now we don't know what's real and what's not.

the problem with ai is that it's doing more harm than good. and we as a society aren't doing our due diligence to understand the unintended consequences of it all. we aren't angry enough. we're too scared of stifling innovation that we're letting it regulate itself (aka letting companies decide), which has never been a good idea. we see it do one cool thing, and somehow that makes up for all the rest of the bullshit?

[educationmore]

Python for Beginners: Launch Your Tech Career with Coding Skills

Are you ready to launch your tech career but don’t know where to start? Learning Python is one of the best ways to break into the world of technology—even if you have zero coding experience.

In this guide, we’ll explore how Python for beginners can be your gateway to a rewarding career in software development, data science, automation, and more.

Why Python Is the Perfect Language for Beginners

Python has become the go-to programming language for beginners and professionals alike—and for good reason:

Simple syntax: Python reads like plain English, making it easy to learn.

High demand: Industries spanning the spectrum are actively seeking Python developers to fuel their technological advancements.

Versatile applications: Python's versatility shines as it powers everything from crafting websites to driving artificial intelligence and dissecting data.

Whether you want to become a software developer, data analyst, or AI engineer, Python lays the foundation.

What Can You Do With Python?

Python is not just a beginner language—it’s a career-building tool. Here are just a few career paths where Python is essential:

Web Development: Frameworks like Django and Flask make it easy to build powerful web applications. You can even enroll in a Python Course in Kochi to gain hands-on experience with real-world web projects.

Data Science & Analytics: For professionals tackling data analysis and visualization, the Python ecosystem, featuring powerhouses like Pandas, NumPy, and Matplotlib, sets the benchmark.

Machine Learning & AI: Spearheading advancements in artificial intelligence development, Python boasts powerful tools such as TensorFlow and scikit-learn.

Automation & Scripting: Simple yet effective Python scripts offer a pathway to amplified efficiency by automating routine workflows.

Cybersecurity & Networking: The application of Python is expanding into crucial domains such as ethical hacking, penetration testing, and the automation of network processes.

How to Get Started with Python

Starting your Python journey doesn't require a computer science degree. Success hinges on a focused commitment combined with a thoughtfully structured educational approach.

Step 1: Install Python

Download and install Python from python.org. It's free and available for all platforms.

Step 2: Choose an IDE

Use beginner-friendly tools like Thonny, PyCharm, or VS Code to write your code.

Step 3: Learn the Basics

Focus on:

Variables and data types

Conditional statements

Loops

Functions

Lists and dictionaries

If you prefer guided learning, a reputable Python Institute in Kochi can offer structured programs and mentorship to help you grasp core concepts efficiently.

Step 4: Build Projects

Learning by doing is key. Start small:

Build a calculator

Automate file organization

Create a to-do list app

As your skills grow, you can tackle more complex projects like data dashboards or web apps.

How Python Skills Can Boost Your Career

Adding Python to your resume instantly opens up new opportunities. Here's how it helps:

Higher employability: Python is one of the top 3 most in-demand programming languages.

Better salaries: Python developers earn competitive salaries across the globe.

Remote job opportunities: Many Python-related jobs are available remotely, offering flexibility.

Even if you're not aiming to be a full-time developer, Python skills can enhance careers in marketing, finance, research, and product management.

If you're serious about starting a career in tech, learning Python is the smartest first step you can take. It’s beginner-friendly, powerful, and widely used across industries.

Whether you're a student, job switcher, or just curious about programming, Python for beginners can unlock countless career opportunities. Invest time in learning today—and start building the future you want in tech.

Globally recognized as a premier educational hub, DataMites Institute delivers in-depth training programs across the pivotal fields of data science, artificial intelligence, and machine learning. They provide expert-led courses designed for both beginners and professionals aiming to boost their careers.

Python Modules Explained - Different Types and Functions - Python Tutorial

[samarthdas]

Exploring DeepSeek and the Best AI Certifications to Boost Your Career

Understanding DeepSeek: A Rising AI Powerhouse

DeepSeek is an emerging player in the artificial intelligence (AI) landscape, specializing in large language models (LLMs) and cutting-edge AI research. As a significant competitor to OpenAI, Google DeepMind, and Anthropic, DeepSeek is pushing the boundaries of AI by developing powerful models tailored for natural language processing, generative AI, and real-world business applications.

With the AI revolution reshaping industries, professionals and students alike must stay ahead by acquiring recognized certifications that validate their skills and knowledge in AI, machine learning, and data science.

Why AI Certifications Matter

AI certifications offer several advantages, such as:

Enhanced Career Opportunities: Certifications validate your expertise and make you more attractive to employers.

Skill Development: Structured courses ensure you gain hands-on experience with AI tools and frameworks.

Higher Salary Potential: AI professionals with recognized certifications often command higher salaries than non-certified peers.

Networking Opportunities: Many AI certification programs connect you with industry experts and like-minded professionals.

Top AI Certifications to Consider

If you are looking to break into AI or upskill, consider the following AI certifications:

1. AICerts – AI Certification Authority

AICerts is a recognized certification body specializing in AI, machine learning, and data science.

It offers industry-recognized credentials that validate your AI proficiency.

Suitable for both beginners and advanced professionals.

2. Google Professional Machine Learning Engineer

Offered by Google Cloud, this certification demonstrates expertise in designing, building, and productionizing machine learning models.

Best for those who work with TensorFlow and Google Cloud AI tools.

3. IBM AI Engineering Professional Certificate

Covers deep learning, machine learning, and AI concepts.

Hands-on projects with TensorFlow, PyTorch, and SciKit-Learn.

4. Microsoft Certified: Azure AI Engineer Associate

Designed for professionals using Azure AI services to develop AI solutions.

Covers cognitive services, machine learning models, and NLP applications.

5. DeepLearning.AI TensorFlow Developer Certificate

Best for those looking to specialize in TensorFlow-based AI development.

Ideal for deep learning practitioners.

6. AWS Certified Machine Learning – Specialty

Focuses on AI and ML applications in AWS environments.

Includes model tuning, data engineering, and deep learning concepts.

7. MIT Professional Certificate in Machine Learning & Artificial Intelligence

A rigorous program by MIT covering AI fundamentals, neural networks, and deep learning.

Ideal for professionals aiming for academic and research-based AI careers.

Choosing the Right AI Certification

Selecting the right certification depends on your career goals, experience level, and preferred AI ecosystem (Google Cloud, AWS, or Azure). If you are a beginner, starting with AICerts, IBM, or DeepLearning.AI is recommended. For professionals looking for specialization, cloud-based AI certifications like Google, AWS, or Microsoft are ideal.

With AI shaping the future, staying certified and skilled will give you a competitive edge in the job market. Invest in your learning today and take your AI career to the next leve

[sarkariresultdude]

Stanford University A Pillar of Excellence

 Stanford University, located in the heart of Silicon Valley, California, is synonymous with instructional excellence, groundbreaking studies, and international impact. As one of the world’s leading establishments, its "outcomes" span various dimensions—instructional achievements, research breakthroughs, societal contributions, and pupil effects. This article delves into the multifaceted outcomes that outline Stanford's unprecedented popularity.

Stanford University Result 

Academic Achievements

Stanford continually ranks among the pinnacle universities globally. In the latest rankings with the aid of institutions like QS World University Rankings and Times Higher Education (THE), Stanford has secured pinnacle positions for its academic excellence, innovation, and studies contributions. Notably, Stanford excels in fields such as pc technological know-how, engineering, commercial enterprise, law, and remedy. These results testify to the university’s dedication to fostering highbrow growth and pushing the boundaries of understanding.

