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As the resident quantitative data analyst in @thesashlab, I’m always so excited when we meet our recruitment goals and can start data analysis!! Just recently we met our goal for the @patersonpreventionproject 💪 and I can’t wait to get into all the new data. Y’all should’ve seen my reaction in real time when we hit our target sample size while we were giving out surveys in Paterson 😂
As the resident quantitative data analyst in @thesashlab, I’m always so excited when we meet our recruitment goals and can start data analysis!! Just recently we met our goal for the @patersonpreventionproject 💪 and I can’t wait to get into all the new data. Y’all should’ve seen my reaction in real time when we hit our target sample size while we were giving out surveys in Paterson 😂
Philomena as a statistician is so academically fascinating🤣 #comedy #comedian #statistics #Statistician #lol #funnyreels #laughter #laughteristhebestmedicine #britishcomedy #mockery #mockumentary #cunkonearth #philomenacunk #DianeMorgan
Philomena as a statistician is so academically fascinating🤣 #comedy #comedian #statistics #Statistician #lol #funnyreels #laughter #laughteristhebestmedicine #britishcomedy #mockery #mockumentary #cunkonearth #philomenacunk #DianeMorgan
Neural networks are useful statistical models when carefully evaluated. Black-box generative AI used uncritically is a problem. #statistics #datascience #machinelearning #research #statistician
Neural networks are useful statistical models when carefully evaluated. Black-box generative AI used uncritically is a problem. #statistics #datascience #machinelearning #research #statistician
Fundamental knowledge of statistics would go a long way in your Data science career. Here are few courses to learn Statistics: 1. Introduction to statistics offered by Stanford on Coursera 🔸Level: Beginner 🔸Duration: Approx. 14 hours 🔸Fee: Free to audit 🔸What you’ll learn: Exploratory Data Analysis, Descriptive Statistics, Sampling and Randomized Controlled Experiments Sampling, Probability, Sampling Distributions and the Central Limit Theorem, Regression, Common Tests of Significance, Resampling, Multiple Comparisons 2. Data Analysis with R Specialization by Duke University on Coursera 🔸Level: Beginner 🔸Duration: Approx. 5-6 hours 🔸Fee: Free to audit 🔸What you’ll learn: Statistics, Linear Regression, R Programming, Regression Analysis, R studio, Exploratory Data Analysis, Statistical Inference, Statistical Hypothesis Testing 3. Harvard University: Statistics and R on Edx 🔸Level: Intermediate 🔸Duration: 4 weeks (2-4 hours/week) 🔸Fee: Free to audit 🔸What you’ll learn: Random variables, Distributions, Inference: p-values and confidence intervals, Exploratory Data Analysis, Non-parametric statistics 4. Statistics with Python Specialization by University of Michigan on Coursera 🔸Level: Beginner 🔸Duration: 3 months (5 hours/week) 🔸Fee: Free to audit 🔸What you’ll learn: Python Programming, Data Visualization (DataViz), Statistical Model, Statistical inference methods . Become statistically significant in the job market by completing these courses.😉 . Type “Statistics” for the link to these courses 👍 . Remember to Follow @citizendatascientist & @saurabhmoody for more curated Data Science and Analytics content.👏 . . #data #datascience #datascientist #statistics #python #statistic #dataanalytics #dataanalysis #dataanalyst #pythonprogramming #r #rprogramming #programming #statistician #duke #michigan #harvard #datascientistskills #citizendatascientist #alphaaai #superai
Fundamental knowledge of statistics would go a long way in your Data science career. Here are few courses to learn Statistics: 1. Introduction to statistics offered by Stanford on Coursera 🔸Level: Beginner 🔸Duration: Approx. 14 hours 🔸Fee: Free to audit 🔸What you’ll learn: Exploratory Data Analysis, Descriptive Statistics, Sampling and Randomized Controlled Experiments Sampling, Probability, Sampling Distributions and the Central Limit Theorem, Regression, Common Tests of Significance, Resampling, Multiple Comparisons 2. Data Analysis with R Specialization by Duke University on Coursera 🔸Level: Beginner 🔸Duration: Approx. 