88.2K
COMicrosoft Data Science certification.
#data #datascience
@corporate.wala.youtuber
#Data Science Certification
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DAFREE Certified Courses Links:
1️⃣Get started with Microsoft data analytics - Microsoft
https://learn.microsoft.com/en-us/training/paths/data-analytics-microsoft/
2️⃣ Python Course for Beginners With Certification - Scaler
https://www.scaler.com/topics/course/python-for-beginners/
3️⃣ Elements of AI - Google
https://www.elementsofai.com/
4️⃣ ML/DL Courses - Kaggle
www.kaggle.com/learn
5️⃣ Huggingface LLM Course
https://huggingface.co/learn/llm-course/chapter1/1
6️⃣Generative AI Explained
https://resources.nvidia.com/en-eu-ai-buying-campaign-fy25q1/generative-ai-explained
7️⃣AI Agents Course
https://huggingface.co/learn/agents-course/en/unit0/introduction
@microsoft @google @nvidia @scaler_official
🚨 The Insane Benefits of becoming a Data Science Brain Instagram Subscriber
💠500+ Data Science Books
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Subscribe now by clicking subscribe button in bio ✅
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#data #datascience #dataanalytics #dataanalysis #dataanalyst #datascientist #datacleaning #statistics #python #sql #dataengineering #engineering #pandas #datavisualization #machinelearning #deeplearning #datasciencejobs #datascienceinternship #datascienceroadmap #learndatascience #learndataanalytics #datascienceinterview #datasciencebooks
@datasciencebrain
1.1M
THHere’s a roadmap to help you go from a software engineer to a data scientist 👩💻 👇
If you’re tired of writing vanilla apps and want to build ML systems instead, this one’s for you.
Step 1 – Learn Python and SQL (not Java, C++, or JavaScript).
→ Focus on pandas, numpy, scikit-learn, matplotlib
→ For SQL: use LeetCode or StrataScratch to practice real-world queries
→ Don’t just write code—learn to think in data
Step 2 – Build your foundation in statistics + math.
→ Start with Practical Statistics for Data Scientists
→ Learn: probability, hypothesis testing, confidence intervals, distributions
→ Brush up on linear algebra (vectors, dot products) and calculus (gradients, chain rule)
Step 3 – Learn ML the right way.
→ Do Andrew Ng’s ML course (Deeplearning.ai)
→ Master the full pipeline: cleaning → feature engineering → modeling → evaluation
→ Read Elements of Statistical Learning or Sutton & Barto if you want to go deeper
Step 4 – Build 2–3 real, messy projects.
→ Don’t follow toy tutorials
→ Use APIs or scrape data, build full pipelines, and deploy using Streamlit or Gradio
→ Upload everything to GitHub with a clear README
Step 5 – Become a storyteller with data.
→ Read Storytelling with Data by Cole Knaflic
→ Learn to explain your findings to non-technical teams
→ Practice communicating precision/recall/F1 in simple language
Step 6 – Stay current. Never stop learning.
→ Follow PapersWithCode (it's now sun-setted, use huggingface.co/papers/trending, ArXiv Sanity, and follow ML practitioners on LinkedIn
→ Join communities, follow researchers, and keep shipping new experiments
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Save this for later.
Tag a friend who’s trying to make the switch.
[software engineer to data scientist, ML career roadmap, python for data science, SQL for ML, statistics for ML, data science career guide, ML project ideas, data storytelling, becoming a data scientist, ML learning path 2025]
@the.datascience.gal
336.6K
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
10.4K
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
115.6K
VEIf 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.
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#datascience #data #interview
@vee_daily19
383.8K
JAIf you’re starting your Data Analyst journey or want to grow in your role, certifications can help you stand out.
Here are 5 top certifications to consider:
1. Microsoft Certified: Power BI Data Analyst Associate
- Master Power BI for creating impactful visuals.
Link : https://learn.microsoft.com/en-us/credentials/certifications/data-analyst-associate/?practice-assessment-type=certification
2. Google Data Analytics Certification
Learn the basics like SQL, Excel, and Tableau.
Link : https://grow.google/intl/en_in/data-analytics-course/
3. Meta Data Analyst Professional Certificate
Hands-on with SQL, Python, and visualization.
Link : https://www.coursera.org/professional-certificates/meta-data-analyst
4. IBM Data Analyst Professional Certificate
Develop skills in Excel, Python, and SQL.
Link : https://www.coursera.org/professional-certificates/ibm-data-analyst
5. Tableau Certified Data Analyst
Become a pro in building dashboards with Tableau.
Link : https://www.tableau.com/learn/certification/certified-data-analyst
Certifications like these are a great way to validate your skills, build confidence, and stand out to recruiters.
Which one are you planning to pursue? Let me know in the comments!
Follow @jayenthakker
Dedicated to helping aspiring data analysts thrive in their careers.
➕ Follow @metricminds.in for more tips, insights, and support on your data journey!
