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@6oa8yergerf7wlg: #audit #fyp

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Sunday 03 May 2026 06:50:25 GMT
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چی ته وایی راسره نه غم وایی نه فکر دی دونیا#پشتون_تاجیک_هزاره_ازبک_زنده_باد🇦🇫 #f #featureme #part279 @Fizzaayy🦋
چی ته وایی راسره نه غم وایی نه فکر دی دونیا#پشتون_تاجیک_هزاره_ازبک_زنده_باد🇦🇫 #f #featureme #part279 @Fizzaayy🦋


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AI is changing the Data Scientist job. But it’s not simply replacing Data Scientists. 🤖📊 OpenAI recently introduced a Data agent in ChatGPT Work that can connect to company data, analyze it using natural-language questions, generate insights, and create interactive dashboards. That means AI can increasingly handle parts of the traditional data workflow: → Data exploration → SQL / data querying → Data analysis → Charts & visualizations → Dashboards & reporting So… is Data Science becoming useless? Not exactly. The bigger shift is that routine data analysis and reporting can become increasingly automated, while human skills like business understanding, problem framing, critical thinking, data validation, and decision-making become more important. The future Data Scientist may need more than Python, SQL, statistics, and machine learning. You need to know: What problem are we actually solving? What does the data really tell us? Can we trust the AI-generated analysis? What decision should the business make? AI can generate an analysis. But asking the right question and making the right decision still requires human judgment. If you're learning Data Science, Machine Learning, AI, or Data Analytics, this shift is worth understanding now. Follow for more AI, Data Science & Machine Learning content. #DataScience #DataScientist #AI #ArtificialIntelligence #MachineLearning #DataAnalytics #AIAgents #DataAnalysis #ChatGPT #OpenAI #SQL #Python #MachineLearningEngineer #AIEngineer #futureofworkuk
AI is changing the Data Scientist job. But it’s not simply replacing Data Scientists. 🤖📊 OpenAI recently introduced a Data agent in ChatGPT Work that can connect to company data, analyze it using natural-language questions, generate insights, and create interactive dashboards. That means AI can increasingly handle parts of the traditional data workflow: → Data exploration → SQL / data querying → Data analysis → Charts & visualizations → Dashboards & reporting So… is Data Science becoming useless? Not exactly. The bigger shift is that routine data analysis and reporting can become increasingly automated, while human skills like business understanding, problem framing, critical thinking, data validation, and decision-making become more important. The future Data Scientist may need more than Python, SQL, statistics, and machine learning. You need to know: What problem are we actually solving? What does the data really tell us? Can we trust the AI-generated analysis? What decision should the business make? AI can generate an analysis. But asking the right question and making the right decision still requires human judgment. If you're learning Data Science, Machine Learning, AI, or Data Analytics, this shift is worth understanding now. Follow for more AI, Data Science & Machine Learning content. #DataScience #DataScientist #AI #ArtificialIntelligence #MachineLearning #DataAnalytics #AIAgents #DataAnalysis #ChatGPT #OpenAI #SQL #Python #MachineLearningEngineer #AIEngineer #futureofworkuk
Gom chân thành đôi mươi để đổi lấy đôi môi em cười 💗 #ketuongvaxuanphi #couple
Gom chân thành đôi mươi để đổi lấy đôi môi em cười 💗 #ketuongvaxuanphi #couple


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