5-6 hours 🔸Fee: Free to audit 🔸What you’ll learn: Statistics, Linear Regression, R Programming, Regression Analysis, R studio, Exploratory Data Analysis, Statistical Inference, Statistical Hypothesis Testing 3. Harvard University: Statistics and R on Edx 🔸Level: Intermediate 🔸Duration: 4 weeks (2-4 hours/week) 🔸Fee: Free to audit 🔸What you’ll learn: Random variables, Distributions, Inference: p-values and confidence intervals, Exploratory Data Analysis, Non-parametric statistics 4. Statistics with Python Specialization by University of Michigan on Coursera 🔸Level: Beginner 🔸Duration: 3 months (5 hours/week) 🔸Fee: Free to audit 🔸What you’ll learn: Python Programming, Data Visualization (DataViz), Statistical Model, Statistical inference methods . Become statistically significant in the job market by completing these courses.😉 . Type “Statistics” for the link to these courses 👍 . Remember to Follow @citizendatascientist & @saurabhmoody for more curated Data Science and Analytics content.👏 . . #data #datascience #datascientist #statistics #python #statistic #dataanalytics #dataanalysis #dataanalyst #pythonprogramming #r #rprogramming #programming #statistician #duke #michigan #harvard #datascientistskills #citizendatascientist #alphaaai #superai
A sports statistician in action 🧑‍💻 (via @antzanderson) #sports #sportsdata #sportsbiz #workinginsports #data #statistician #satisitcs
A sports statistician in action 🧑‍💻 (via @antzanderson) #sports #sportsdata #sportsbiz #workinginsports #data #statistician #satisitcs
Did you know that a data scientist job family has existed since 1700s? Before 2012 data scientist were actually called statistician. It wasn’t until the infamous 2012 Harvard business review that rebranded the statistician job family to the scientist. Data scientist is obviously a more glamorous title, which has created a lot more interest in the job family since 2012. But I do wonder what is the purpose of rebranding given the amount of history statisticians have had in important events in history. Thoughts? Why you think there was a rebranding? #datascience #datascientist #machinelearning #womenintech #softwareengineer #dataanalyst #dataanalytics #mlops #techjobs #girlswhocode #statistics #statistician
Did you know that a data scientist job family has existed since 1700s? Before 2012 data scientist were actually called statistician. It wasn’t until the infamous 2012 Harvard business review that rebranded the statistician job family to the scientist. Data scientist is obviously a more glamorous title, which has created a lot more interest in the job family since 2012. But I do wonder what is the purpose of rebranding given the amount of history statisticians have had in important events in history. Thoughts? Why you think there was a rebranding? #datascience #datascientist #machinelearning #womenintech #softwareengineer #dataanalyst #dataanalytics #mlops #techjobs #girlswhocode #statistics #statistician
Link do meu acervo na bio 📚 — Saiba mais sobre o nosso trabalho com Estatística e Ciência de Dados acessando nosso site (link na bio) 💻 -— Hashtags: #estatistica #cienciadedados #consultoria #consultoriaestatistica #assessoria #cursos #aulas #dados #analisededados #basededados #bancodedados #artigo #tcc #dissertação #tese #mestrado #doutorado #analise #data #statistician #statistics #datascience #dataanalytics #database #studygram #study
Link do meu acervo na bio 📚 — Saiba mais sobre o nosso trabalho com Estatística e Ciência de Dados acessando nosso site (link na bio) 💻 -— Hashtags: #estatistica #cienciadedados #consultoria #consultoriaestatistica #assessoria #cursos #aulas #dados #analisededados #basededados #bancodedados #artigo #tcc #dissertação #tese #mestrado #doutorado #analise #data #statistician #statistics #datascience #dataanalytics #database #studygram #study
This is a very common question I get asked. SAVE POST and SCREENSHOT it! The most important of this is to share the work that you have done ✔️ Share it on LinkedIn of the problem that you analyzed and what you learned. Share in comments below of what you analyzed today 👇 #data #dataanalytics #dataanalyst #datascience #datascientist #datacareer #dataanalysis #bigdata #ml #machinelearning #deeplearning #ai #artificialintelligence #datascientists #datamining #database #deeplearning #analytics #statistics #statistician #nuggetsofstatistics #career #careercoach #trending #explorepage #post #desiinusa #desidallas
