#Data Science Bootcamp

This 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

Here is a full roadmap on how to get started with Data Science. Comment “DATA” for the full roadmap pdf. #datascience #machinelearning #coding #ai #university

Data Science 4 All is a free training program that makes data science shockingly uncomplicated

Comment “skills” to get more details! Join Coding Ninjas Data Analytics Job Bootcamp to master the skills, tools, crack interviews, and land your dream job✨ #codingninjas #dataanalytics

Learn data science fundamentals for free! STEM background recommened but not required for most courses. - free data science courses? - best way to learn data science online? - how do I learn data science? #ai #datascience #learning #sabrinaramonov

Comment ‘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

Accredited and vendor certifications you should look out for when applying for a data science bootcamp. @zaiotechnology #tech #bootcamp #southafrica #TechCareers #datascience

The best projects serve a real use case Comment “data” for all the links and project descriptions #tech #data #datascience #ml #explore

Comment PROJECT to access my step-by-step Python tutorial that anyone can follow to build your very first geospatial dashboard web app! 🌍📊 A good number of portfolio projects is 3–5, and the types of projects you choose should reflect the kind of data role you’re going after. A data analyst portfolio should look very different from a machine learning engineer one. Even within data science, a product/decision data scientist portfolio should focus on A/B testing and metrics storytelling—while an algorithm data scientist portfolio might highlight modeling and experimentation. ✨ Especially if you’re building your very first project, prioritize: 🌱 Real-world messiness (not polished Kaggle sets) 🌱 Business context and decision-making 🌱 Clear documentation (what you did and why) 🌱Visuals to help your work stand out No one’s asking for perfection—they want to see how you think. #datascienceportfolio #dataanalyst #learnpython #codingjourney #techcareers

Comment "DATA" for the links. You Will Never Struggle With Data Science Again 📌 Learn the most important foundations with these beginner-friendly resources: 1️⃣ Learn Python for Data Science – FreeCodeCamp’s full beginner course 2️⃣ Essence of Linear Algebra – 3Blue1Brown’s visual, intuitive playlist 3️⃣ Statistics – A Full Lecture (2025) – step-by-step breakdown of core stats concepts Stop feeling overwhelmed by Python, statistics, or linear algebra. These tutorials simplify the fundamentals of Data Science with clear explanations, visuals, and real-world examples. Whether you’re preparing for a career in Data Science, getting into machine learning, or just curious about data analysis, this is the fastest way to finally understand how it all fits together. Save this post, share it, and turn confusion into clarity with Python, Stats, and Linear Algebra for Data Science 📊

If you want to crack Data Science jobs in the next 30 days, here’s the three step process which you will follow which literally no one talks about. . . . #datascience #data #interview

Data Scientist Roadmap . . . . . #reels #viral #trendingreels #newcollection #viralvideos #reelsvideo #reelsinstagram #shorts #trending #viralreels