Notable Programs

Graduate School of Business: Stanford GSB is renowned for generating leaders in international industries. MBA graduates constantly file for excessive starting salaries and professional delight, reflecting the college’s rigorous curriculum and strong alumni community.

School of Engineering: Often taken into consideration as the backbone of Silicon Valley, Stanford’s engineering programs make contributions notably to technological advancements. Fields like artificial intelligence, bioengineering, and sustainable electricity are key focus areas.

School of Medicine: Stanford Medicine is diagnosed for its modern studies and healthcare innovations, such as contributions to cancer remedies, genomics, and vaccine development.

Results in Rankings

QS Rankings 2024: Stanford is ranked #three globally, highlighting its studies output, educational effect, and agency popularity.

THE Impact Rankings: Stanford ranks the various pinnacle 10 universities for its contributions to the United Nations’ Sustainable Development Goals (SDGs), including great schooling, climate movement, and enterprise innovation.

 Research Breakthroughs

Stanford’s reputation as a studies powerhouse is unrivaled. Every 12 months, the university secures billions in study funding from government agencies, private corporations, and philanthropic donors. The effects of this investment take place in improvements that shape industries and enhance lives.

Key Areas of Impact

Artificial Intelligence (AI) and Machine Learning: Stanford researchers have pioneered AI technologies that affect sectors like healthcare, finance, and self-sufficient systems.

Biotechnology: Discoveries in gene modifying, CRISPR generation, and customized remedy underscore Stanford’s role in advancing lifestyles sciences.

Climate and Sustainability: The college’s Stanford Doerr School of Sustainability drives studies in renewable electricity, climate alternate mitigation, and conservation efforts.

Metrics of Success

Research Funding: In 2023, Stanford acquired over $1.Ninety-three billion in subsidized studies investment.

Publications and Citations: Stanford scholars post drastically in high-impact journals, with research mentioned hundreds of thousands of times globally.

Nobel Laureates: Over 20 faculty individuals and alumni have been awarded Nobel Prizes, reflecting the groundbreaking nature of their work.

 Entrepreneurial Success

Stanford's entrepreneurial atmosphere is considered one of its maximum amazing outcomes. As the birthplace of companies like Google, Apple, and Tesla, the university fosters a spirit of innovation that extends a long way beyond its campus. Programs just like the Stanford Entrepreneurship Network and access to resources in Silicon Valley offer students and schools unheard-of opportunities to release ventures.

Entrepreneurial Metrics

Startups Founded by Way of Alumni: Over 39,000 agencies had been started out by using Stanford alumni, generating trillions in annual revenue.

Venture Capital Funding: Stanford-affiliated startups entice sizable assignment capital investments, with the college constantly rating as a pinnacle manufacturer of funded marketers.

Economic Impact: Companies founded by Stanford graduates collectively hire hundreds of thousands of human beings internationally, making widespread contributions to the global economy.

Student Success and Satisfaction

The results of Stanford’s educational philosophy are glaring within the achievements of its students and alumni. The college offers a rigorous yet supportive environment that encourages creativity, critical questioning, and interdisciplinary collaboration.

Key Outcomes

Graduation Rates: Stanford boasts a 94% graduation rate, one of the maximum amongst U.S. Universities.

Post-Graduation Employment: A marvelous 91% of graduates steady employment or pursue advanced studies within six months of commencement.

Alumni Impact: Stanford alumni encompass Fortune 500 CEOs, influential policymakers, award-triumphing artists, and leaders in nonprofit sectors.

Enhancing Student Experience

Diversity and Inclusion: Stanford is devoted to constructing a various scholar body, with over 45% of college students figuring out as minorities.

Scholarships and Financial Aid: The college offers a need-primarily based resource to over 70% of students, ensuring get right of entry schooling for talented individuals no matter their economic historical past.

Global Opportunities: Programs just like the Bing Overseas Studies Program permit students to gain global exposure, getting ready them for international careers.

Contributions to Society

Stanford’s impact extends beyond academia and enterprise; its results resonate globally via tasks aimed at addressing societal challenges.

Social and Environmental Impact

Sustainability Efforts: Stanford’s campus is a model of sustainable layout, presenting initiatives to reduce carbon emissions, conserve water, and sell green power.

Public Policy Influence: Stanford’s Hoover Institution and Freeman Spogli Institute for International Studies produce studies that shape public policy on problems like cybersecurity, global health, and governance.

Community Engagement: Through carrier-learning programs and volunteer tasks, Stanford college students contribute lots of hours annually to local and worldwide groups.

Measuring Broader Impact

SDG Contributions: Stanford ranks exceedingly in metrics related to health, training, and innovation, reflecting its alignment with global desires.

Partnerships and Collaborations: The university collaborates with companies like the World Health Organization (WHO), the United Nations (UN), and main nonprofits to cope with urgent international demands.

 Challenges and Areas for Growth

While Stanford’s results are overwhelmingly wonderful, the university acknowledges demanding situations and areas for improvement. These include:

Affordability and Accessibility: Despite its beneficent economic aid packages, Stanford faces complaints for its excessive training charges.

Mental Health Resources: As with many elite establishments, the pressures of educational existence can affect scholar well-being, prompting calls for more desirable support offerings.

Sustainability Goals: While Stanford leads in sustainability, reaching carbon neutrality via 2050 stays a protracted-time period venture.

[aionlinemoney]

India’s Tech Sector to Create 1.2 Lakh AI Job Vacancies in Two Years

India’s technology sector is set to experience a hiring boom with job vacancies for artificial intelligence (AI) roles projected to reach 1.2 lakh over the next two years. As the demand for AI latest technology increases across industries, companies are rapidly adopting advanced tools to stay competitive. These new roles will span across tech services, Global Capability Centres (GCCs), pure-play AI and analytics firms, startups, and product companies.

Following a slowdown in tech hiring, the focus is shifting toward the development of AI. Market analysts estimate that Indian companies are moving beyond Proof of Concept (PoC) and deploying large-scale AI systems, generating high demand for roles such as AI researchers, product managers, and data application specialists. “We foresee about 120,000 to 150,000 AI-related job vacancies emerging as Indian IT services ramp up AI applications,” noted Gaurav Vasu, CEO of UnearthInsight.

India currently has 4 lakh AI professionals, but the gap between demand and supply is widening, with job requirements expected to reach 6 lakh soon. By 2026, experts predict the number of AI specialists required will hit 1 million, reflecting the deep integration of AI latest technology into industries like healthcare, e-commerce, and manufacturing.

The transition to AI-driven operations is also altering the nature of job vacancies. Unlike traditional software engineering roles, artificial intelligence positions focus on advanced algorithms, automation, and machine learning. Companies are recruiting experts in fields like deep learning, robotics, and natural language processing to meet the growing demand for innovative AI solutions. The development of AI has led to the rise of specialised roles such as Machine Learning Engineers, Data Scientists, and Prompt Engineers.

Krishna Vij, Vice President of TeamLease Digital, remarked that new AI roles are evolving across industries as AI latest technology becomes an essential tool for product development, operations, and consulting. “We expect close to 120,000 new job vacancies in AI across different sectors like finance, healthcare, and autonomous systems,” he said.

AI professionals also enjoy higher compensation compared to their traditional tech counterparts. Around 80% of AI-related job vacancies offer premium salaries, with packages 40%-80% higher due to the limited pool of trained talent. “The low availability of experienced AI professionals ensures that artificial intelligence roles will command attractive pay for the next 2-3 years,” noted Krishna Gautam, Business Head of Xpheno.

