#how to become data scientist

[mitcenter]

How to become Data scientist | 8 Essential Steps for Success

Unlock the secrets to becoming a successful data scientist with "Become a Successful Data Scientist: 8 Essential Career Steps." This comprehensive guide outlines a strategic roadmap for aspiring data scientists, providing a clear path to success in this dynamic field. Delve into the intricacies of data science, mastering key skills and techniques that set the foundation for a thriving career. From acquiring the right education and technical proficiency to gaining practical experience and building a strong professional network, these eight essential steps act as a compass, guiding you through the challenging terrain of the data science landscape. Discover the transformative journey that awaits as you embark on the quest to become a highly sought-after data scientist, equipped with the knowledge and expertise to excel in this rapidly evolving field.

[swallowtail-ageha]

Ive heard people being divisive in particular about these two things of evichro, but honestly 1) the songs being romanticized retellings of history by Ma who is using them as plots for her plays and 2) the big post apocaliptic sci-fi plot twist are genuinely my favourite part of the series because it really genuinely makes it unique

[education43]

What Are the Qualifications for a Data Scientist?

In today's data-driven world, the role of a data scientist has become one of the most coveted career paths. With businesses relying on data for decision-making, understanding customer behavior, and improving products, the demand for skilled professionals who can analyze, interpret, and extract value from data is at an all-time high. If you're wondering what qualifications are needed to become a successful data scientist, how DataCouncil can help you get there, and why a data science course in Pune is a great option, this blog has the answers.

The Key Qualifications for a Data Scientist

To succeed as a data scientist, a mix of technical skills, education, and hands-on experience is essential. Here are the core qualifications required:

1. Educational Background

A strong foundation in mathematics, statistics, or computer science is typically expected. Most data scientists hold at least a bachelor’s degree in one of these fields, with many pursuing higher education such as a master's or a Ph.D. A data science course in Pune with DataCouncil can bridge this gap, offering the academic and practical knowledge required for a strong start in the industry.

2. Proficiency in Programming Languages

Programming is at the heart of data science. You need to be comfortable with languages like Python, R, and SQL, which are widely used for data analysis, machine learning, and database management. A comprehensive data science course in Pune will teach these programming skills from scratch, ensuring you become proficient in coding for data science tasks.

3. Understanding of Machine Learning

Data scientists must have a solid grasp of machine learning techniques and algorithms such as regression, clustering, and decision trees. By enrolling in a DataCouncil course, you'll learn how to implement machine learning models to analyze data and make predictions, an essential qualification for landing a data science job.

4. Data Wrangling Skills

Raw data is often messy and unstructured, and a good data scientist needs to be adept at cleaning and processing data before it can be analyzed. DataCouncil's data science course in Pune includes practical training in tools like Pandas and Numpy for effective data wrangling, helping you develop a strong skill set in this critical area.

5. Statistical Knowledge

Statistical analysis forms the backbone of data science. Knowledge of probability, hypothesis testing, and statistical modeling allows data scientists to draw meaningful insights from data. A structured data science course in Pune offers the theoretical and practical aspects of statistics required to excel.

6. Communication and Data Visualization Skills

Being able to explain your findings in a clear and concise manner is crucial. Data scientists often need to communicate with non-technical stakeholders, making tools like Tableau, Power BI, and Matplotlib essential for creating insightful visualizations. DataCouncil’s data science course in Pune includes modules on data visualization, which can help you present data in a way that’s easy to understand.

7. Domain Knowledge

Apart from technical skills, understanding the industry you work in is a major asset. Whether it’s healthcare, finance, or e-commerce, knowing how data applies within your industry will set you apart from the competition. DataCouncil's data science course in Pune is designed to offer case studies from multiple industries, helping students gain domain-specific insights.

Why Choose DataCouncil for a Data Science Course in Pune?

If you're looking to build a successful career as a data scientist, enrolling in a data science course in Pune with DataCouncil can be your first step toward reaching your goals. Here’s why DataCouncil is the ideal choice:

Comprehensive Curriculum: The course covers everything from the basics of data science to advanced machine learning techniques.

Hands-On Projects: You'll work on real-world projects that mimic the challenges faced by data scientists in various industries.

Experienced Faculty: Learn from industry professionals who have years of experience in data science and analytics.

100% Placement Support: DataCouncil provides job assistance to help you land a data science job in Pune or anywhere else, making it a great investment in your future.

Flexible Learning Options: With both weekday and weekend batches, DataCouncil ensures that you can learn at your own pace without compromising your current commitments.

Conclusion

Becoming a data scientist requires a combination of technical expertise, analytical skills, and industry knowledge. By enrolling in a data science course in Pune with DataCouncil, you can gain all the qualifications you need to thrive in this exciting field. Whether you're a fresher looking to start your career or a professional wanting to upskill, this course will equip you with the knowledge, skills, and practical experience to succeed as a data scientist.

Explore DataCouncil’s offerings today and take the first step toward unlocking a rewarding career in data science! Looking for the best data science course in Pune? DataCouncil offers comprehensive data science classes in Pune, designed to equip you with the skills to excel in this booming field. Our data science course in Pune covers everything from data analysis to machine learning, with competitive data science course fees in Pune. We provide job-oriented programs, making us the best institute for data science in Pune with placement support. Explore online data science training in Pune and take your career to new heights!

[psych0p0mp-on-ao3]

The scientist urge to analyze my ao3 stats

[juliebowie]

How to Become a Data Scientist after 10th: A Roadmap

Summary: Learn the essential steps and skills required to become a Data Scientist after 10th grade, including subject selection, additional courses, higher education paths, and gaining practical experience.

Introduction 

Data Science is revolutionising industries with its ability to analyse vast amounts of data for actionable insights. Pursuing a career in Data Science is highly beneficial due to the increasing demand for skilled professionals and the lucrative opportunities available. 

