#Computer Science Vs Data Science

What 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

Is it worth it to study computer science?

Computer Science was the craze in 2021 and all of a sudden, anyone with a 5-month bootcamp and their grandma could get a coding job. But the hype is gone. It’s not that computer science has become one of the worst degrees, it was just unsustainably easy to get a job and has now gone down to a normal level like any other degree. The truth is, Computer Science is still arguably one of the best degrees you can study. No other degree is going to make you as prepared, well-rounded for learninng or well adapted in the real-world. But it’s not worth if you’re any one of these 3 things, if you are, don’t even think about it 1. You think it’s going to be fun and easy because of the salary Yes, the software engineer salary and worklife can be great but it comes at a codt. It can be one of the hardest jobs, constant mental taxation, long overtimes, being on-call when things go wrong. If you’re not willing to do the hard things, don’t expect the nice perks. 2. Not willing to put in work outside of university Learning theory in university will never be enough unless you’re willing to apply the knowledge. Cruising through a CS degree is no longer an option, if you can’t put in the extra time, don’t bother. 3. Not willing to learn Technology is so vast and quick in evolving. You’d never be able to know everything at once. So, at every new job and every new class, you’re going to have to learn something new. You’ll be left in the dust if you can’t learn. Follow me @isaac.arli for more

This is your professors favorite professor! His name is Abdul Bari and he has a bunch of playlists on YouTube of his lectures teaching Computer Science and coding! The way he explains things is so clear and easy to understand! 💌SEND this to yourself or save it! ✅FOLLOW for more Computer Science tips! #computerscience #compsci #programming #coding #computersciencemajor #computersciencestudent #softwareengineering #datastructuresandalgorithms #dsa

📍Learning to code and becoming a data scientist without a background in computer science or mathematics is absolutely possible, but it will require dedication, time, and a structured approach. ✨👌🏻 🖐🏻Here’s a step-by-step guide to help you get started: 1. Start with the Basics: - Begin by learning the fundamentals of programming. Choose a beginner-friendly programming language like Python, which is widely used in data science. - Online platforms like Codecademy, Coursera, and Khan Academy offer interactive courses for beginners. 2. Learn Mathematics and Statistics: - While you don’t need to be a mathematician, a solid understanding of key concepts like algebra, calculus, and statistics is crucial for data science. - Platforms like Khan Academy and MIT OpenCourseWare provide free resources for learning math. 3. Online Courses and Tutorials: - Enroll in online data science courses on platforms like Coursera, edX, Udacity, and DataCamp. Look for beginner-level courses that cover data analysis, visualization, and machine learning. 4. Structured Learning Paths: - Follow structured learning paths offered by online platforms. These paths guide you through various topics in a logical sequence. 5. Practice with Real Data: - Work on hands-on projects using real-world data. Websites like Kaggle offer datasets and competitions for practicing data analysis and machine learning. 6. Coding Exercises: - Practice coding regularly to build your skills. Sites like LeetCode and HackerRank offer coding challenges that can help improve your programming proficiency. 7. Learn Data Manipulation and Analysis Libraries: - Familiarize yourself with Python libraries like NumPy, pandas, and Matplotlib for data manipulation, analysis, and visualization. For more look at the comment ⤵️ . . . #datascience #computerscience #datascientist #dataanalytics #dataanalyticstraining #python #softwaredeveloper #dataanalysis #bigdata #generativeai #codingbootcamp #businesswoman #veribilimi #codemotivation

Computer Science😭💔 #EmergentPartner - - #university #college #engineering #collegeadvice

Confused between becoming a Data Scientist or an AI Engineer? Both roles are powerful—but require different skills, tools, and thinking. Comment “Roles” and I’ll send you a detailed roadmap for both 🚀 Got questions or feeling stuck? Drop your doubts in the comments—I’ll personally help you get clarity and move forward on your journey. #datascientist #datascience #ai #aiengineer #careergrowth

The phrase “Computer Science is not science, and it’s not about computers” highlights that the field focuses more on problem-solving, algorithms, and theory than the physical hardware of computers. It’s about how information is processed and manipulated, not just building machines. At its heart, computer science is about understanding abstract concepts and logical frameworks to solve complex problems, blending mathematics, engineering, and logic. What do you think—should we rethink how we teach computer science based on this? #TechPhilosophy #ComputerScienceTheory #ProblemSolving #AbstractThinking #BeyondComputers

Where are all our data scientists at! 👀👇🏻 #young4stem #datascience #job #reel #stem #computerscience

3️⃣ things could be limiting your ability to succeed in your Computer Science classes: 1️⃣ 🧳 Resources: There are loads of resources online (free and freemium) to help you deepen your understanding of the topics you learn in class. If you don’t know which resources to use for your class, follow this page. I share resources for various areas in Computer Science like ✨ compscilib.com for Discrete Math ✨ and ✨ visualgo.net for Data Structures ✨✅ 2️⃣ ⏱️ Time: You can have a deep understanding of the topics you learn but still mot be able to complete programming projects and assignments on time. That’s okay. Don’t stress. Instead, try AI code completion tools like ✨ Github Copilot ✨ and ✨Blackbox.io✨. Only use these if you understand the topic well enough and can comfortably debug if needed. ✅ 3️⃣ 👭 Community: Being around other techies who support you and work with you is crucial for growth in Computer Science. If you don’t have such buddies around you join a community of individuals like you. If you’re a woman in Computer Science, you can join our “Computer Science Girlies” server. Simply, comment “community” and i’ll dm the server link to you 💗💗💗 Remember, good things take time and effort. In just a few years, you’ll look back to this moment and will be glad you persevered. Keep going. 🤍

Data Science is art paired with logic 😊. In my soft girl in tech era 💕. Calm lights, chaotic datasets #datascience #stem #womeninstem #study #computerscience #coding #programming #tech #explore #ai #python #dev #tools #study #datascientist #data #design #software #codinglife #programmer #datascience #build #learning #growth #technology #information

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