Hello, I am an Analyst with intermediate Sql skills. I don’t say advanced, because I do need to Google some stuff. Familiar with a bunch of analytics tools. Transitioned to this career from a different industry. I really want to better my data chops: a. Use more Python for analytics automation - not a ton of opportunities in my current role b. create advanced/stunning visualizations, c. get started on a kaggle project, d. develop a sound understanding of terms like machine learning, AI I used to be a self starter but right now recovering from some life events. I really could use some help from a knowledgeable and engaged mentor who can help me make a plan to master these topics. I don’t know how I can re-pay you for your time. For one, I will definitely pay it forward. Please let me know if you will be interested. Thank you!
I teach these topics on one of the online course platforms. Happy to mentor you.
@py1 I’m curious about what your role is at Apple. I have an analytics background but rarely see roles that match.
Interested. (In the same boat)
Working Parents
20h
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Closed now - thank you all
Tech Industry
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Women, help me understand why this is inspirational
India
Yesterday
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Modi is a legend, will be remembered for centuries to come
Tech Industry
2h
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What happens when most of your team is Indian?
Software Engineering Career
Yesterday
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Offers after multiple months of prep
Send me a message. I’m a former teacher with wide experience, now data scientist.
What books/courses do you suggest for starters with basic coding experience?
TL;DR. Really, anything to get you to work on projects and keep learning. For data science/ML concepts, I recommend introduction to statistical learning: http://www-bcf.usc.edu/~gareth/ISL/ (Elements of Statistical Learning is more advanced if you need it) For code, since ISLR has R exercises, for python, go to the source, the author of scikit-learn. ML notebooks: https://github.com/amueller/introduction_to_ml_with_python Then, try Kaggles or self-directed projects. For engineering-type data science, stick to python. But for analytics data science, R may be sufficient. If so, R for data science is likely the best for most people: https://r4ds.had.co.nz/