Candidates aiming for AI roles need to master key competencies. Proficiency in programming languages like Python, R, Java, or C++ is essential, along with knowledge of AI latest technology such as large language models (LLMs). Expertise in statistics, machine learning algorithms, and cloud computing platforms adds value to applicants. As companies adopt AI latest technology across domains, candidates with critical thinking and  AI adaptability will stay ahead so it is important to learn and stay updated with AI informative blogs & news.

Although companies are prioritising experienced professionals for mid-to-senior roles, entry-level job vacancies are also rising, driven by the increased use of AI in enterprises. Bootcamps, certifications, and academic programs are helping freshers gain the skills required for artificial intelligence roles. As AI development progresses, entry-level roles are expected to expand in the near future. AI is reshaping the industries providing automation & the techniques to save time , to increase work efficiency. 

India’s tech sector is entering a transformative phase, with a surge in job vacancies linked to AI latest technology adoption. The next two years will witness fierce competition for AI talent, reshaping hiring trends across industries and unlocking new growth opportunities in artificial intelligence. Both startups and established companies are racing to secure talent, fostering a dynamic landscape where artificial intelligence expertise will be help in innovation and growth. AI will help organizations and businesses to actively participate in new trends.

#aionlinemoney.com

[capstonees]

BIM Careers: Building Your Future in the Digital AEC Arena

The construction industry is undergoing a digital revolution, and BIM (Building Information Modeling) is at the forefront. It's no longer just a fancy 3D modeling tool; BIM is a collaborative platform that integrates data-rich models with workflows across the entire building lifecycle. This translates to exciting career opportunities for those who can harness the power of BIM.

Are you ready to step into the octagon of the digital construction arena? (Yes, we're keeping the fighting metaphor alive!) Here's a breakdown of the in-demand skills, salary ranges, and future prospects for BIM professionals:

The In-Demand Skillset: Your BIM Arsenal

Think of your BIM skills as your tools in the digital construction toolbox. Here are the top weapons you'll need:

BIM Software Proficiency: Mastering software like Revit, ArchiCAD, or Navisworks is crucial. Understanding their functionalities allows you to create, manipulate, and analyze BIM models.

Building Science Fundamentals: A solid grasp of architectural, structural, and MEP (mechanical, electrical, and plumbing) principles is essential for creating BIM models that reflect real-world construction realities.

Collaboration & Communication: BIM thrives on teamwork. The ability to collaborate effectively with architects, engineers, and other stakeholders is paramount.

Data Management & Analysis: BIM models are data-rich. Being adept at data extraction, analysis, and interpretation unlocks the true potential of BIM for informed decision-making.

Problem-Solving & Critical Thinking: BIM projects are complex. The ability to identify and solve problems creatively, while thinking critically about the design and construction process, is invaluable.

Salary Showdown: The BIM Payday Punch

Now, let's talk about the real knock-out factor – salaries! According to Indeed, BIM professionals in the US can expect an average annual salary of around $85,000. This number can vary depending on experience, location, and specific BIM expertise. Entry-level BIM roles might start around $60,000, while BIM Managers and BIM Specialists with extensive experience can command salaries exceeding $100,000.

Future Forecast: A Bright BIM Horizon

The future of BIM is bright. The global BIM market is projected to reach a staggering $8.8 billion by 2025 (Grand View Research). This translates to a continuous rise in demand for skilled BIM professionals. Here are some exciting trends shaping the future of BIM careers:

BIM for Specialty Trades: BIM is no longer just for architects and engineers. We'll see increased adoption by specialty trades like HVAC technicians and fire protection specialists.

Integration with AI and Machine Learning: Imagine BIM models that can predict potential issues or suggest optimal design solutions. AI and machine learning will revolutionize BIM capabilities.

VR and AR for Enhanced Collaboration: Virtual Reality (VR) and Augmented Reality (AR) will allow for immersive BIM model walkthroughs, facilitating better collaboration and design communication.

Ready to Join the BIM Revolution?

The BIM landscape offers a dynamic and rewarding career path for those with the right skills. If you're passionate about technology, construction, and shaping the future of the built environment, then BIM might be your perfect career match. So, hone your skills, embrace the digital revolution, and step into the exciting world of BIM with Capstone Engineering!

[willcodehtmlforfood]

The quickest way to second-guess a decision to major in English is this: have an extended family full of Salvadoran immigrants and pragmatic midwesterners. The ability to recite Chaucer in the original Middle English was unlikely to land me a job that would pay off my student loans and help me save for retirement, they suggested when I was a college freshman still figuring out my future. I stuck with English, but when my B.A. eventually spat me out into the thick of the Great Recession, I worried that they’d been right.

After all, computer-science degrees, and certainly not English, have long been sold to college students as among the safest paths toward 21st-century job security. Coding jobs are plentiful across industries, and the pay is good—even after the tech layoffs of the past year. The average starting salary for someone with a computer-science degree is significantly higher than that of a mid-career English graduate, according to the Federal Reserve; at Google, an entry-level software engineer reportedly makes $184,000, and that doesn’t include the free meals, massages, and other perks. Perhaps nothing has defined higher education over the past two decades more than the rise of computer science and STEM. Since 2016, enrollment in undergraduate computer-science programs has increased nearly 49 percent. Meanwhile, humanities enrollments across the United States have withered at a clip—in some cases, shrinking entire departments to nonexistence.

But that was before the age of generative AI. ChatGPT and other chatbots can do more than compose full essays in an instant; they can also write lines of code in any number of programming languages. You can’t just type make me a video game into ChatGPT and get something that’s playable on the other end, but many programmers have now developed rudimentary smartphone apps coded by AI. In the ultimate irony, software engineers helped create AI, and now they are the American workers who think it will have the biggest impact on their livelihoods, according to a new survey from Pew Research Center. So much for learning to code.

ChatGPT cannot yet write a better essay than a human author can, nor can it code better than a garden-variety developer, but something has changed even in the 10 months since its introduction. Coders are now using AI as a sort of souped-up Clippy to accelerate the more routine parts of their job, such as debugging lines of code. In one study, software developers with access to GitHub’s Copilot chatbot were able to finish a coding task 56 percent faster than those who did it solo. In 10 years, or maybe five, coding bots may be able to do so much more.

People will still get jobs, though they may not be as lucrative, says Matt Welsh, a former Harvard computer-science professor and entrepreneur. He hypothesizes that automation will lower the barrier to entry into the field: More people might get more jobs in software, guiding the machines toward ever-faster production. This development could make highly skilled developers even more essential in the tech ecosystem. But Welsh also says that an expanded talent pool “may change the economics of the situation,” possibly leading to lower pay and diminished job security.

If mid-career developers have to fret about what automation might soon do to their job, students are in the especially tough spot of anticipating the long-term implications before they even start their career. “The question of what it will look like for a student to go through an undergraduate program in computer science, graduate with that degree, and go on into the industry … That is something I do worry about,” Timothy Richards, a computer-science professor at the University of Massachusetts at Amherst, told me. Not only do teachers like Richards have to wrestle with just how worthwhile learning to code is anymore, but even teaching students to code has become a tougher task. ChatGPT and other chatbots can handle some of the basic tasks in any introductory class, such as finding problems with blocks of code. Some students might habitually use ChatGPT to cheat on their assignments, eventually collecting their diploma without having learned how to do the work themselves.