This article aims to guide students who have completed their 10th grade on how to become Data Scientists after 10th grade. It provides a clear roadmap highlighting essential steps, skills, and educational paths necessary to embark on this exciting career journey, ensuring students are well-prepared for future success in the dynamic field of Data Science.

Understanding Data Science

Data Science is an interdisciplinary field that uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data. It encompasses various techniques and tools for understanding and interpreting complex data sets. 

The scope of Data Science extends beyond mere data analysis; it includes data collection, data cleaning, data visualisation, and predictive modelling. Data Science turns raw data into actionable insights, driving decision-making across various industries.

Key Components and Skills Required in Data Science

To excel in Data Science, one must master several key components and skills. Firstly, a solid understanding of statistics is crucial. Statistics provides the foundation for making inferences about data and testing hypotheses. 

Secondly, proficiency in programming is essential. Languages like Python and R are widely used for data manipulation and analysis. Additionally, familiarity with SQL is vital for querying databases.

Furthermore, data analysis skills are necessary for exploring and interpreting data sets. This involves using statistical methods to identify patterns, correlations, and trends. Machine learning is another critical component, enabling Data Scientists to build predictive models and automate decision-making processes.

Lastly, data visualisation skills are essential for clearly presenting findings and compellingly using tools like Tableau and Power BI.

Different Roles and Career Paths Within Data Science

Data Science offers diverse career paths, each with distinct roles and responsibilities. A data analyst interprets data and generates reports to support business decisions. They often use large data sets to identify trends and provide actionable insights.

A data engineer builds and maintains the data generation, storage, and processing infrastructure. They ensure that data pipelines are robust and scalable, enabling efficient data flow within the organisation.

A machine learning engineer designs and deploys machine learning models. They work on developing algorithms that can learn from data and make predictions or decisions without explicit programming.

Other roles include data architects, who design data frameworks, and business intelligence analysts, who leverage data to drive business strategies. With such a broad array of opportunities, Data Science professionals can tailor their careers to their interests and strengths, making it a dynamic and rewarding field.

Roadmap to Becoming a Data Scientist after 10th

By following this roadmap and leveraging resources like Pickl.AI’s comprehensive Data Science courses and practical learning opportunities, you can set yourself on a successful path to becoming a Data Scientist.

Choosing the Right Subjects in 11th and 12th

Becoming a Data Scientist begins with the subjects you choose in your 11th and 12th grades. Mathematics forms the backbone of Data Science, providing the essential tools for statistical analysis, algorithm development, and problem-solving. Concepts such as calculus, linear algebra, and probability are fundamental to understanding Data Science methodologies.

Computer Science is another crucial subject. It introduces you to programming languages, data structures, and algorithms integral to data manipulation and analysis. Understanding how computers process data will give you a solid foundation for more advanced Data Science topics.

In addition, subjects like physics and economics can be beneficial. They help develop analytical thinking and an understanding of data science's real-world applications.

Recommendations for Additional Courses or Certifications during School

To further bolster your knowledge and skills, consider enrolling in additional courses or certifications related to Data Science. Online platforms offer courses specifically designed for high school students. Pickl.AI, for instance, provides some of India's best Data Science courses for beginners and professionals.

At Pickl.AI, you can benefit from:

Monthly Offline Interactions: Engage in face-to-face sessions with industry experts to clarify doubts and gain deeper insights.

Real Projects: Work on actual Data Science projects that provide hands-on experience and enhance your practical skills.

Doubt Clearing Sessions: Regular sessions address your queries and ensure you understand the concepts thoroughly.

Consider taking courses such as:

Data Science Bootcamp

Job Preparation Program

Data Science Course for Kids

Python for Data Science

Data Analytics Certification Course

ML 101 – Introduction to Machine Learning

ChatGPT Course

These courses offer a range of learning formats, from free one-hour sessions to comprehensive bootcamps with 100+ hours of expert-led lectures, placement support, and flexible learning options. 

Pursuing Relevant Higher Education

After completing 12th grade, the next step is pursuing an undergraduate degree in a relevant field. Degrees like B.Sc in Data Science, Computer Science, Statistics, or Mathematics are highly recommended. These programs provide a structured curriculum covering essential Data Science theories and practices.

However, there are other paths to becoming a Data Scientist than traditional degrees. Diplomas and online courses can also be practical, especially for those who prefer a more flexible learning schedule. Many online platforms offer industry-recognised specialised Data Science courses that provide useful knowledge. Pickl.AI’s offerings, for instance, include:

Data Science Tools: Learn to use cutting-edge tech tools trusted by thousands of companies.

Free Anytime Learning: Flexible courses that you can start anytime.

Gaining Practical Experience

To excel in Data Science, you need more than just theory. Practical experience is crucial. Internships, projects, and practical training allow you to apply your knowledge in real-world scenarios. 

Look for internships at companies that have strong Data Science teams. During internships, you will learn how to handle actual data, use Data Science tools, and work in a professional environment.

Participating in Data Science competitions and hackathons can significantly enhance your skills. Platforms like Kaggle host competitions that challenge you to solve complex data problems. These competitions provide an excellent opportunity to test your skills, learn from others, and gain recognition in the Data Science community.

Developing Key Skills

Proficiency in programming languages is a must for any aspiring Data Scientist. Start with Python, as it is widely used in the industry due to its simplicity and extensive libraries for data analysis. R is another valuable language, particularly for statistical analysis and data visualisation.

Beyond programming, you should also gain knowledge in databases, data visualisation, and machine learning. Understanding SQL and NoSQL databases is essential for managing and querying large datasets. 

Tableau and Power BI are crucial for visualising data and deriving insights. Machine learning, the core of Data Science, involves algorithms and models that can predict outcomes and identify patterns in data.

