#Data scientist

[my-midlife-crisis]

[thedatarogue]

All D&D 5E Spells, in one place

Hello, D&D players!

Are you tired of having to go through multiple books, pdf files or third-party websites just to find the one spell you're looking for? Don't want to pay hundreds of dollars to be able to access all the spells in DND Beyond?

Well, I've got just the thing for you.

In this Github repository, I've uploaded a dataset with information on all of the 5E spells (inside the datasets folder). The README file has all the information you need to use it, along with some other stuff.

If you have any problems using these assets, feel free to contact me either through here or Github. I'm thinking of adding pictures to the guide on Github, but it might be a while before I do that.

If the link isn't working, just remove the https://href.li/? part and you should be good.

Happy travels, adventurers.

[herpersonafire]

Hey! and welcome back!

As Uni is about to begin in a few days....I upgraded to a third monitor! Also!! I job a Data entry job! Big things moving forward :)

Let me introduce myself;

I'm Mick, (she/her) and I currently study Data Analytics. I'll be 26 in July and I love to read and play video games in my free time. I also like to watch football (LIVERPOOL xx)

Im currently taking the time to learn Excel and Python. However, I know for school I'll be learning Python, SQL and maybe some other things.

FOLLOW me along on this journey and if you have any questions please ask!

[datascienceunicorn]

The Data Scientist Handbook 2024

HT @dataelixir

[ameera-ameera]

[ID: Crayon style drawing of a light brown mouse wearing a button down shirt, a black blazer, and glasses. She holds a tablet with various types of charts in her paw. /end ID]

I was listening to a pre-recorded meeting at work and wanted to keep my hands busy, so I created this game! Dress a mouse girl data scientist in formal button downs or relaxed grafic t-shirts, and finish the look with one of 19 different charts and data visualizations for her tablet. There’s bar charts, line charts, pie charts, scatter plots, table data, and much more!

Mouse Girl Data Scientist Dress Up

[kochivamarketing]

Why Study Data Science?

Data science is an exciting and rewarding field that offers numerous compelling reasons to pursue it as a career path. Here are five key reasons why you should consider studying data science:

High Demand and Lucrative Salaries: With companies across industries recognizing the value of data-driven decision-making, the demand for skilled data scientists is skyrocketing, leading to abundant job opportunities and attractive compensation packages.

Work on Cutting-Edge Technologies: Data science lies at the intersection of emerging technologies like AI, machine learning, big data, and cloud computing, allowing you to work with cutting-edge tools and drive innovation.

Solve Complex Problems and Make an Impact: As a data scientist, you'll tackle real-world challenges across diverse domains, using data to develop solutions that can improve lives, drive social change, and shape the future.

Develop Highly Transferable Skills: Data science requires a unique combination of technical and analytical skills, such as programming, statistics, machine learning, and data visualization, which are highly transferable across industries and job roles.

Join a Vibrant Community: The data science community is diverse, dynamic, and collaborative, offering opportunities for continuous learning, networking, and professional growth through conferences, hackathons, and engagement with like-minded individuals.

With its high demand, potential for innovation, and the ability to make a meaningful impact, data science offers a rewarding and future-proof career path for those driven by intellectual curiosity and a passion for solving complex problems.

If you're in Delhi and looking to kickstart your data science journey, there are several excellent courses to consider, check out - Top 6 Best Data Science Courses in Delhi – The Complete Information

[d0nutzgg]

Tonight I am hunting down venomous and nonvenomous snake pictures that are under the creative commons of specific breeds in order to create one of the most advanced, in depth datasets of different venomous and nonvenomous snakes as well as a test set that will include snakes from both sides of all species. I love snakes a lot and really, all reptiles. It is definitely tedious work, as I have to make sure each picture is cleared before I can use it (ethically), but I am making a lot of progress! I have species such as the King Cobra, Inland Taipan, and Eyelash Pit Viper among just a few! Wikimedia Commons has been a huge help!

I'm super excited.

Hope your nights are going good. I am still not feeling good but jamming + virtual snake hunting is keeping me busy!

[adamsvanrhijn]

reblogs appreciated :-)

[subrage]

Truth speaking on the corporate obsession with AI

Hilarious. Something tells me this person's on the hellsite(affectionate)

[tech-insides]

What are the skills needed for a data scientist job?

It’s one of those careers that’s been getting a lot of buzz lately, and for good reason. But what exactly do you need to become a data scientist? Let’s break it down.

Technical Skills

First off, let's talk about the technical skills. These are the nuts and bolts of what you'll be doing every day.

Programming Skills: At the top of the list is programming. You’ll need to be proficient in languages like Python and R. These are the go-to tools for data manipulation, analysis, and visualization. If you’re comfortable writing scripts and solving problems with code, you’re on the right track.

Statistical Knowledge: Next up, you’ve got to have a solid grasp of statistics. This isn’t just about knowing the theory; it’s about applying statistical techniques to real-world data. You’ll need to understand concepts like regression, hypothesis testing, and probability.

Machine Learning: Machine learning is another biggie. You should know how to build and deploy machine learning models. This includes everything from simple linear regressions to complex neural networks. Familiarity with libraries like scikit-learn, TensorFlow, and PyTorch will be a huge plus.