Richards has already started to tweak his approach. He now tells his introductory-programming students to use AI the way a math student would use a calculator, asking that they disclose the exact prompts they fed into the machine, and explain their reasoning. Instead of taking assignments home, Richards’s students now do the bulk of their work in the classroom, under his supervision. “I don’t think we can really teach students in the way that we’ve been teaching them for a long time, at least not in computer science,” he said.

Fiddling with the computer-science curriculum still might not be enough to maintain coding’s spot at the top of the higher-education hierarchy. “Prompt engineering,” which entails feeding phrases to large language models to make their responses more human-sounding, has already surfaced as a lucrative job option—and one perhaps better suited to English majors than computer-science grads. “Machines can’t be creative; at best, they’re very elaborate derivatives,” says Ben Royce, an AI lecturer at Columbia University. Chatbots don’t know what to do with a novel coding problem. They sputter and choke. They make stuff up. As AI becomes more sophisticated and better able to code, programmers may be tasked with leaning into the parts of their job that draw on conceptual ingenuity as opposed to sheer technical know-how. Those who are able to think more entrepreneurially—the tinkerers and the question-askers—will be the ones who tend to be almost immune to automation in the workforce.

The potential decline of “learn to code” doesn’t mean that the technologists are doomed to become the authors of their own obsolescence, nor that the English majors were right all along (I wish). Rather, the turmoil presented by AI could signal that exactly what students decide to major in is less important than an ability to think conceptually about the various problems that technology could help us solve. The next great Silicon Valley juggernaut might be seeded by a humanities grad with no coding expertise or a computer-science grad with lots of it. After all, the discipline has always been about more than just learning the ropes of Python and C++. Identifying patterns and piecing them together is its essence.

In that way, the answer to the question of what happens next in higher education may lie in what the machines can’t do. Royce pointed me toward Moravec’s paradox, the observation that AI shines at high-level reasoning and the kinds of skills that are generally considered to reflect cognitive aptitude (think: playing chess), but fumbles with the basic ones. The curiosity-driven instincts that have always been at the root of how humans create things are not just sticking around in an AI world; they are now more important than ever. Thankfully, students have plenty of ways to get there.

[onlineprofessionalcourse]

Top GCP Certification For Beginners To Consider In 2024

In 2024, Google Cloud Platform (GCP) continues to dominate the cloud computing landscape with its robust set of services and solutions. For beginners looking to establish a career in cloud technology, obtaining GCP certifications is a strategic move. These certifications validate expertise in various GCP services, enhancing credibility and opening doors to lucrative career opportunities.

Why Choose GCP Certifications?

Career Advantages

GCP certifications are recognized globally and are highly valued by employers across industries. They validate skills in cloud architecture, data engineering, machine learning, and more, making certified professionals indispensable in today’s digital economy. With cloud adoption accelerating, companies are actively seeking GCP-certified professionals to drive their digital transformation initiatives.

Comprehensive Certification Options

Google offers a range of GCP certifications tailored to different job roles and skill levels:

1. Associate Cloud Engineer

The Associate Cloud Engineer certification is ideal for beginners aiming to demonstrate proficiency in deploying applications, monitoring operations, and managing enterprise solutions on GCP. It establishes a solid foundation in cloud architecture and infrastructure.

2. Professional Cloud Architect

For professionals aspiring to design and deploy dynamic and scalable GCP solutions, the Professional Cloud Architect certification is paramount. It covers advanced concepts such as security, compliance, and high availability.

3. Data Engineer

The Data Engineer certification focuses on designing and building data processing systems on GCP. It equips individuals with skills in data transformation, loading, and processing that are crucial in today’s data-driven enterprises.

4. Cloud Developer

The Cloud Developer certification validates proficiency in designing, building, and deploying applications on GCP. It emphasizes skills in application development, debugging, and performance optimization using Google technologies.

Preparation Tips for GCP Certification Exams

Achieving GCP certifications requires diligent preparation:

– Hands-on Experience

Practice using GCP services through labs and real-world scenarios to familiarize yourself with the platform’s features and functionalities.

– Official Study Materials

Utilize Google’s official training resources, including online courses, practice exams, and documentation, to gain comprehensive knowledge of exam objectives.

– Community Support

Engage with the GCP community through forums, study groups, and social media channels to exchange insights, tips, and best practices with fellow learners and professionals.

Career Growth and Opportunities

Earning GCP certifications not only enhances technical skills but also opens doors to a wide array of career opportunities:

High-demand Skills: Companies seek GCP-certified professionals for roles such as cloud architect, solutions engineer, and data analyst, offering competitive salaries and career advancement prospects.

Industry Recognition: GCP certifications validate expertise in cutting-edge cloud technologies, boosting credibility and marketability in the job market.

Continuous Learning: GCP certifications require ongoing learning and skill development, keeping professionals abreast of industry trends and innovations.

Conclusion

In conclusion, GCP certifications are indispensable for beginners looking to establish a successful career in cloud computing. Whether aiming to become an Associate Cloud Engineer, Professional Cloud Architect, Data Engineer, or Cloud Developer, these certifications validate expertise and open doors to lucrative career opportunities in 2024 and beyond.

[study-in-uk-msm-unify]

Emerging Industries: Opportunities in the UK Job Market

Planning to study in the UK? Want to explore career opportunities in the United Kingdom?

In the ever-evolving world, the UK stands as a hub for innovation and growth, bringing numerous emerging sectors that offer promising career prospects. As technology continues to reshape the global economy, several industries in the UK have captured attention, presenting exciting opportunities for job seekers and entrepreneurs alike. Take a look at some of the career opportunities you could take advantage of.  

1. Fintech (Financial Technology)

The UK has strengthened its position as a leading fintech hub, with London being a prominent center for financial innovation. Fintech includes a wide array of sectors, including mobile payments, blockchain, and cybersecurity. Job opportunities in this field span software development, data analysis, financial consultancy, and regulatory compliance.

2. Technology and IT 

In the emerging era of the digital world, technology continues to dominate businesses worldwide. As, a result the demand for technologically advanced professionals tends to rise. Software developers, data analysts, cybersecurity experts, and artificial intelligence specialists roles are in high demand. With the increasing use of technologies and the need for innovative solutions, these roles offer tremendous growth opportunities and competitive salaries. 

3. Healthtech

The combination of healthcare and technology has given rise to HealthTech, a sector dedicated to enhancing medical services through innovative solutions. From telemedicine to health analytics and AI-driven diagnostics, HealthTech offers diverse career paths for healthcare professionals, software developers, data scientists, and researchers.

4. Renewable energy and sustainability

With an increased focus on sustainability and combating climate change, the UK has been investing significantly in renewable energy sources. Wind, solar, and hydroelectric power are among the sectors experiencing rapid growth. Job roles in renewable energy range from engineering and project management to research and policy development, catering to those passionate about environmental conservation.

5. Cybersecurity

With the increasing frequency of cyber threats, the demand for cybersecurity experts is on the rise. Businesses and governments are investing heavily in safeguarding digital infrastructure. Job roles in cybersecurity encompass ethical hacking, network security, data protection, and risk analysis, presenting ample opportunities for skilled professionals in this field.

6. Artificial Intelligence and Machine Learning

AI and machine learning are revolutionizing various industries, including finance, healthcare, and manufacturing. The UK is fostering innovation in AI research and development, offering roles in AI programming, data engineering, robotics, and AI ethics.

7. Creative industries

The UK has a rich heritage in the creative sector, encompassing fields like media, design, gaming, and entertainment. Roles in creative industries span from content creation and graphic design to video production and game development, appealing to individuals with artistic and technical skills.