Building a Strong Portfolio

A strong portfolio showcases your skills and projects to potential employers. It is evidence of your practical experience and ability to apply Data Science concepts effectively. Include a variety of projects that demonstrate your expertise in different areas of Data Science, such as data cleaning, visualisation, machine learning, and statistical analysis.

To make your portfolio stand out, ensure each project is well-documented. Explain the problem you tackled, the approach you took, the tools and techniques you used, and the results you achieved. 

Use platforms like GitHub to host your projects and make them easily accessible to others. Regularly update your portfolio with new projects and improvements to showcase your continuous learning and growth in the field.

Frequently Asked Questions

How can students pursue Data Science after 10th grade?

After 10th grade, students should choose Mathematics and Computer Science in 11th and 12th grades, take relevant online courses, gain practical experience through projects, and pursue higher education in Data Science.

What skills are essential for becoming a Data Scientist after 10th grade?

Essential skills include proficiency in statistics, programming (Python, R), data analysis, machine learning, and data visualisation. Students should also develop problem-solving and analytical thinking skills.

What higher education paths should students follow to become Data Scientists?

Students can pursue Data Science, Computer Science, Statistics, or Mathematics degrees. Online courses, diplomas, and practical training through internships and projects are also beneficial.

Conclusion

Becoming a Data Scientist after 10th grade involves strategic planning and dedication. By choosing the proper subjects, gaining relevant skills, pursuing higher education, and acquiring practical experience, students can build a strong foundation for a successful career in Data Science. 

With continuous learning and hands-on practice, the journey to becoming a proficient Data Scientist is achievable and rewarding.

[cromacampusinstitute]

To become a data scientist after the 12th grade, pursue a bachelor's degree in computer science, mathematics, or a related field. Focus on acquiring skills in programming (Python, R), statistics, and machine learning. Engage in online courses and certifications for additional expertise. Participate in internships and projects to gain practical experience.

[arolesbianism]

Vibrates. Normal. I'm normal. I'm so normal.

[reasonsforhope]

"A century of gradual reforestation across the American East and Southeast has kept the region cooler than it otherwise would have become, a new study shows.

The pioneering study of progress shows how the last 25 years of accelerated reforestation around the world might significantly pay off in the second half of the 21st century.

Using a variety of calculative methods and estimations based on satellite and temperature data from weather stations, the authors determined that forests in the eastern United States cool the land surface by 1.8 – 3.6°F annually compared to nearby grasslands and croplands, with the strongest effect seen in summer, when cooling amounts to 3.6 – 9°F.

The younger the forest, the more this cooling effect was detected, with forest trees between 20 and 40 years old offering the coolest temperatures underneath.

“The reforestation has been remarkable and we have shown this has translated into the surrounding air temperature,” Mallory Barnes, an environmental scientist at Indiana University who led the research, told The Guardian.

“Moving forward, we need to think about tree planting not just as a way to absorb carbon dioxide but also the cooling effects in adapting for climate change, to help cities be resilient against these very hot temperatures.”

The cooling of the land surface affected the air near ground level as well, with a stepwise reduction in heat linked to reductions in near-surface air temps.

“Analyses of historical land cover and air temperature trends showed that the cooling benefits of reforestation extend across the landscape,” the authors write. “Locations surrounded by reforestation were up to 1.8°F cooler than neighboring locations that did not undergo land cover change, and areas dominated by regrowing forests were associated with cooling temperature trends in much of the Eastern United States.”

By the 1930s, forest cover loss in the eastern states like the Carolinas and Mississippi had stopped, as the descendants of European settlers moved in greater and greater numbers into cities and marginal agricultural land was abandoned.

The Civilian Conservation Corps undertook large replanting efforts of forests that had been cleared, and this is believed to be what is causing the lower average temperatures observed in the study data.

However, the authors note that other causes, like more sophisticated crop irrigation and increases in airborne pollutants that block incoming sunlight, may have also contributed to the lowering of temperatures over time. They also note that tree planting might not always produce this effect, such as in the boreal zone where increases in trees are linked with increases in humidity that way raise average temperatures."

-via Good News Network, February 20, 2024

[feminist-space]

"Balaji’s death comes three months after he publicly accused OpenAI of violating U.S. copyright law while developing ChatGPT, a generative artificial intelligence program that has become a moneymaking sensation used by hundreds of millions of people across the world.

Its public release in late 2022 spurred a torrent of lawsuits against OpenAI from authors, computer programmers and journalists, who say the company illegally stole their copyrighted material to train its program and elevate its value past $150 billion.

The Mercury News and seven sister news outlets are among several newspapers, including the New York Times, to sue OpenAI in the past year.

In an interview with the New York Times published Oct. 23, Balaji argued OpenAI was harming businesses and entrepreneurs whose data were used to train ChatGPT.

“If you believe what I believe, you have to just leave the company,” he told the outlet, adding that “this is not a sustainable model for the internet ecosystem as a whole.”

Balaji grew up in Cupertino before attending UC Berkeley to study computer science. It was then he became a believer in the potential benefits that artificial intelligence could offer society, including its ability to cure diseases and stop aging, the Times reported. “I thought we could invent some kind of scientist that could help solve them,” he told the newspaper.

But his outlook began to sour in 2022, two years after joining OpenAI as a researcher. He grew particularly concerned about his assignment of gathering data from the internet for the company’s GPT-4 program, which analyzed text from nearly the entire internet to train its artificial intelligence program, the news outlet reported.

The practice, he told the Times, ran afoul of the country’s “fair use” laws governing how people can use previously published work. In late October, he posted an analysis on his personal website arguing that point.

No known factors “seem to weigh in favor of ChatGPT being a fair use of its training data,” Balaji wrote. “That being said, none of the arguments here are fundamentally specific to ChatGPT either, and similar arguments could be made for many generative AI products in a wide variety of domains.”