This is a very common question I get asked. SAVE POST and SCREENSHOT it! The most important of this is to share the work that you have done ✔️ Share it on LinkedIn of the problem that you analyzed and what you learned. Share in comments below of what you analyzed today 👇 #data #dataanalytics #dataanalyst #datascience #datascientist #datacareer #dataanalysis #bigdata #ml #machinelearning #deeplearning #ai #artificialintelligence #datascientists #datamining #database #deeplearning #analytics #statistics #statistician #nuggetsofstatistics #career #careercoach #trending #explorepage #post #desiinusa #desidallas
Someone tell me what it means?⚡️I think ‘Contradiction’ suffices.🤣 Being a Maths student, i assume it so. #mathematician #statistician #math #hr13ingermany #kaiserslautern
Someone tell me what it means?⚡️I think ‘Contradiction’ suffices.🤣 Being a Maths student, i assume it so. #mathematician #statistician #math #hr13ingermany #kaiserslautern
🆕 Episode 7: How are European statistics made? 📊 To mark European Statistics Day, this episode of our podcast series #StatsInAWrap is dedicated to Eurostat. Our objective was to take our users on a small journey through the inner mechanics of the organization and the craft of the people who work here.📈📊 🎧Listen through the LINK IN BIO! #EurStatsDay . . . #data #database #statistics #datascience #stats #statistical #powerofdata #dataviz #publicdata #europedata #Eurostat #AskEurostat #EU #europeanstatisticsday #statistician
🆕 Episode 7: How are European statistics made? 📊 To mark European Statistics Day, this episode of our podcast series #StatsInAWrap is dedicated to Eurostat. Our objective was to take our users on a small journey through the inner mechanics of the organization and the craft of the people who work here.📈📊 🎧Listen through the LINK IN BIO! #EurStatsDay . . . #data #database #statistics #datascience #stats #statistical #powerofdata #dataviz #publicdata #europedata #Eurostat #AskEurostat #EU #europeanstatisticsday #statistician
What programming language should I learn? Learn any of these and your bright future is guaranteed! (in the order of my preference) Wonderful libraries, great community support, simple syntax and easy to learn.. Yep, that’s Python. Powerful ML and NLP libraries such as: PyTorch, TensorFlow, SpaCy, NLTK and Hugging Face (on top of PyTorch). 2 Java: the best object-oriented programming language with easy access to big data platforms like Apache Spark and Hadoop. Deep Java Library (by Amazon), TensorFlow support, Java-ML and much more. JVM (Java Virtual Machine Technology) makes it run easily across Java- supported platforms. Julia (by MIT): best suited for numerical analytics and computing, which is, duh, what Al is all about It works with popular editors and IDEs such as Vim and Visual Studio. Library-wise it’s not as rich as the previous two, but it’s getting there There are wrappers available like TensorFlow.jl and Mocha (similar to caffe). Swift is a young language, developed by apple, but it’s not just for app development, heard of “Swift for TensorFlow”? ➡The next generation system for deep learning and differentiable computing. Soon we’ll have a swift version of all libraries, Fast. Al is focusing on embracing Swift for Deep Learning. Swift is fas, high performance with good support, and might really lead in the future of Al world. Couldn’t end this Reels without mentioning Kotlin: also a young language, by Google for Android app development, with similar syntax to Swift. It’s initially designed for the JVM, so could be a good alternative to Java too. I’d say as much chance as Java has to lead, Kotlin does as well. You can also leverage Jupyter notebook (Kotlin-Jupyter) to get your hands dirty! ⭕️What’s your favorite programming language? Follow @INSAID for Data Science, Artificial Intelligence and Machine Learning tutorials and Tech news! If you like the posts share it with your techie friends. And btw If you have questions please ask them as comments. #Statistics #datascience #dataanalytics #dataanalyst #data #datascienceenthusiasts #statistician #nuggetsofstatistics #machinelearning #learning #trending