In conclusion, the UK job market is filled with opportunities within emerging industries, showing the nation's commitment to innovation and progress. Whether one's passion lies in sustainability, technology, healthcare, or creative endeavors, these sectors offer an array of possibilities for career growth and contribution to shaping the future.

By embracing change, acquiring relevant skills, and staying adaptable, individuals can position themselves to thrive in these dynamic and promising industries, contributing to both personal success and the advancement of these transformative sectors in the UK.

If you are struggling to get the right guidance, please do not hesitate to consult MSM Unify. 

At MSM Unify, you can explore more than 50,000 courses across 1500+ educational institutions across the globe. MSM Unify has helped 1,50,000+ students achieve their study abroad dream so far. Now, it is your turn to attain your study-abroad dreams and elevate your professional journey! So, get ready to broaden your horizons and make unforgettable memories on your upcoming adventure.

[vivekavicky12]

Decoding Data Science: Unveiling the Vast Landscape and Career Opportunities

In the era of big data, Data Science has emerged as a transformative force, reshaping industries and driving innovation. This blog aims to unravel the essence of Data Science, exploring its multidisciplinary nature and shedding light on the extensive scope and promising career opportunities within this dynamic field. Whether you're a beginner or looking to specialize, understanding the types of data science courses available is crucial. Choosing the best Data Science Institute can further accelerate your journey into this thriving industry.

What is Data Science?

At its core, Data Science is the art and science of extracting valuable insights and knowledge from complex data sets. By employing a combination of scientific methods, algorithms, and domain-specific knowledge, Data Science transforms raw data into actionable intelligence. This multidisciplinary field encompasses statistics, mathematics, computer science, and more to analyze and interpret both structured and unstructured data.

Scope of Data Science:

Job Opportunities:

Data scientists are sought after across diverse industries such as finance, healthcare, technology, and e-commerce.

Roles include data analyst, machine learning engineer, data engineer, business intelligence analyst, and data scientist.

Educational Landscape:

The educational landscape for Data Science is expansive, with universities and online platforms offering a plethora of courses, degrees, and certifications.

Specialized programs cover machine learning, big data, data engineering, and business analytics to cater to varying skill levels.

Industry Integration:

Organizations are increasingly integrating data science into their operations, influencing decision-making processes.

Data-driven strategies impact areas like marketing, product development, and overall business strategy.

Government Initiatives:

Governments recognize the importance of data science in driving innovation and economic growth.

Initiatives and policies promote data literacy and skill development, aligning education with industry needs.

Diverse Applications:

Data science finds applications in diverse fields, including finance for fraud detection, healthcare for predictive analytics, marketing for customer segmentation, and agriculture for precision farming.

Its versatility is reflected in its broad spectrum of applications.

Competitive Salaries:

Skilled data science professionals command competitive salaries due to the specialized nature of their expertise.

Salaries vary based on factors like experience, location, and the specific role within the data science field.

Global Contribution:

Data scientists contribute globally, collaborating on projects addressing societal challenges, healthcare advancements, and environmental issues.

The global nature of data science fosters a culture of collaboration and knowledge exchange.

Continuous Innovation:

Data science stands at the forefront of technological innovation, driving advancements in artificial intelligence, machine learning models, and predictive analytics.

Professionals engage in cutting-edge research, contributing to the ongoing evolution of the field.

Career Opportunities:

Data Scientist

Data Analyst

Machine Learning Engineer

Data Engineer

Business Intelligence Analyst

Data Architect

Statistician

Quantitative Analyst

Research Scientist

Predictive Modeler

Data Science is not just a field; it's a dynamic force shaping the future of industries. With a vast scope and diverse career opportunities, it offers a compelling journey for those seeking to immerse themselves in the intersection of technology, analytics, and innovation. As organizations continue to recognize the value of data-driven insights, the demand for skilled data scientists is set to soar, making Data Science a promising and rewarding career path. Choosing the best Data Science courses in Chennai is a crucial step in acquiring the necessary expertise for a successful career in the evolving landscape of data science.

[transstadiauniversity]

Why Is B. Sc In Computer Science A Rewarding Career?

B.Sc in computer science is a degree that teaches students about  programming,  maintenance, development, and more. The degree teaches students to see computers as science and takes them into deeper aspects. Computer science is a subject for students with an in-depth understanding of and love for computers.

India is one of the biggest IT hubs in the world, and people across the world come to India for IT Solutions. Doing a B.Sc in computer science is a good move, as it will make you eligible for  work in the ever-growing IT industry of the country.

You can have an excellent and high-paying career.  You will get the experience for success and fulfillment. It is vital to learn about a course before you decide to enroll. Here you will  get to know about eligibility. careers, jobs, and more that will help you realise the potential of the B.Sc in computer science degree course.

Course highlights: B.Sc in computer science

The following are the highlights of the B.Sc in Computer Science course. it will give you a quick insight into all of the information with respect to a B.Sc in computer science. In terms of the CS course level, it is an undergraduate course.

 It takes about 3 years to complete and gets divided into 6 semesters.

You will need to pass your 12th exam in science with PCM subjects. The course fees in India will range between 1 lakh to 7 lahks.

Exams will be conducted each semester with an exam at the end of each semester. In most cases, admissions will be granted based on the 12th score.  some colleges will also have entrance examinations.

Eligibility criteria:  B.Sc in computer science

  You need to clear the following eligibility criteria to be considered eligible for the B.Sc in Computer Science degree. 

Students will need to complete their 12th standard in the science stream  which physics chemistry and maths PCM.

Some private colleges may grant admission to the students who have Sciences with physics chemistry and Biology.

Scope of the course:  B.Sc in computer science

B.Sc in computer science has immense scope in India.  Computer education has always had a lot of importance owing to the IT industry of the country. B.Sc in Computer Science degree has a lot of value and is most likely employment with a good salary and other benefits.

Computer education in India is so important that people with other degrees also do additional Computer Based certification courses to add value to their degrees.

Benefits of B.Sc in computer science 

Knowing the benefits of the degree course will help you understand how it can shape your career in the future and help you make up your mind about completing the course.

Career-oriented course 

It's a highly career-oriented degree.  Right after graduation, students can find employment and get started with their professional journey.

High pay scale

  B.Sc in Computer Science students will get an excellent starting salary figure when compared to other graduates. The figure shows a substantial growth over the years. B.Sc in Computer Science graduates will make good money throughout their careers.

If you have a B.Sc in Computer Science degree, you can wish to study further. you can do courses like MBA, MCA and PGDM  and get an amazing career.

Job security

B.Sc in computer science will allow graduates to find a job in the IT industry which is one of the fastest-growing industries in the nation. Jobs in the industry are secured.

 Technologically advanced degree 

Technology is going to be a part of everyday life.  Getting a technology-based like graduation degree in computer science will be advantageous in the long run.

Job opportunities

AI and Machine Learning specialists 

Artificial intelligence and machine learning are revolutionizing many industries. A job as a machine learning engineer is an option for B.Sc. graduates with knowledge of data modeling, machine learning methods, and programming. Starting pay of INR 6 to 9 lakhs per year is typical for machine learning engineers in India. Salary ranges between INR 15 and 25 lakh per year are possible with deep learning and neural network skills and abilities.

Software engineering 

Software development or engineering is one of the most popular job pathways for B.Sc. in Computer Science graduates. Software engineers are responsible for devising, maintaining, and developing apps and software programs. In India, the annual salary of an entry-level software developer may be between INR 3.5 and 6 lakhs. With experience, the pay can rise dramatically and, for senior jobs, can reach INR 15 lakhs or more.