Reached by this news agency, Balaji’s mother requested privacy while grieving the death of her son.

In a Nov. 18 letter filed in federal court, attorneys for The New York Times named Balaji as someone who had “unique and relevant documents” that would support their case against OpenAI. He was among at least 12 people — many of them past or present OpenAI employees — the newspaper had named in court filings as having material helpful to their case, ahead of depositions."

[vakilkarosblog]

A Nidhi company registration is a type of non-banking financial institution (NBFC) that primarily exists for cultivating the habit of thrift and savings amongst its members. It functions on the principle of mutual benefit - the funds contributed by the members are recycled within the group, providing them with loans at reasonable interest rates. These companies are regulated by the Ministry of Corporate Affairs in India. Read More

[vlruso]

How to Become a Data Scientist After the 12th Standard?

🌟 Exciting news! Are you a young professional fascinated by the field of data science? "How to Become a Data Scientist After the 12th Standard?" is a must-read article that explores the rising popularity of data science as a career choice! 📈✨ Discover how this industry has evolved over the years and catch valuable insights. Whether you're just starting out or looking to advance your skills, this article from Analytics Vidhya can provide some guidance. 📚 Don't miss your chance to explore the opportunities in this booming field! Check out the article here: https://ift.tt/ZiT6SPe 📲✅ For more interesting content related to AI, data science, and beyond, follow us on Twitter @itinai_com! 🐦💼 #data #science #career #opportunities List of Useful Links: AI Scrum Bot - ask about AI scrum and agile Our Telegram @itinai Twitter -  @itinaicom

[themanjeet]

How to Become a Data Scientist

Data science is a rapidly growing field, and the demand for skilled data scientists is high.

https://medium.com/@rolandmack63/how-to-become-a-data-scientist-degrees-skills-and-pathway-b09d04eabf1b

[sunarryn]

DP X Marvel #27

Danny wasn’t trying to become a supervillain’s protégé. Honestly, he was just trying to survive another semester at MIT without spontaneously combusting from stress. At nineteen, between triple-majoring in Astrophysics, Mechanical Engineering, and Paranormal Biochemistry—and moonlighting as the occasionally-glowy, occasionally-exploding, semi-competent vigilante known to the public as Phantom—Danny was hanging on by a thread. A very frayed, very caffeine-soaked thread. So when one of his professors suggested a special “independent study project” with a visiting Latverian dignitary-slash-scientist, Danny said yes without thinking. He needed the credits. He needed the money. He needed the free lunch vouchers. What he did not need, apparently, was to accidentally apprentice himself to Doctor Fucking’ Doom.

At first, he didn’t know. To Danny, “Victor” was just this weird, intense European dude with a crazy sense of fashion (who the hell wore a green cape in broad daylight?) and a laugh that definitely belonged in a villain origin story. But Victor paid well, never judged him for falling asleep mid-sentence, and always had the best coffee imported from who-knows-where. Danny figured he was just some rich old nerd with a lot of quirks. Maybe a little murder-y, but hey, Danny was from Amity Park. His standards for “dangerous mentor figure” were catastrophically low.

“Daniel,” Victor intoned one day, standing over a schematic that looked suspiciously like a laser death satellite. “Tell me: what improvements would you make to a mobile interdimensional particle cannon capable of vaporizing Manhattan?”

Danny, who hadn’t slept in three days and thought this was just a theoretical design, squinted at the blueprints and muttered, “Uh… you forgot the phase stabilizer. Without it, the cannon would rip itself apart before you could fire. Also, your aim’s gonna suck unless you recalibrate the gyroscopic system.”

Victor went unnaturally still. “Explain.”

Danny yawned so hard his jaw cracked. “M’kay, so if you adjust the vibrational harmonics here”—he drew all over the deadly weapon diagram with a crayon—“and rework the mana-infused crystal lattice to resonate at a higher frequency… boom. Stable, precise, terrifying. A+ on your murder machine, Professor Von Evilcape.”

Victor stared at him for a long time. Then he laughed. Not just any laugh. A full, villainous, booming laugh that echoed through the lab and set off three alarms in the next building over. Danny didn’t even blink. He just kept doodling tiny ghosts on the margins of the schematic.

From that moment onward, Victor—Doctor Doom, actual dictator of Latveria, sorcerer supreme wannabe, world-class narcissist—decided Danny was his heir apparent. His secret weapon. His beautiful chaotic son who understood him better than any of the clowns in Latveria ever had. He didn’t ask Danny if he wanted the role. He just started sending Danny increasingly absurd “assignments” that Danny, running on Monster Energy and bad life choices, completed without registering how criminally insane they were.

Case in point: one evening, Danny stumbled into the lab with a Red Bull in one hand and a half-eaten burrito in the other. Victor handed him a device.

“Install this at Stark Tower.”

Danny blinked at the tiny, harmless-looking black box. “Uh, what is it?”

“A signal booster for quantum research purposes.”

Danny, who trusted absolutely no one and also didn’t care because he had a paper due at midnight, shrugged. “Okay, cool.”

He broke into Stark Tower that night with the ease of a sleepwalking raccoon, installed the “signal booster” inside one of Tony Stark’s servers, and left. The next morning, the news was screaming about a massive data breach that almost triggered World War III. Danny was too busy trying to finish his midterm essay on quantum entanglement to notice.

“Good work, Daniel,” Victor said approvingly during their next meeting, clapping him on the back so hard he almost faceplanted into a dimensional rift. “You have the soul of a conqueror.”

“Thanks, man,” Danny mumbled, chugging coffee straight from the pot.

Victor took it a step further. He started introducing Danny at fancy functions. “This is Daniel. He is my most promising apprentice. One day he will inherit my empire.”