#DataAnalytics #DataAnalysts #Tableau #freeresources #onlinecourses
@jayenthakker
39.1K
WO📍How to prepare for Data Scientist role in 2026 🚀
CORE SKILLS YOU MUST MASTER: Programming You must be fluent in:
● Python
● NumPy
● Pandas
● Scikit-learn
Writing clean, readable, bug free code
Data transformations without IDE help
Expect:
● Data cleaning
● Feature extraction
● Aggregations
● Writing logic heavy code
SQL
Almost every Data Science role tests SQL. You should be comfortable with:
● Joins - inner, left, self
● Window functions
● Grouping & aggregations
● Subqueries
● Handling NULLs
Statistics & Probability:
● Probability distributions
● Hypothesis testing
● Confidence intervals
● A/B testing
● Correlation vs causation
● Sampling bias
Machine Learning Fundamentals. You must know:
● Supervised vs Unsupervised learning
● Regression & Classification
● Bias Variance tradeoff
● Overfitting / Underfitting
Evaluation metrics:
● Accuracy
● Precision / Recall
● F1-score
● ROC-AUC
● RMSE
FEATURE ENGINEERING & DATA UNDERSTANDING:
● This is where strong candidates stand out.
● Handling missing data
● Encoding categorical variables
● Feature scaling
● Outlier treatment
CORE SKILLS YOU MUST MASTER: Programming You must be fluent in:
● Python
● NumPy
● Pandas
● Scikit-learn
Writing clean, readable, bug free code
Data transformations without IDE help
Expect:
● Data cleaning
● Feature extraction
● Aggregations
● Writing logic heavy code
SQL
Almost every Data Science role tests SQL. You should be comfortable with:
● Joins - inner, left, self
● Window functions
● Grouping & aggregations
● Subqueries
● Handling NULLs
Statistics & Probability:
● Probability distributions
● Hypothesis testing
● Confidence intervals
● A/B testing
● Correlation vs causation
● Sampling bias
Machine Learning Fundamentals. You must know:
● Supervised vs Unsupervised learning
● Regression & Classification
● Bias Variance tradeoff
● Overfitting / Underfitting
Evaluation metrics:
● Accuracy
● Precision / Recall
● F1-score
● ROC-AUC
● RMSE
+++ for more look at the comment
#datascientist #aiengineer #softwareengineer #datascience #dataengineer
@woman.engineer
293.0K
QRComment “Link” to get link of these courses
Unlock Your Data Analytics Potential with Free Courses! 🌟
Are you passionate about data analytics and eager to advance your career without spending a dime? We’ve curated the top 3 free data analyst courses that not only provide valuable knowledge but also come with certifications to boost your resume:
✅1. Power PA Data Analyst Professional Certificate by Microsoft: This course offers comprehensive training from industry experts at Microsoft. Learn how to analyze data, create reports, and make data-driven decisions with advanced tools and techniques.
✅2. Data Analyst Professional Certificate by Meta: Dive into data analytics with Meta’s specialised course. Gain insights into the latest data analysis methodologies and tools used by professionals at Meta, and develop skills that are in high demand in the tech industry.
✅3. Data Analyst Capstone Project by IBM: This project-based course from IBM allows you to work on real-world data analysis projects. Get hands-on experience with IBM’s advanced analytics tools and showcase your skills with a recognized certification.
To get these free courses link,
1.Share this video
2.Follow @qriocity.in
3.Comment “Link” in comment box
Turn on 🔔 notification on this profile & so that you don’t miss our posts.
#learnforfree #dataanalytics #careerboost
@qriocity.in
431.9K
CHThe best projects serve a real use case
Comment “data” for all the links and project descriptions
#tech #data #datascience #ml #explore
@chrisoh.zip
190.5K
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
344.7K
THFree Microsoft Data Analysis Certification: Unlock High-Paying Jobs 🚀
To access the certification course by Microsoft, Like this reel and comment “Microsoft“ and I’ll share all the info 💯
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We discuss a free data analysis certification course by Microsoft that can help you land a high-paying job as a fresher, with a salary range of 10 to 16 lakh rupees per annum. The course is designed and taught by Microsoft experts, and upon completion, you’ll receive a certification that can open doors to opportunities at multiple MNCs, including Microsoft itself. This is an absolutely free course, so don’t miss out on this chance to kickstart your career in data analysis.
-
#DataAnalysis #MicrosoftCertification #HighPayingJob #FreeOnlineCourse #CareerGrowth #it #placement #interview
@thegauravghai
✨ Руководство по #Data Science Certification
Instagram содержит 16K публикаций под #Data Science Certification, создавая одну из самых ярких визуальных экосистем платформы.
Огромная коллекция #Data Science Certification в Instagram представляет самые привлекательные видео сегодня. Контент от @the.datascience.gal, @chrisoh.zip and @jayenthakker и других креативных производителей достиг 16K публикаций по всему миру.
Что в тренде в #Data Science Certification? Самые просматриваемые видео Reels и вирусный контент представлены выше.
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