Data analysts 

As organizations rely on data-driven insights for decision-making, data analysis is essential in today's corporate world. Data analysts are B.Sc. graduates with a focus on data analysis. They collect, organize, and analyze data to derive useful insights. In India, entry-level data analysts typically make between INR 4 and INR 7 lakhs annually. Salary ranges between INR 12 and 18 lakh per year are possible with experience and expertise in sophisticated analytics methodologies and data visualization technologies.

Key Takeaway 

The B.Sc in computer science is one of the finest courses that you may prefer to do after your 12th grade. You won’t just be eligible for a high-paying job. But, your contributions can also make a difference in the world and the quality of life. It is a degree with lucrative benefits and offers complete value for the time and money invested. 

TransStadia University may have a strong focus on industry integration, providing students with opportunities for internships, industry projects, and collaborations with companies. Such practical exposure can enhance students' skills and employability. The university's curriculum for the B.Sc. in Computer Science program may be designed to align with industry needs, emphasizing practical skills, project-based learning, and emerging technologies.

You can apply today if you want to enroll in B.Sc Computer Science. 

[sgtuniversityggn]

Best colleges for BCA in Artificial Intelligence & Machine Learning

BCA in Artificial Intelligence & Machine Learning: Starting the Journey into AI & ML

Artificial Intelligence (AI) and Machine Learning (ML) have become crucial technologies across various industries. They have changed the way we work, and interact with technology. Pursuing a Bachelor of Computer Applications (BCA) in Artificial Intelligence and Machine Learning meets the growing demand for professionals who possess a strong foundation in both AI and ML.

In this article, we will explore the significance of BCA in Artificial Intelligence and Machine Learning and how it can shape your career.

Introduction to BCA in Artificial Intelligence & Machine Learning

BCA in Artificial Intelligence and Machine Learning is a 3 year UG course that combines computer science with AI and ML concepts. It is designed to provide students with a comprehensive understanding of the theoretical foundations and practical applications of AI and ML technologies.

This program equips students with the skills required to develop intelligent systems, analyze complex data sets, and build predictive models using ML algorithms.

BCA in AI & ML Syllabus

The curriculum of BCA in Artificial Intelligence and Machine Learning is carefully crafted to provide students with a strong foundation in computer science, programming, mathematics, and statistics. Additionally, it includes specialized courses in AI and ML, covering topics such as:

Data Structures and Algorithms

Probability and Statistics

Data Mining and Data Warehousing

Deep Learning

Natural Language Processing

Computer Vision

Reinforcement Learning

Big Data Analytics

Cloud Computing

Learn more about the complete BCA in AI and ML syllabus at SGT University.

Job Opportunities for BCA in AI & ML Graduates

Upon completing BCA in Artificial Intelligence and Machine Learning, graduates can explore various career opportunities in both established companies and startups. Some of the common jobs in this field include:

AI Engineer

Machine Learning Engineer

Data Scientist

Business Intelligence Analyst

AI Researcher

Robotics Engineer

Data Analyst

Software Developer

Data Engineer

Salary Potential

BCA graduates in Artificial Intelligence and Machine Learning can expect competitive salaries due to the high demand for AI and ML professionals. Entry-level positions typically offer salaries ranging from 6 to 8 LPA according to Upgrad.

Future Scope of BCA in Artificial Intelligence & Machine Learning

The future scope of BCA in Artificial Intelligence and Machine Learning is promising.

As AI and ML continue to advance and permeate various sectors, the demand for skilled professionals in this field will only increase.

Industries such as healthcare, finance, retail, manufacturing, and transportation are actively adopting AI and ML technologies, creating a wealth of opportunities for BCA graduates.

How to Excel in Artificial Intelligence and Machine Learning Studies

To excel in BCA studies, follow these tips:

Stay Updated: Keep up with the latest advancements in AI and ML through academic journals, conferences, and online resources.

Practice Coding: Develop proficiency in programming languages commonly used in AI and ML, such as Python and R.

Hands-on Projects: Engage in practical projects to apply theoretical knowledge and build a strong portfolio.

Collaborate and Network: Join AI and ML communities, attend meetups, and participate in hackathons to collaborate with peers and learn from experts.

Continuous Learning: Embrace continuous learning to stay relevant in the rapidly evolving field of AI and ML.

Why Study BCA in Artificial Intelligence and Machine Learning from SGT University?

The following reasons make SGT University the best colleges for BCA in Artificial Intelligence & Machine Learning:

A future-proof career in technology.

Specialization in AI and ML.

Expertise in cutting-edge technologies.

Strong industry demand for graduates.

Access to renowned faculty and resources.

Networking with industry professionals.

Gateway to innovation and research.

Conclusion

BCA in Artificial Intelligence and Machine Learning offers a comprehensive education that combines computer science with AI and ML concepts.

With the increasing demand for AI and ML professionals, pursuing BCA in this domain can open up exciting career opportunities and provide a strong foundation for future growth.

Enroll now at SGT University to learn this course.

[womenclature]

What is the evidence that they don’t have the required training? These DOGE employees aren’t just your random average coders. They’re some of the best and brightest analytical minds of their generation. Why should they not be able to understand the government’s computer software systems and properly analyze their data? In some ways, these employees have handled far more complex projects in the past… I think the post shown here is not really being fair or taking enough information into account before forming an opinion. I think OP *wants* to believe that anything having to do with Trump is evil, and will therefore ignore evidence to the contrary.

The DOGE Team

Here are some excerpts from an article that shares more about the team.

"Edward Coristine [19] ... is a college student at Northeastern University in Boston. He’s already interned at Musk’s Neuralink and is seen as an expert in his field. “

"Akash Bobba [21] … previously interned at Meta and Palantir, and his background in investment engineering and data analysis makes him a valuable asset in streamlining government operations.” (Akash is also Indian.)

"Ethan Shaotran [22] is the founder of Energize AI, an AI-driven startup, and a senior at Harvard University. With a background in computing and autonomous vehicles, he’s a perfect fit… ...having participated in the xAI hackathon.”

"Luke Farritor [23] is no stranger to high-pressure problem-solving. A former intern at SpaceX … Luke’s AI skills were on full display when he helped decipher ancient Vesuvius scrolls” Please allow me to add something here about that Vesuvius Challenge. Source Farritor figured out how to read these extremely fragile burnt scrolls without unrolling them. He solved a problem that experts has been puzzling over for years.

"Contestants had until the end of 2023 to decipher one of around 1,000 Herculaneum Papyri scrolls recovered from the library of the Villa dei Papyri, which was decimated by the same 79 CE eruption of Mount Vesuvius that froze the city of Pompeii in time. Discovered in the eighteenth century, the excavated scrolls have been sitting in museums and universities around Europe, unable to be touched “without them turning to ash,” Farritor said.”

“Left: the scroll read by the winners. Right: result of an attempt to physically unroll a scroll. (Vesuvius Challenge)” "Farritor explained to me that his AI program took the image of the scroll and chopped it up into “tiny bits of 100 pixels by 100 pixels. And then the machine learning algorithm looks at each one and it asks itself, do I think there’s ink here? Or do I think there’s no ink here?” By compiling these tiles, the AI program can do what was impossible only a few years ago: read the scroll.”

Moving on… (Back to our prior article.)

5. "Gautier Cole Killian [24] … brings his expertise from the high-frequency trading world, where he worked at Jump Trading. … Gautier’s background in algorithms and financial markets positions him to make big changes in how government funds are managed."