Danny, half-dead from exams and not paying attention, just nodded absently and said, “Yup. Love the Empire Strikes Back. Great movie. Big fan.”

Victor beamed.

It wasn’t until six months later, after the “Study Abroad” paperwork (actually an all-expenses-paid trip to Latveria) and the suspiciously grand laboratory gifted to him “for his brilliance,” that Danny realized something was deeply wrong.

He was skimming through some documents on Victor’s encrypted network—because of course Doom had an encrypted network called “DoomNet”—when he found it.

Last Will and Testament of Victor Von Doom: In the event of my death, all of Latveria, my scientific research, all proprietary technology, magical artifacts, nuclear launch codes, hidden doomsday devices, and the title of Supreme Monarch will pass to my chosen heir: Daniel Fenton, aka “Phantom,” aka “My Beautiful Disaster Child.”

Danny read it three times.

“Wait. Wait, wait, wait,” he whispered, voice cracking. “Am I—AM I A VILLAIN PRINCE?!”

Cue the world’s most pathetic breakdown.

“NO NO NO NO NO. I JUST WANTED A DAMN SCHOLARSHIP!” He hurled a coffee mug at the wall. It phased through because he lost control of his intangibility again. “THIS IS WHAT I GET FOR TRUSTING ANYONE IN A CAPE.”

Danny spent the next two hours panic-researching Victor Von Doom. It was bad. It was really bad. It was, like, world-endingly bad. Murder records. Wars. Kidnapping Reed Richards’ kids. Banning Beyoncé from Latveria because she rejected his dinner invitation. BAD.

And it was too late. Doom had gone on international television that morning and announced Danny’s name as his successor.

“I have chosen my heir,” Doom declared, standing proudly atop his gold-plated balcony while cameras flashed below. “The boy shall inherit everything I have built. Bow before your future king, Daniel Fenton!”

Meanwhile, in his MIT dorm room, Danny choked on his cereal.

“Oh my God,” Tucker screamed over Facetime. “YOU’RE DOOM JUNIOR!”

Jazz was furiously typing. “Danny, that’s treason. Like, actual treason.”

Sam just stared at him with unholy glee. “So… when are you conquering America?”

“NEVER,” Danny screeched.

Too late. The Avengers showed up at MIT the next day. It was not subtle.

Tony Stark crashed into Danny’s quantum physics lecture, kicked open the door, and pointed dramatically at him. “YOU!”

Danny, hunched over his notes and running on negative hours of sleep, blinked. “Me?”

“Yeah, you, Doom Boy,” Tony said, stomping down the aisle while half the class screamed and ducked for cover. “You hacked my servers, hijacked my satellites, and installed a literal doom-signal into my mainframe. Care to explain, junior dictator?”

Danny held up his hands. “Okay, look. In my defense, I thought it was a Wi-Fi booster.”

Steve Rogers leaned in. “Are you actively trying to destroy America?”

Danny’s eye twitched. “Sir, I am actively trying to pass Organic Chemistry.”

Natasha Romanoff clicked a pen menacingly. “Are you or are you not plotting to overthrow the world?”

Danny hesitated. “I mean… define ‘plotting’?”

There was a long, painful silence.

Tony sighed, dragging a hand down his face. “Kid. You’re on, like, several different international watchlists. Half of SHIELD thinks you’re planning to nuke New York.”

Danny’s voice cracked. “I didn’t even know how to do laundry until last month.”

And thus began the most chaotic custody battle in history: Doom versus the Avengers versus Danny versus himself.

Victor, naturally, was thrilled. He sent Danny monogrammed armor. A custom throne. A letter that read “My son, all great rulers are hated before they are loved. However feat not. Seize your destiny.”

Danny sent it back with a post-it note that said “pls stop.”

Tony tried to recruit him instead. “Work for me. You like tech, you like coffee, you’re already better at hacking than Peter—”

“HEY,” Peter Parker shouted from across the hall.

Danny groaned into his hands. “I don’t want to work for anyone! I just want a nap!”

Sam Wilson patted him on the back sympathetically. “Welcome to adulthood, kid.”

Things escalated horrifyingly fast. Latverian officials tried to smuggle Danny out of Massachusetts under the cover of night. Doom built a life-sized gold statue of him in Latveria’s capital square. The Avengers started putting “Phantom Threat Level: High” on their briefing files. Nick Fury cornered him in a diner and deadpanned, “Son, you’re one bad day away from becoming an international incident.”

Danny, shoving pancakes in his mouth, muffled, “I don’t wanna.”

Of course, life didn’t let him off that easy.

When Doom inevitably “died”—allegedly vaporized by a malfunctioning time machine because of course he did—Danny woke up to find a legal team at his dorm room.

“Congratulations, Your Majesty,” the lead lawyer said with an evil smile. “You are now King of Latveria.”

Danny fainted on the spot.

He woke up fifteen minutes later to find Sam fanning him with a Doom flag and Tucker wearing a Latverian general’s hat he stole from one of the lawyers.

“So…” Tucker grinned. “Wanna invade Canada first?”

Danny screamed into his pillow.

And somewhere, deep in the void between worlds, Doom—very much alive and sipping espresso—chuckled darkly.

“Atta boy, Daniel,” he whispered. “Atta boy.”

[4kingz]

eyeless jack nsfw headcanons warnings : 18+ mdni, virgin!reader, control without cruelty, anatomy kink, praise kink, obsessive behavior

It’s your first time, and you’re trusting Jack? He doesn’t believe you at first—actually, he pretends he doesn’t hear you when you bring it up.

How could he even think of deflowering you, someone so pure and innocent?

It isn’t until about an hour later, when you finally work up the courage to bring it up again.

“I was waiting for you to make the first move… I didn’t want to scare you…” you mumble, sheepishly dragging your foot across the floor.