What programming language should I learn? Learn any of these and your bright future is guaranteed! (in the order of my preference) Wonderful libraries, great community support, simple syntax and easy to learn.. Yep, that’s Python. Powerful ML and NLP libraries such as: PyTorch, TensorFlow, SpaCy, NLTK and Hugging Face (on top of PyTorch). 2 Java: the best object-oriented programming language with easy access to big data platforms like Apache Spark and Hadoop. Deep Java Library (by Amazon), TensorFlow support, Java-ML and much more. JVM (Java Virtual Machine Technology) makes it run easily across Java- supported platforms. Julia (by MIT): best suited for numerical analytics and computing, which is, duh, what Al is all about It works with popular editors and IDEs such as Vim and Visual Studio. Library-wise it’s not as rich as the previous two, but it’s getting there There are wrappers available like TensorFlow.jl and Mocha (similar to caffe). Swift is a young language, developed by apple, but it’s not just for app development, heard of “Swift for TensorFlow”? ➡The next generation system for deep learning and differentiable computing. Soon we’ll have a swift version of all libraries, Fast. Al is focusing on embracing Swift for Deep Learning. Swift is fas, high performance with good support, and might really lead in the future of Al world. Couldn’t end this Reels without mentioning Kotlin: also a young language, by Google for Android app development, with similar syntax to Swift. It’s initially designed for the JVM, so could be a good alternative to Java too. I’d say as much chance as Java has to lead, Kotlin does as well. You can also leverage Jupyter notebook (Kotlin-Jupyter) to get your hands dirty! ⭕️What’s your favorite programming language? Follow @INSAID for Data Science, Artificial Intelligence and Machine Learning tutorials and Tech news! If you like the posts share it with your techie friends. And btw If you have questions please ask them as comments. #Statistics #datascience #dataanalytics #dataanalyst #data #datascienceenthusiasts #statistician #nuggetsofstatistics #machinelearning #learning #trending
These are five reasons to choose Data Science as your career 📌 1️⃣ - Large amount of Data is generated every minute. Watching this reel is also generating data 😉 2️⃣ - Growing demand for data professionals. Increase in data would require more people to handle 3️⃣ - High paying jobs 🤑 4️⃣ - Ample opportunities in every sector. Financial services, media, retail, sports, healthcare etc. 5️⃣ - Wide range of job profiles. Data analyst, Business analyst, Data Scientist, Data Engineer, ML Engineer to name few. Drop a like and share this reel if you liked it. 😄 Don’t forget to turn on post notifications 🔔 . . . Follow @analytic__ace . . . #statistics #datascience #dataanalyticss #dataanalyst #data #datascienceenthusiasts #statistician #nuggetsofstatistics #machinelearning #learning #trending #mathematics #tips #analytics #ml #career #teaching #businessanalyticss #explorepage #howto #why #reels #instagood #instagram
These are five reasons to choose Data Science as your career 📌 1️⃣ - Large amount of Data is generated every minute. Watching this reel is also generating data 😉 2️⃣ - Growing demand for data professionals. Increase in data would require more people to handle 3️⃣ - High paying jobs 🤑 4️⃣ - Ample opportunities in every sector. Financial services, media, retail, sports, healthcare etc. 5️⃣ - Wide range of job profiles. Data analyst, Business analyst, Data Scientist, Data Engineer, ML Engineer to name few. Drop a like and share this reel if you liked it. 😄 Don’t forget to turn on post notifications 🔔 . . . Follow @analytic__ace . . . #statistics #datascience #dataanalyticss #dataanalyst #data #datascienceenthusiasts #statistician #nuggetsofstatistics #machinelearning #learning #trending #mathematics #tips #analytics #ml #career #teaching #businessanalyticss #explorepage #howto #why #reels #instagood #instagram
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