6. "Gavin Kliger [25] ... the oldest of the group, has a unique role in DOGE, having made waves by sending a controversial email that shook up the USAID staff. A graduate of Berkeley, Gavin’s no stranger to big decisions and leadership roles. His willingness to leave a seven-figure salary to join Musk’s mission underscores his dedication to reforming government systems.”

My Point

As we can see, all of these young men are quite capable. I think that many posts on Tumblr, like the ones shown in the original post above, oversimplify and misconstrue the actual facts in favor of supporting a more shocking and upsetting narrative. Please take time to review some of the information related to the claims you’re seeing. Take a little time to decide whether you actually want to incorporate a claim into your worldview. Don’t blindly accept anything.

“But these boys are too young!”

-In 1777, when Alexander Hamilton was (at most) 22 years old, "he had captured the attention of the army’s commander-in-chief, General George Washington, who gave him a position on his staff.” (Source) -In 1797, when Gauss was only 20, his "doctoral thesis of 1797 gave a proof of the fundamental theorem of algebra.” (Source) -In 1773, when Mozart was just 17, he had already composed his very famous Symphony No. 25 in G minor, K. 183 (Youtube video link if you’d like to listen).

-Évariste Galois only made it to 20 y.o., but he had already made groundbreaking contributions to mathematics by the time he died in a pistol duel in 1832. "While still in his teens, he was able to determine a necessary and sufficient condition for a polynomial to be solvable by radicals, thereby solving a problem that had been open for 350 years. His work laid the foundations for Galois theory and group theory, two major branches of abstract algebra.” [Wikipedia] -Ada Lovelace (1815–1852) Wrote the first algorithm intended to be processed by a machine, making her the world’s first computer programmer at the age of 25 (working with Charles Babbage’s Analytical Engine).

-By the age of 25, Alexander the Great (356–323 BCE) had already conquered most of the known world, including Persia and Egypt, creating one of the largest empires in history.

-By the time he was 25, Johannes Kepler (1571–1630) had developed his laws of planetary motion, which were foundational in understanding how planets orbit the sun.

Conclusion

To quote Akash Bobba at his UC Berkeley graduation in 2021: "We live in an age where simplicity reigns supreme, where 30-second TikToks and 280-character tweets come to define our identities,” he then said. “This increasing willingness to simplify even the most complex narratives into sensational tidbits, perpetuates misinformation and in the process divides the communities, families, and relationships we cherish. What’s the solution, you might ask? Seek discomfort.”

It's a heist. Elon is the fraud. DOGE is the fraud. The coders destroying databases are the waste.

[fromdevcom]

Every so often we come across terms such as Artificial Intelligence (AI) or Machine Learning (ML) in popular media and public in general. These terms have become much closer to reality than most of us dare to admit, engineers and top writers included. While we may be far from stable autonomous AI technologies, Machine Learning is a different beast entirely. What exactly is Machine Learning and why do you need to know about it now that we have stepped far enough into the 21st century? The Definition of Machine Learning As you might have summarized from the term itself, ML stands for independent AI-driven learning that allows devices to learn new algorithms in order to be more efficient at their jobs. This may be too much to process at once, but there is a multitude of applications in which Machine Learning is already implemented. These encompass services such as travel navigation applications, self-driven cars, and even services that provide online college help. Devices and applications that use ML technology use Big Data as a hub for their learning needs, applying statistical analysis to necessary information and learning as they go along. This technological breakthrough is changing the computer landscape as we speak, which is one of the many reasons to seriously consider ML as a skill to learn. Why You Should Care About Machine Learning A chance to change the world People who work closely with Machine Learning technologies have a rare chance to be a part of the change that is coming to our world. If you have ever used social media or popular sites such as YouTube or LinkedIn, you would have noticed Machine Learning patterns by now. No matter if you are hunting for an essay writing site or an interesting video to share with your friends, ML algorithms are there to help you at every step of the way. Data scientists and Machine Learning experts are sought after in different branches of web development. Hefty salaries that often go above $100,000 are a very good reason to pay some attention to Machine Learning technologies. Different Machine Learning Specializations Machine Learning experts often fall into two categories. On one hand, people that are in charge of programming machine learning devices fall into the “unsupervised” category. These expert programmers work on making sure that Machine Learning devices work the way they should. Such is the case with AI-driven vehicle systems, smart house systems that operate household items and balance the quality of life, etc. On the other hand, “supervised” experts work on already programmed Machine Learning devices in order to ensure the maximum quality of service for these devices and their users. Some devices simply need a human touch in order to work correctly, like in the case of essay paper help services online. The ability to focus on one of these ML specializations offers people to not only inform them about the technology but also learn as much or less as they want at any given moment. Data Analysis and Big Data Many experts overlook the significance of Machine Learning due to its surface message and the fact that it represents the next step in AI development. But what are the implications of adapting Machine Learning in large corporations that focus on data mining, analysis, and evaluation? ML technologies are more than capable of integrating algorithms into existing workflows in order to provide genuine feedback for their users. For example, if you were to ask your computer station for the last month’s data analysis or even write help with your report, it would be obliged to help you in an instant. These analytical positions may soon be filled with AI-driven machines that do things much faster than humans, allowing living breathing people to focus on more pressing matters. Big Data plays a huge part in what makes Machine Learning so interesting for many companies. Implementing ML algorithms into Big Data servers and allowing them to scrounge information from your available archives can save you months of on-foot analysis.

Not to mention the potential for report essay help, creating viable presentations for your corporate meetings, or even doing the company accounting for you. Vast Implementation Options You might have noticed a pattern of different Machine Learning implementations that lead to a very clear answer – this technology is omnipotent in its application. Machine Learning has successfully been implemented in a variety of different fields such as health care, transportation, online marketing, and sales, as well as writing help and financial services. The sheer amount of fields you can dedicate your time to in order to make an impact by using Machine Learning is nothing short of astonishing. Keep in mind that some core principles still apply and supervised or unsupervised ML algorithms are still very much present in every field. The reason for that is the ability to produce a device that can learn from seeing how a human does something and then repeating the process as many times as needed. While Machine Learning devices still can’t exchange a human touch in their work, they can still work relentlessly if shown how to do so. Even if you have a passing interest in Machine Learning, it’s still good practice to familiarize yourself with the benefits of implementing this technology in our everyday life. In Summation Machine Learning technologies are already present in large due to our constant use of social media such as Facebook and Instagram. Corporations are learning how to implement these algorithms to the best of their knowledge in order to provide better service for their clients. We have only scratched the surface of what Machine Learning is bringing with each passing day and the technology is poised to dethrone artificial intelligence in the future. If you or someone you know is facing a technical problem that can’t be solved with traditional programming or web development means, consider using ML technologies to help you out. Start simple and see how the algorithms react to your instructions before choosing to implement them completely.

[praveennareshit]

☁️ Cloud Computing Courses for Beginners (2025): Where to Start and What to Expect

👨🎓 New to Tech? Wondering if You Can Learn Cloud Computing?

You’ve seen the job listings. You’ve heard about AWS, Azure, and Google Cloud. You might’ve even asked yourself, “Is this something I can learn, or is it only for experienced developers?”

Here’s the honest answer: Yes, you absolutely can learn cloud computing—even as a beginner. And no—you don’t need to be a coder to get started.

🧠 What Exactly Is Cloud Computing?

Let’s break it down in real-world terms.

Cloud computing is about accessing technology services (like servers, storage, and databases) over the internet instead of owning them physically. Just like you stream music without downloading every song, companies use cloud platforms to run apps without buying physical machines.