YOU? Scare HIM? 

He can’t believe he’s made you wait so long. No, he has to make it up to you, you’re his and he should’ve known better. How could he neglect you like this?

Minutes later, you’re completely helpless—laid out flat on your back, Jack guiding you step by step, every instruction soft but firm.

He doesn’t rush. Every touch, every press of his gloved fingers feel calculated—but hungry. Like he’s starving, but too patient to eat all at once. 

“Lie still.” You try, but your breathing is already unsteady. “You’re twitching,” he murmurs, fingers skimming along your ribs. “I haven’t even started.” 

Touches. Everywhere. His hands wander like they’re mapping you—behind your knees, under your ribs, up your thighs with maddening slowness. He has a fascination with overlooked spots that make you twitch. Just to feel you squirm. He’ll find that one nerve cluster behind your ear and brush it over and over until you’re a whimpering mess. Fingers dipping under the hem of your clothes, grazing skin he’s already touched—only now softer, slower. Studying your reactions like they’re data points

“What’s this spot?” His voice is low, amused, like a scientist with a new specimen.  You jolt when his thumb presses near your hip bone.  “Sensitive? Hmm…” The pad of his glove circles the spot lazily. “Noted.”

Jack isn't mean intentionally—he's just... studying. Learning your every curve, dip and weakness. 

“Does this feel better than before?” He asks, while his fingers make circular motions on your clit, one finger slowly pulsing in and out of your slit. “P-please, Jack, I've already come three tim—” He adds another finger before you can finish.  ... Make that four.

Jack knows that you’ll never be able to experience this kind of pleasure with anyone else. 

After all, no one’s more skilled than him when it comes to human anatomy—no one more in tune with your mind, your body, your needs. You just have to rely on him. Let him take care of you.

He’s quiet, but intense. He doesn’t speak unless he means it, and when he’s silent, the room is thick with tension. The stillness becomes its own kind of pressure, heightening every sensation. Your sounds fill the space instead—your breathing, your moans, the way your voice catches when he does something just right.

“You always sound this pretty, or is it just for me?” You try to stifle the next noise, embarrassed. His voice is low, coaxing. “Don’t hold back. I want to hear everything.”

Control without cruelty. He’s not harsh for the sake of it. He wants to push you, wants to take you apart—but never without care. The softness comes in the way he steadies you afterward. In the way he wraps his body around yours after you’ve fallen apart.

“Breathe.” You didn’t even notice you’d been holding your breath. His hand slides under your head, his voice—still low—finally soothes. “Good girl. You did so well.”

And this—this was only your first time. He pushed you to your limits, and now? That’s the standard. A ritual. You won’t ever know what “normal” feels like, at least not with him. He’s already thinking about next time, already aching for it.

He wants you to be used to him. To his pace, his body, his touch. Because there’s so much more he plans to do to you. A whole world of things he’ll be waiting—patiently—to try.

[skmhlml]

hey! you can make a Enderman x Fem Reader in which he is learning the ways in which she shows pleasure? With smut, pleeeease.

and also, I admit that I've always had a bit of a crush on this monster, and it's at least interesting to see people liking him so much now

P.S: I'll also be so sad when the obsession with him ends

Note: watching kalmekrist rn, feeling pretty, might make jaw-dropping traumatizing smut, idk.

Endermen are naturally curious, and this one is especially intrigued by you—your laugh, your touch, the way your eyes soften when you’re happy. He doesn’t quite get it yet, but he wants to. Every sound, expression, or gesture you make fascinates him.

He becomes obsessed with your sounds—gasps, giggles, sighs. Every little noise you make teaches him something new. He starts experimenting: holding your hand longer, brushing your hair from your face, standing close to feel your body heat. Every pleased sigh or happy noise is a win in his book.

At first, his fingers were awkward—long and spindly, not used to soft skin. But he’s a quick learner. He watches how you react when he drags those inky-black fingertips along the inside of your thighs. The way your breath hitches when he strokes just under your navel. He files it away like a scientist cataloging data—except it’s deeply personal, primal even.

The first time he made you moan—really moan—it stunned him. He paused mid-movement, pupils glowing brighter as he stared at your lips, then your eyes. Then he did it again. And again. He started to chase those sounds like treasure, each new pitch and gasp making his tendrils twitch in response.

He studies the arch of your back when his long wet tongue flicks between your legs. The way your thighs tremble, the way your hands reach for his shoulders, trying to pull him closer or push him deeper. He learns how your body tightens just before release—and that knowledge drives him wild.

Endermen radiate a strange chill, but when aroused, their core temperature spikes. You can feel it in the way his body hums against yours, how the room feels charged with energy. He’ll lift you effortlessly, pressing you against walls, tables, or pinning you to the bed, entirely focused on what makes you writhe.

He doesn’t stop when you cum. No, that’s when it gets really good for him. He leans in close, head brushing your neck, tendrils writhing inside you, around you, coaxing orgasm after orgasm from your spent body. He whispers your own moans back into your ear like a language he’s learning by heart.

One tendril wraps around your neck like a loose choker, another teases your clit in time with your pulse, and inside—he stretches you wide, too much, just enough to make your breath catch. He wants you to be ruined by him. No one else. Ever.

He didn’t mean to intrude. Not the first time. He was just… curious. You were always so warm, your voice soft, your body fascinating. He never meant to appear in your room at night. But then you moaned.

His eyes locked on you from the shadows as your fingers slid between your thighs. Your head tilted back. You sighed his name—soft and breathy—and he froze. Time stopped. He didn’t understand what you were doing. But it made his core burn. Something primal and wrong and so right curled inside him.

After that, he watched every time. Hidden in the dark corners of your room, in the rafters, behind the portal frame—you never noticed. Or maybe you wanted him to watch. He became obsessed. Not with sex—but your pleasure. The way your hips rocked, the shape of your parted lips, the heat that built in your body until you shattered around your own fingers.