Data Wrangling: Data isn’t always clean and tidy when you get it. Often, it’s messy and requires a lot of preprocessing. Skills in data wrangling, which means cleaning and organizing data, are essential. Tools like Pandas in Python can help a lot here.

Data Visualization: Being able to visualize data is key. It’s not enough to just analyze data; you need to present it in a way that makes sense to others. Tools like Matplotlib, Seaborn, and Tableau can help you create clear and compelling visuals.

Analytical Skills

Now, let’s talk about the analytical skills. These are just as important as the technical skills, if not more so.

Problem-Solving: At its core, data science is about solving problems. You need to be curious and have a knack for figuring out why something isn’t working and how to fix it. This means thinking critically and logically.

Domain Knowledge: Understanding the industry you’re working in is crucial. Whether it’s healthcare, finance, marketing, or any other field, knowing the specifics of the industry will help you make better decisions and provide more valuable insights.

Communication Skills: You might be working with complex data, but if you can’t explain your findings to others, it’s all for nothing. Being able to communicate clearly and effectively with both technical and non-technical stakeholders is a must.

Soft Skills

Don’t underestimate the importance of soft skills. These might not be as obvious, but they’re just as critical.

Collaboration: Data scientists often work in teams, so being able to collaborate with others is essential. This means being open to feedback, sharing your ideas, and working well with colleagues from different backgrounds.

Time Management: You’ll likely be juggling multiple projects at once, so good time management skills are crucial. Knowing how to prioritize tasks and manage your time effectively can make a big difference.

Adaptability: The field of data science is always evolving. New tools, techniques, and technologies are constantly emerging. Being adaptable and willing to learn new things is key to staying current and relevant in the field.

Conclusion

So, there you have it. Becoming a data scientist requires a mix of technical prowess, analytical thinking, and soft skills. It’s a challenging but incredibly rewarding career path. If you’re passionate about data and love solving problems, it might just be the perfect fit for you.

Good luck to all of you aspiring data scientists out there!

[theverynearfuture]

Not the Droid we were looking for.

[womaneng]

View this post on Instagram

A post shared by Zeynep Küçük Woman Engineer (@woman.engineer)

Hey there! 🚀 Becoming a data analyst is an awesome journey! Here’s a roadmap for you:

1. Start with the Basics 📚:

- Dive into the basics of data analysis and statistics. 📊

- Platforms like Learnbay (Data Analytics Certification Program For Non-Tech Professionals), Edx, and Intellipaat offer fantastic courses. Check them out! 🎓

2. Master Excel 📈:

- Excel is your best friend! Learn to crunch numbers and create killer spreadsheets. 📊🔢

3. Get Hands-on with Tools 🛠️:

- Familiarize yourself with data analysis tools like SQL, Python, and R. Pluralsight has some great courses to level up your skills! 🐍📊

4. Data Visualization 📊:

- Learn to tell a story with your data. Tools like Tableau and Power BI can be game-changers! 📈📉

5. Build a Solid Foundation 🏗️:

- Understand databases, data cleaning, and data wrangling. It’s the backbone of effective analysis! 💪🔍

6. Machine Learning Basics 🤖:

- Get a taste of machine learning concepts. It’s not mandatory but can be a huge plus! 🤓🤖

7. Projects, Projects, Projects! 🚀:

- Apply your skills to real-world projects. It’s the best way to learn and showcase your abilities! 🌐💻

8. Networking is Key 👥:

- Connect with fellow data enthusiasts on LinkedIn, attend meetups, and join relevant communities. Networking opens doors! 🌐👋

9. Certifications 📜:

- Consider getting certified. It adds credibility to your profile. 🎓💼

10. Stay Updated 🔄:

- The data world evolves fast. Keep learning and stay up-to-date with the latest trends and technologies. 📆🚀

. . .

[sumita-sengg]

SQL Server deadlocks are a common phenomenon, particularly in multi-user environments where concurrency is essential. Let's Explore:

https://madesimplemssql.com/deadlocks-in-sql-server/

Please follow on FB: https://www.facebook.com/profile.php?id=100091338502392

[datascienceunicorn]

ML Code Challenges HT @dataelixir

[deeones]

🚀 Revolutionize Your Data Management! 🚀 Discover how Python-based RPA integration with BI tools can automate ETL processes, increasing efficiency, accuracy, and scalability. Learn how businesses like yours are leveraging this technology to drive data-driven decision-making. 💡Learn More: https://lnkd.in/giV6BPNQ The latest scoop, straight to your mailbox : http://surl.li/omuvuv #DataManagement #ETL #RPA #BI #Automation #DigitalTransformation #DataAnalytics #BusinessIntelligence #TechnologyInnovation #DataScience #Innovation #BusinessSolutions #DataProcessing #SoftwareDevelopment #DataVisualization #Analytics

[aeolianblues]

heart-sinking part of work is I'll make some code work and then it's joy! Code works! Only to then realise I am in fact a data scientist ad not a programmer and so my work has only just begun :( The Analysis :///