This makes cloud computing:

🔄 Scalable

⚡ Fast

💰 Cost-effective

🌐 Accessible from anywhere

Think of it as “IT on rent.”

🌐 What Are the Major Cloud Platforms?

There are three major players in the cloud computing space:

🔹 Amazon Web Services (AWS)

Largest market share globally

Great documentation and job demand

Ideal for beginners starting a cloud career

🔹 Microsoft Azure

Preferred by companies already using Microsoft services

Common in large enterprises and MNCs

Works well for IT support engineers or Windows admins

🔹 Google Cloud Platform (GCP)

Known for machine learning, analytics, and modern web apps

Growing ecosystem with startups and AI companies

Ideal for learners with interest in data + development

🎓 What to Expect from a Beginner-Friendly Cloud Course?

The right course should cover:

Cloud concepts: IaaS, PaaS, SaaS

Platform navigation (AWS Console, Azure Portal, GCP Dashboard)

Virtual Machines, storage, identity & access

Networking and basic security setup

Hands-on labs and small projects

Guidance for entry-level certifications

And most importantly, it should be beginner-friendly—not overloaded with theory or code.

🧑🏫 Why Learn Cloud with NareshIT?

At NareshIT, we’ve trained over 100,000 students in real-world IT skills. Our cloud computing courses are designed to help absolute beginners start from scratch, learn hands-on, and become confident enough to apply for jobs or certifications within weeks.

📘 NareshIT’s Cloud Computing Courses for Beginners

✅ AWS Cloud Foundations (Beginner Level)

Duration: 60 Days

Topics: EC2, IAM, S3, Lambda, VPC

Bonus: Live labs, project guidance, AWS Cloud Practitioner & Associate certification prep

Outcome: Ready for junior cloud jobs & support roles

✅ Azure Essentials Course (Beginner + Admin)

Duration: 45 Days

Topics: Azure AD, VMs, Blob Storage, Azure Monitor

Bonus: AZ-900 + AZ-104 prep, DevOps preview

Outcome: Ideal for support engineers and system admins

✅ GCP Starter Course (Beginner + Cloud Native Tools)

Duration: 30 Days

Topics: Compute Engine, IAM, BigQuery, Cloud Functions

Bonus: GCP Associate Cloud Engineer certification coaching

Outcome: Great for data lovers and devs entering cloud

🎓 DevOps with Multi-Cloud Training in KPHB by NareshIT

Located in Hyderabad’s tech-learning hub, NareshIT’s DevOps with Multi-Cloud Training in KPHB is tailored for:

✅ Beginners who want an IT job fast

✅ Professionals switching from support/manual testing

✅ Freshers looking for job-ready cloud + DevOps skills

🧾 Course Highlights:

Cloud Platforms Covered: AWS, Azure, GCP

DevOps Tools: Git, Jenkins, Docker, Kubernetes, Terraform

Duration: ~60 days

Batch Options: Weekday, Weekend, Fast-track

Includes: Real-world projects, certification support, job readiness prep

Location: KPHB, Hyderabad (Online + Offline options)

📅 New Batches Are Starting Now Choose from weekday, weekend, or fast-track options based on your schedule.

👉 Check NareshIT's Latest Cloud Batches Here

🧩 Bonus: Why Learning Cloud Computing Is Worth It

💼 High-demand job roles: Cloud support, DevOps, Admin

💸 Strong entry-level salaries: ₹4.5 to ₹7 LPA (for certified freshers)

🌱 Fast career growth: Start simple, grow into architecture or security

🌍 Global opportunities: Remote jobs across India, US, UAE, and more

You don’t need to master everything at once. Just start with one platform. And with the right mentor, you'll move faster than you thought possible.

[educationtech]

Top 10 In-Demand Courses for BTech CSE Graduates in 2025

In Arya College of Engineering & I.T. guide students for choosing the right course after a BTech in Computer Science Engineering (CSE) can significantly boost your career prospects. The technology sector is rapidly evolving, and specialized skills are in high demand. Here are ten of the best courses you can pursue after BTech CSE, along with the job opportunities they offer in 2025:

1. Master of Technology (MTech) in Computer Science

Deepens your technical expertise in core computer science areas.

Opens doors to roles such as Software Developer, Systems Architect, and Research Engineer in top tech companies and research organizations.

2. Master of Science (MS/MSc) in Computer Science or Engineering

Offers advanced learning and research in areas like AI, data science, cybersecurity, and software engineering.

Graduates can pursue roles such as Data Scientist, Machine Learning Engineer, and Cloud Solutions Architect.

3. MBA in Information Technology

Combines management skills with IT knowledge, preparing you for leadership roles.

Leads to positions like IT Manager, Product Manager, and Technology Consultant in IT firms and startups.

4. Masters in Data Science or Big Data Analytics

Focuses on data analysis, machine learning, and business intelligence.

High demand for Data Scientists, Data Analysts, and Business Intelligence Analysts across industries.

5. Masters in Artificial Intelligence and Machine Learning

Specialized training in AI algorithms, robotics, and deep learning.

Opens up careers as an AI Engineer, Research Scientist, and NLP Engineer in tech giants and research labs.

6. Masters in Cybersecurity

Covers network security, ethical hacking, and digital forensics.

Growing need for Cybersecurity Analysts, Security Engineers, and Information Security Managers in both private and government sectors.

7. Masters in Software Engineering

Advanced study in software development, testing, and project management.

Prepares you for roles like Senior Software Engineer, DevOps Engineer, and Software Project Manager.

8. Masters in Cloud Computing

In-depth knowledge of cloud platforms, virtualization, and distributed systems.

Cloud Solutions Architect, Cloud Engineer, and Cloud Security Specialist are highly sought-after roles.

9. Masters in Computer Networking or Network Engineering

Focuses on network design, management, and security.

Network Engineer, Network Architect, and Systems Administrator roles are available in IT infrastructure companies.

10. Certification Courses (Short-term/Online)

Specialized certifications in fields like Blockchain, Internet of Things (IoT), Full Stack Development, or DevOps.

These certifications can quickly upskill you for niche roles such as Blockchain Developer, IoT Solutions Architect, or DevOps Engineer.

Job Opportunities and Industry Demand

Data Science, AI, and Cybersecurity are among the fastest-growing fields, with high salaries and global demand.

Cloud Computing and Software Engineering continue to be core areas for IT companies, offering stability and growth.

Management roles (with an MBA) are ideal for those interested in leadership and strategic decision-making.

Certification courses provide flexibility and can be pursued alongside jobs to specialize in emerging technologies.

Summary Table

Course/Specialization

Key Job Roles

Industry Demand in 2025

MTech/MS/MSc in Computer Science

Software Developer, Systems Architect

High

MBA in IT

IT Manager, Product Manager

High

Master's in Data Science/Big Data

Data Scientist, BI Analyst

Very High

Masters in AI & Machine Learning

AI Engineer, Research Scientist

Very High

Masters in Cybersecurity

Security Analyst, Security Engineer

Very High

Masters in Software Engineering

Senior Software Engineer, DevOps Engineer

High

Masters in Cloud Computing

Cloud Architect, Cloud Engineer

Very High

Masters in Computer Networking

Network Engineer, Systems Admin

High

Certification in Blockchain/IoT/DevOps

Blockchain Developer, IoT Architect

Growing

Masters in Network Engineering

Network Architect, Network Analyst

High

Pursuing any of these courses after BTech CSE in 2025 will enhance your skills, increase employability, and position you for success in the rapidly evolving tech landscape.