The next time you were near him, he mimicked the way you touched yourself. His hand moved slowly, fingers curling in the same rhythm you used. He tilted his head, confused and fascinated, watching your face as he repeated the motion—not on himself, but on you. You gasped. Eyes wide. He froze, then did it again, watching your body jolt. He had learned.

You were on your bed again, fingers buried deep, panting his name. And then—you felt something else.Long, shadowy tendrils curled around your ankles, thighs, waist—restraining, but not cruel. A cool, slick pressure replaced your fingers. You opened your eyes.

He was standing at the foot of your bed. Silent. Glowing eyes boring into yours, wide and starving. The tendril thrust inside slowly—mocking your own rhythm from before. He had studied you. And now he was testing what he’d learned.

He knows what noises mean you’re close. He knows the twitch in your thighs, the breath you hold, the way your hips lift—he’s memorized your pleasure. So when he wraps two tendrils around your wrists, holds your legs apart, and thrusts a third into you with expert rhythm—he does it with complete, focused precision.

His face is inches from yours, his eyes glowing bright, fixated on every moan, every breath, every reaction. His body is still—only his tendrils move. You’re the experiment. The obsession. The lesson.

He doesn’t stop when you cum. He wants to see it again. And again. And again.

“Ah…” he mimics you. Not perfect—but close enough to make your skin crawl with lust. His voice is distorted, otherworldly, but it’s trying to sound like you. His tendrils spread you wide, teasing, thrusting, overstimulating until you sob for mercy. He leans in close, tongue sliding over your cheek, breath hot and damp.

And then, in your own voice, he whispers: “Again.”

[juliebowie]

Unlocking the Path: How to Become a Data Scientist

Summary: Mastering technical and soft skills is essential for aspiring Data Scientists. Certification courses provide industry recognition and prepare individuals for competitive job markets. Embracing continuous learning and networking maximises success in this dynamic field.

Unlocking the Path: How to Become a Data Scientist

Introduction

Industries crave Data Scientists. In today's data-centric universe, Data Science reigns supreme. Ready to explore the path to becoming a Data Scientist? Let's dive in. Ever wondered how to become a Data Scientist? 

Look no further. Certification courses in Data Science pave the way. But first, let's understand the demand. Businesses hunger for data-driven insights, and Data Scientists satisfy this craving. 

They decode complex data puzzles and unearth valuable insights. This introduction sets the stage for our journey. Buckle up; we're about to unravel the secrets of Data Science."

What Is A Data Scientist?

Data Scientists build insights, transforming raw data into actionable intelligence. They possess a unique blend of analytical prowess, technological proficiency, and domain knowledge.

Defining The Role Of A Data Scientist

At its core, a Data Scientist is a problem solver, leveraging data-driven approaches to tackle complex challenges. They extract, analyse, and interpret vast datasets to extract meaningful patterns and trends. With their keen analytical skills, they uncover hidden insights that drive informed decision-making and strategic planning.

Key Responsibilities And Tasks Performed By Data Scientists

Data Scientists are tasked with many responsibilities, including data collection, preprocessing, and analysis. They develop predictive models and algorithms to forecast future trends and behaviours. Moreover, they collaborate closely with stakeholders to communicate findings effectively, translating technical jargon into actionable insights that drive business growth.

Differentiating Data Science From Related Fields Like Data Analysis And Machine Learning Engineering

While Data Science, Data Analysis, and Machine Learning engineering share commonalities, they serve distinct purposes. Data Science encompasses a broader spectrum, integrating statistical analysis, Machine Learning, and domain expertise to extract insights from data. 

In contrast, Data Analysis focuses primarily on descriptive analytics, summarising historical data to derive actionable insights. On the other hand, Machine Learning engineering emphasises developing and deploying Machine Learning models to automate decision-making processes.

Data Scientists serve as the linchpins of data-driven innovation, bridging the gap between raw data and strategic insights.

Scope Of Data Science

In today's digital era, Data Science permeates diverse industries, reshaping traditional paradigms and fostering innovation. Let's delve into the myriad sectors where Data Science is making profound impacts.

Data Science In Industries

Industries across the spectrum, from healthcare to finance, are harnessing the power of Data Science to drive decision-making and optimise processes. Predictive analytics and Machine Learning algorithms revolutionise patient care, enabling early disease detection and personalised treatment plans.

Transforming Finance With Data Science

Data Science is indispensable for risk management, fraud detection, and algorithmic trading in the financial realm. Advanced analytics tools sift through vast datasets to identify patterns and trends, empowering financial institutions to make real-time informed decisions.

Data-Driven Marketing Strategies

In marketing, Data Science fuels targeted advertising campaigns and customer segmentation strategies. By analysing consumer behaviour and preferences, businesses can tailor their marketing efforts for maximum impact and ROI.

Future Prospects And Emerging Trends

Looking ahead, the future of Data Science is brimming with possibilities. With advancements in artificial intelligence, Machine Learning, and big data technologies, the scope of Data Science will continue to expand, unlocking new opportunities and challenges across industries.

Skills and Qualifications Required

In the rapidly evolving field of Data Science, possessing a blend of technical expertise and soft skills is crucial for success. Here's a breakdown of the essential skills and qualifications required to thrive as a Data Scientist:

Technical Skills

Mastering critical programming languages such as Python, R, and SQL lays the foundation for effective data manipulation and analysis. Python's versatility and extensive libraries make it a preferred choice for tasks ranging from data cleaning to Machine Learning model implementation. 

With its robust statistical capabilities, R is indispensable for in-depth Data Analysis and visualisation. SQL proficiency is essential for querying databases and extracting valuable insights efficiently.

