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7 Websites to Learn Data Science for FREE🧑💻
✅ w3school
✅ datasimplifier
✅ hackerrank
✅ kaggle
✅ geeksforgeeks
✅ leetcode
✅ freecodecamp
✅ w3school
✅ datasimplifier
✅ hackerrank
✅ kaggle
✅ geeksforgeeks
✅ leetcode
✅ freecodecamp
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Free courses to learn Data Science in 2023
👇👇
https://www.linkedin.com/posts/sql-analysts_programming-computerscience-datascience-activity-7126408061472112641-agJe
Like this Linkedin post so that it reaches to more data aspirants ❤️
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https://www.linkedin.com/posts/sql-analysts_programming-computerscience-datascience-activity-7126408061472112641-agJe
Like this Linkedin post so that it reaches to more data aspirants ❤️
👍4
Essential Data Science Skills for data scientists
👇👇
https://www.linkedin.com/posts/sql-analysts_datascience-dataskills-transferableskills-activity-7128372157230809089-GHRF
Add in the comments if anything missed in the post 😄
👇👇
https://www.linkedin.com/posts/sql-analysts_datascience-dataskills-transferableskills-activity-7128372157230809089-GHRF
Add in the comments if anything missed in the post 😄
👍6❤5👏1
ChatGPT for Data Scientist
👇👇
https://www.linkedin.com/posts/sql-analysts_chatgpt-for-data-science-activity-7128583314378043393-kYzL
👇👇
https://www.linkedin.com/posts/sql-analysts_chatgpt-for-data-science-activity-7128583314378043393-kYzL
👍1
❤5
👍4
Data Science & Machine Learning
Do you want Harvard Resume and CV Career Guide?
Nice to 200+ people interested in this
Here is a free resume guide from Harvard
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https://www.linkedin.com/posts/sql-analysts_harvard-resume-and-cv-career-guide-activity-7129694373688070144-RS2m
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Save it for your future reference
Here is a free resume guide from Harvard
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https://www.linkedin.com/posts/sql-analysts_harvard-resume-and-cv-career-guide-activity-7129694373688070144-RS2m
Like and comment on this post so that it reaches more jobseekers 😄👍
Save it for your future reference
👍5❤4
👍4
Which social media platform do you use the most?
Anonymous Poll
54%
Telegram
40%
Whatsapp
26%
Instagram
10%
Twitter
32%
YouTube
3%
Tiktok
18%
Linkedin
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🤬6😁5👍3🥰3
Which of the following python library is used for data visualization?
Anonymous Quiz
92%
Matplotlib
8%
Numpy
👍8😢4
365 data science courses for free till Nov 20
👇👇
https://www.linkedin.com/posts/sql-analysts_datascience-dataanalytics-activity-7128217526924177408-0DtE
Many people in telegram are unnecessarily charging huge money for this course
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https://www.linkedin.com/posts/sql-analysts_datascience-dataanalytics-activity-7128217526924177408-0DtE
Many people in telegram are unnecessarily charging huge money for this course
👍8🔥2🤩1
Top 20 Pandas Interview Questions with Answers
👇👇
https://datasimplifier.com/pandas-interview-questions-with-answers/
👇👇
https://datasimplifier.com/pandas-interview-questions-with-answers/
❤4👍1
Which function is used to read CSV file in Pandas?
Anonymous Quiz
7%
read_file()
85%
read_csv()
5%
readcsvfile()
3%
readfile()
😁7👎1
Forwarded from Data Science Projects
Python Science Projects.pdf_20231120_013618_0000.pdf
2.1 MB
Python Data Science Projects For Boosting Your Portfolio
👍8❤1👏1
10 Things you need to become an AI/ML engineer:
1. Framing machine learning problems
2. Weak supervision and active learning
3. Processing, training, deploying, inference pipelines
4. Offline evaluation and testing in production
5. Performing error analysis. Where to work next
6. Distributed training. Data and model parallelism
7. Pruning, quantization, and knowledge distillation
8. Serving predictions. Online and batch inference
9. Monitoring models and data distribution shifts
10. Automatic retraining and evaluation of models
1. Framing machine learning problems
2. Weak supervision and active learning
3. Processing, training, deploying, inference pipelines
4. Offline evaluation and testing in production
5. Performing error analysis. Where to work next
6. Distributed training. Data and model parallelism
7. Pruning, quantization, and knowledge distillation
8. Serving predictions. Online and batch inference
9. Monitoring models and data distribution shifts
10. Automatic retraining and evaluation of models
👍11🔥5❤2
Software Engineers vs AI Engineers: 👊
Software engineers are often shocked when they learn of AI engineers' salaries. There are two reasons for this surprise.
1. The total compensation for AI engineers is jaw-dropping. You can check it out at AIPaygrad.es, which has manually verified data for AI engineers. The median overall compensation for a “Novice” is $328,350/year.
2. AI engineers are no smarter than software engineers. You figure this out only after a friend or acquaintance upskills and finds a lucrative AI job.
The biggest difference between Software and AI engineers is the demand for such roles. One role is declining, and the other is reaching stratospheric heights.
Here is an example.
Just last week, we saw an implosion of OpenAI after Sam Altman was unceremoniously removed from his CEO position. About 95% of their AI Engineers threatened to quit in protest. Rumor had it that these 700 engineers had an open job offer from Microsoft. 🚀
Contrast this with the events a few months back. Microsoft laid off 10,000 Software Engineers while setting aside $10B to invest in OpenAI. They cut these jobs despite making stunning profits in 2023.
In conclusion, these events underline a significant shift in the tech industry. For software engineers, it's a call to adapt and possibly upskill in AI, while companies need to balance AI investments with nurturing their current talent. The future of tech hinges on flexibility and continuous learning for everyone involved."
Software engineers are often shocked when they learn of AI engineers' salaries. There are two reasons for this surprise.
1. The total compensation for AI engineers is jaw-dropping. You can check it out at AIPaygrad.es, which has manually verified data for AI engineers. The median overall compensation for a “Novice” is $328,350/year.
2. AI engineers are no smarter than software engineers. You figure this out only after a friend or acquaintance upskills and finds a lucrative AI job.
The biggest difference between Software and AI engineers is the demand for such roles. One role is declining, and the other is reaching stratospheric heights.
Here is an example.
Just last week, we saw an implosion of OpenAI after Sam Altman was unceremoniously removed from his CEO position. About 95% of their AI Engineers threatened to quit in protest. Rumor had it that these 700 engineers had an open job offer from Microsoft. 🚀
Contrast this with the events a few months back. Microsoft laid off 10,000 Software Engineers while setting aside $10B to invest in OpenAI. They cut these jobs despite making stunning profits in 2023.
In conclusion, these events underline a significant shift in the tech industry. For software engineers, it's a call to adapt and possibly upskill in AI, while companies need to balance AI investments with nurturing their current talent. The future of tech hinges on flexibility and continuous learning for everyone involved."
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