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ANDATA pronunciation 🗣
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#english #learnenglish #englishtips #vocabulary #englishteacher #inglese #ingles #aprendeingles #imparainglese #englishlesson #anglais #englishexam #easyenglish
@antonios.english
#Data Definition Language Tutorial
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SIThinking about applying to dataannotation.tech?
Here’s what you need to know before you waste time.
I’ve applied twice and still haven’t passed their test. And I’m not the only one—Reddit and YouTube comments are full of people saying the same.
But if you do get in?
The work is real.
You’re annotating text—basically labeling or correcting AI-generated answers.
It’s not hard once you know what to do, but passing the initial test? That’s the tricky part.
Most people say the pay is decent for side income—nothing crazy—but flexible and remote.
Searches for “data annotation” are blowing up right now because it feels like easy money. But you have to pass the exam. No shortcuts. No guarantees.
I’ll share what I’ve learned from the process so far and what I’ve found online about the kind of work they assign.
Let me know if you’ve passed the test or if you want me to keep documenting this journey.
@side.hustlereview
14.3K
ASThis is the EXACT order I would learn Data Science in 2026.
Hi 😊 my name is Dawn. I’ve been a Data Scientist at Meta, Patreon and other startups. And have coached 20+ clients into landing their dream Data jobs in the past year.
1️⃣ Learn SQL
SQL is a must-have skill for every data professional because it’s the primary way you get data OUT of a database.
It’s also a very easy coding language to learn, so I would start there.
Use Interview Master to learn and practice SQL (link in bio):
→ Learn SQL: www.interviewmaster.ai/content/sql
→ Practice SQL: www.interviewmaster.ai/home
2️⃣ Start building Product Sense & Business Sense
Product sense & business sense basically means you know how to use Data to solve real problems.
I would start building this “soft” skill early because (1) it takes time to really learn this, and (2) as you’re learning Stats and Python, you already have context on how these might be used in the real world.
I found the book: Cracking the PM Career to be super helpful before I landed my first Data Science job.
3️⃣ Learn Statistics
How much Stats do you need for Data Science? Just the foundations, but you need to know it really really well.
→ Descriptive statistics
→ Common distributions
→ Probability and Bayes’ Theorem
→ Basic Machine Learning models
→ Experimentation concepts
→ A/B experiment design
Check out Stanford’s Introduction to Statistics, which is free on Coursera.
4️⃣ Learn Python
Python is the #1 skill for Data Scientists in 2025, but I put it 4th on this list because I find that it builds on skills 1-3.
I learned Python on my own using DataCamp’s Python Data Fundamentals (link in bio).
5️⃣ Use AI-assisted coding tools
Many data scientists are already using tools, like Claude Code & Cursor, to 2x their productivity.
And also many companies are evaluating you on your use of AI during interviews.
#datascience #datascientist
@askdatadawn
349.3K
SUComment ‘Projects’ to get 5 Data Scientist Project ideas and a plan 👩🏻💻
♻️ repost to share with friends. Here is how to become a data scientist in 2026 and beyond 📈 the original video was 4 min Andi had to cut it down to 3 because instagram. Should I do a part 3v
what are other skills that you would add to the list and let me know what I should cover in the next video 👩🏻💻
#datascientist #datascience #python #machinelearning #sql #ai
@sundaskhalidd
54.3K
SHWant to present data like a pro?
Here are 3 tricks (plus a bonus) that make your slides clear, confident, and impossible to ignore:
1️⃣ Write headlines, not titles. Headlines tell the story, not just the topic.
2️⃣ Use reference lines. Add benchmarks or targets so your audience instantly understands context and comparison.
3️⃣ Use color with purpose. Highlight what matters most so your audience’s eyes go exactly where you want them to.
✨ Bonus tip: Add annotations. Label the “why” behind the numbers, like “Q4 spike due to holiday promo.” It keeps people focused on the insight, not just the chart.
Great presenters don’t just show data, they explain it visually.
🚨FYI: charts with reference lines can be tricky to create
Comment the word DATA and I’ll send you my Google Sheets template!
#datavisualization #presentationskills #presentationdesign #communicationskills #careeradvice
@showupsmart
4.4K
DAData Science Explained Simply | Beginner to Pro Journey | DataTeach
Want to start a career in Data Science but don’t know where to begin?
This video gives you a clear and simple understanding of the entire journey.
✅ Basics of Data Science in simple language
✅ Difference between Data Science, AI & ML
✅ How companies use data in real life
✅ Skills and tools required to start
✅ Beginner-friendly learning roadmap
Designed for beginners, freshers, and non-IT backgrounds who want to enter the data field.
#datateachai #dataanalytics #machinelearning #artificialintelligence
@datateach.ai
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JEComment “project” for my full video that breaks each of these projects down in detail with examples from my own work.
If you’re using the Titanic, Iris, or COVID-19 dataset for data analytics projects, STOP NOW! These are so boring and over used and scream “newbie”. You can find way more interesting datasets for FREE on public data sites and you can even make your own using ChatGPT or Claude!
Here are the 3 types of projects you need:
↳Exploratory Data Analysis (EDA): Exploring a dataset to uncover insights through descriptive statistics (averages, ranges, distributions) and data visualization, including analyzing relationships between variables
↳Full Stack Data Analytics Project: An end-to-end project that covers the entire data pipeline: wrangling data from a database, cleaning and transforming it. It demonstrates proficiency across multiple tools, not just one.