Data visualisation skills are indispensable for communicating complex findings to stakeholders effectively. Data Scientists can use tools like Matplotlib, Seaborn, or Tableau to create visually compelling representations of data, aiding comprehension and decision-making.

Machine learning expertise is increasingly in demand as organisations seek to harness the power of predictive analytics. Understanding various Machine Learning algorithms, their applications, and the ability to implement them using libraries like Scikit-learn or TensorFlow is essential for building accurate and scalable predictive models.

Soft Skills

Critical thinking skills enable Data Scientists to approach problems analytically, identify patterns, and formulate innovative solutions. They can uncover hidden insights and make informed decisions by questioning assumptions and evaluating evidence.

Practical problem-solving skills are fundamental to navigating the complexities of real-world data challenges. Data Scientists must be adept at breaking down complex problems into manageable components, devising systematic approaches, and iterating solutions based on feedback.

Strong communication skills are essential for conveying technical findings to diverse audiences, including non-technical stakeholders. Data Scientists must articulate complex concepts clearly, tailor presentations to the audience's level of understanding, and translate technical jargon into actionable insights.

The Importance Of Domain Knowledge And Continuous Learning

In addition to technical and soft skills, domain knowledge is crucial to Data Science success. Understanding the context and nuances of the industry or domain in which one operates allows Data Scientists to ask relevant questions, interpret results accurately, and derive meaningful insights.

Continuous learning is imperative in a rapidly evolving field like Data Science. Staying abreast of the latest tools, techniques, and methodologies through courses, workshops, and self-study ensures that Data Scientists remain competitive and adaptable to technological advancements and industry trends.

Certification Courses in Data Science

Embarking on a journey towards becoming a proficient Data Scientist often begins with acquiring relevant certifications. These certifications serve as milestones, validating one's expertise and readiness for the dynamic field of Data Science. Explore renowned programs, each offering unique pathways to mastery and career advancement.

Data Scientist Certification Course By DataCamp

This certification program from DataCamp equips you with the skills to collect, analyse, and interpret large datasets using Machine Learning and AI techniques. The course emphasises effective communication of analytical results to business stakeholders.

Key Features

Industry Recognition

Enhanced Professional Credibility

Expanded Career Opportunities

Stay Ahead of Industry Trends

Approved and Recognised by Industry Experts

Job Guarantee Program By Pickl.AI

Pickl.AI's Job Guarantee Program in Data Science offers a comprehensive curriculum covering ten modules and 246 lessons. With an emphasis on practical learning, industry-relevant projects, and one-on-one expert mentorship, this program ensures job readiness and placement assistance.

Key Features

Online Bootcamp Format

Access to Cutting-edge Data Science Tools

Comprehensive Curriculum covering ten modules

Job Guarantee upon completion

Placement Assistance and Career Growth Opportunities

Data Science Bootcamp With AI Program By UpGrad

UpGrad's Data Science Bootcamp with AI program prepares you to become a skilled and job-ready Data Scientist. With revamped content that integrates AI concepts, this program offers a comprehensive curriculum and practical hands-on experience through capstone projects.

Key Features

Job-ready portfolio of 17 capstone projects

Complementary AI Engineer Bootcamp

Mastery of MS Excel and Programming Concepts

Extensive Live Instructor-Led Sessions

Placement Support and Career Planning

Each certification course offers unique benefits and features tailored to different learning preferences and career goals in Data Science. 

Whether you're looking to enhance your skills, expand your career opportunities, or secure a job in the industry, these programs provide the necessary training and support to succeed in the dynamic field of Data Science.

Challenges And Opportunities In Data Science Career

Embarking on a career in Data Science presents both challenges and opportunities. Aspiring Data Scientists must navigate hurdles like skill development and market demand in a fiercely competitive job market. Yet, within this landscape lie diverse career paths, from Data Analysis to Machine Learning, each offering avenues for growth and success.

Navigating the Job Market

Data Science is highly competitive, with many aspiring professionals vying for limited positions. Securing a job in Data Science requires more than just technical skills; employers often seek candidates with practical experience and a demonstrated ability to solve real-world problems. 

Additionally, the rapid pace of technological advancement means that staying relevant requires continuous skill development and adaptation to new tools and methodologies.

Seizing Career Opportunities

Despite the challenges, the Data Science field offers many career opportunities across various industries. From analysing consumer behaviour in marketing to optimising healthcare systems through predictive analytics, Data Science applications are virtually limitless. 

Roles in Data Analysis, Machine Learning, data engineering, and beyond allow professionals to specialise and carve out fulfilling careers tailored to their interests and strengths.

Maximising Success in Data Science

To thrive in a Data Science career, aspiring professionals must proactively overcome challenges and seize opportunities. This entails honing technical skills and cultivating soft skills such as critical thinking, problem-solving, and effective communication. 

Networking with industry professionals, participating in Data Science communities, and pursuing continuous learning through online courses and workshops are essential strategies for staying ahead.

Frequently Asked Questions

How To Become A Data Scientist?

Becoming a Data Scientist involves mastering technical skills like Python and SQL alongside soft skills such as critical thinking and communication. Enrolling in reputable Data Science certification courses can provide structured learning and industry recognition.

What Are the Key Benefits of Data Science Certification Courses?

Data Science certification courses offer industry recognition, enhanced professional credibility, and expanded career opportunities. They provide the essential skills and knowledge required to excel in the competitive field of Data Science.

What Challenges Await Aspiring Data Scientists?

Due to market competitiveness and evolving technological landscapes, aspiring Data Scientists may face job security challenges. However, continuous skill development, practical experience, and networking can help overcome these hurdles.

Conclusion

In conclusion, the path to becoming a Data Scientist is paved with rigorous learning and continuous skill development. Data Science certification courses offer structured training and industry recognition, preparing individuals for diverse career opportunities in this dynamic field.