↳Funnel Analysis: Tracking users or items move from point A to point B, and how many make it through each step in between. This demonstrates a deeper level of business thinking by analyzing the process from beginning to end and providing actionable recommendations to improve it
Save this video for later + send to a data friend!
@jessramosdata
2.1K
MEStatistics is NOT just for statisticians.
It’s the secret weapon of every Data Analyst.
Each dataset hides a story, and distributions help us decode it.
👉 A quick cheat sheet for you (save this!):
1. Normal = classic bell curve
2. Uniform = equal chance
3. Binomial/Bernoulli = success vs failure
4. Poisson = rare events
5. Log Normal = skewed data
6. Gamma/Beta = flexible shapes
7. Geometric = time until first success
⚡ Knowing the right distribution = better insights, smarter decisions.
Ask yourself:
What story is my data’s distribution telling me?
Which of these do you use most?
--
Follow @jayenthakker and @metricminds.in
➕ Dedicated to helping aspiring data analysts thrive in their careers.
--
#dataanalytics #datascience #data #metricminds #datavisualization #analytics #artificialintelligence #python #ml #careers #sql #careerswitch #trendingreels #foryoupage #learning
@metricminds.in
275.6K
GEFrom basics to advanced… now I can query, analyze & solve real-world problems 🚀
This is just the beginning of my Data Analytics journey 📊
👉 Follow @GeekswithRaj for daily learning
👉 Save this for your journey motivation 🔥
[ SQL DataAnalytics LearnSQL DataAnalyst TechSkills CodingJourney CareerGrowth Database SQLPractice InterviewPrep GeeksWithRaj ] #geekswithraj #sql #data #dsa #dataanalytics
@geekswithraj
1.9M
DA🧭 Data Analysis Roadmap (Short Version)
1. SQL → W3Schools Learn basics (SELECT, JOIN, GROUP BY), then practice on sample datasets.
2. Maths → Khan Academy Focus on statistics, probability, and basic algebra relevant to data analysis.
3. Excel → Chandoo (YT) Master formulas, pivot tables, charts, and simple dashboards.
4. Power BI → Avi Singh (YT) Learn Power Query, DAX, and build interactive dashboards.
5. Tableau → Tableau Tim (YT) Create visualizations, use filters, and build dashboards.
6. Python → CS50 (YT) Learn basics + data analysis with Pandas, NumPy, Matplotlib/Seaborn.
7. Data Analysis → Alex The Analyst (YT) Follow end-to-end tutorials, build projects, and prep for interviews.
Special Benefits for Our Instagram Subscribers 🔻
➡️ Free Resume Reviews & ATS-Compatible Resume Template
➡️ Quick Responses and Support
➡️ Exclusive Q&A Sessions
➡️ Data Science Job Postings
➡️ Access to MIT + Stanford Notes
➡️ Full Data Science Masterclass PDFs
⭐️ All this for just Rs.45/month!
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#datascience #machinelearning #python #ai #dataanalytics #artificialintelligence #deeplearning #bigdata #agenticai #aiagents #statistics #dataanalysis #datavisualization #analytics #datascientist #neuralnetworks #100daysofcode #genai #llms #datasciencebootcamp
@datasciencebrain
17.0K
POWhat is Data Science? 🤖📊
It’s literally where human intelligence meets computer science — a field where we actually predict the future using data. 🔮
Companies study graphs, maps, past trends, and millions of data points to understand what might happen next… because yes, history repeats itself.
Election agencies even pay millions for prediction models before the results are out. 🗳️📈
And tech companies? They track your behaviour to recommend products, personalize your apps, and show ads you’re most likely to click. 🎯📱
If you want to enter the world of Data Science, here are the 3 skills you NEED:
1️⃣ Mathematics — statistics & probability
2️⃣ Programming — Python or R for analysis & visualization
3️⃣ Machine Learning Algorithms — including regressions 🤝🤖
Comment “Data Science + your favourite company” and I’ll send you a full beginner-friendly roadmap!
Follow @podus.app for more tech breakdowns, coding insights, and career guides. 🚀✨
#datascience #machinelearning #pythonprogramming #techcontent #aicommunity #programminglife #learnpython #datavisualization #techfacts #techreels #codingreels #aiml #artificialintelligence #bigdata #datatrends #datascientist #analytics #mlalgorithms #statistics #probability #codinglife #techcreator #techguide #computerscience #techlearning #futuretech #programmingtutorial #dataanalysis #reelsinstagram #podus
@podus.app
647.3K
FIEp44- Stop learning everything!!
Are you learning everything in data analytics??
that’sthe biggest mistake and the reason people stay stuck with out getting a job.
Interviews don’t test random topics. They test specific skills. Right tools and project scenario based knowledge.
As an experienced data analyst with over 8 years of experience i have created a detailed pdf from my data analyst journey on which topics needs to be covered. Which needs to be ignored. How to prepare your own project based portfolio. Answer questions with right tools and skill. Below are the details included in pdf.
✔️ What to learn (and what to skip)
✔️ Skills interviewers actually ask
✔️ Role-wise roadmap (Fresher → Job ready)
✔️ Project clarity + interview direction
This is only for serious learners. Hence i made it as a paid one which costs a minimal fee.
Follow and comment EP-44. I’ll send you the link directly.
[data analytics, journey, road map, data analyst, jobs]
#dataanalyst #journey #roadmap #skills #growth
@fitwit_krish
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