Coding & Data Science Resources
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Official Telegram Channel for Free Coding & Data Science Resources

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Some useful telegram channels to learn data analytics & data science

Python interview books
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https://t.iss.one/dsabooks

Data Analyst Interviews
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https://t.iss.one/DataAnalystInterview

SQL for data analysis
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https://t.iss.one/sqlanalyst

Data Science &  Machine Learning
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https://t.iss.one/datasciencefun

Data Science Projects
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https://t.iss.one/pythonspecialist

Python for data analysis
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https://t.iss.one/pythonanalyst

Excel for data analysis
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https://t.iss.one/excel_analyst

Power BI/ Tableau
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https://t.iss.one/PowerBI_analyst

Data Analysis Books
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https://t.iss.one/learndataanalysis
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πŸ•― Sites to practice programming and solve challenges to improve programming skills πŸ•―

1️⃣ https://edabit.com
2️⃣ https://codeforces.com
3️⃣ https://www.codechef.com
4️⃣ https://leetcode.com
5️⃣ https://www.codewars.com
6️⃣ https://www.pythonchallenge.com
7️⃣ https://coderbyte.com
8️⃣ https://www.codingame.com/start
9️⃣ https://www.freecodecamp.org/learn

ENJOY LEARNING πŸ‘πŸ‘
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Please go through this top 10 SQL projects with Datasets that you can practice and can add in your resume

πŸ“Œ1. Social Media Analytics:
(https://www.kaggle.com/amanajmera1/framingham-heart-study-dataset)

πŸš€2. Web Analytics:
(https://www.kaggle.com/zynicide/wine-reviews)

πŸ“Œ3. HR Analytics:
(https://www.kaggle.com/pavansubhasht/ibm-hr-analytics-
attrition-dataset)

πŸš€4. Healthcare Data Analysis:
(https://www.kaggle.com/cdc/mortality)

πŸ“Œ5. E-commerce Analysis:
(https://www.kaggle.com/olistbr/brazilian-ecommerce)

πŸš€6. Inventory Management:
(https://www.kaggle.com/datasets?
search=inventory+management)

πŸ“Œ 7.Customer Relationship Management:
(https://www.kaggle.com/pankajjsh06/ibm-watson-
marketing-customer-value-data)

πŸš€8. Financial Data Analysis:
(https://www.kaggle.com/awaiskalia/banking-database)

πŸ“Œ9. Supply Chain Management:
(https://www.kaggle.com/shashwatwork/procurement-analytics)

πŸš€10. Analysis of Sales Data:
(https://www.kaggle.com/kyanyoga/sample-sales-data)

Small suggestion from my side for non tech students: kindly pick those datasets which you like the subject in general, that way you will be more excited to practice it, instead of just doing it for the sake of resume, you will learn SQL more passionately, since it’s a programming language try to make it more exciting for yourself.

Join for more: https://t.iss.one/DataPortfolio

Hope this piece of information helps you
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Python Projects
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Generative AI in Data Analytics βœ…
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⭐️6 Tips to Study Coding Effectively⭐️
by UFV Academic Success Centre

1. Don’t just read the code exampleβ€”Type it out and then create a similar one
πŸ”Ή A code sample is the representation of the idea or program.
πŸ”Ή Type it in your own words to understand how the five components are working together.
πŸ”Ή Create a similar sample to understand the abstract of the program.
πŸ”Ή Try some code challenges from some well-known websites, such as leetcode, codewars, and
topcoders.

2. Practice and keep track of what you have learned
πŸ”Ή Practice makes perfect.
πŸ”Ή As a programmer, you often can have some repetitive tasks. Keeping track of what you learn will
help you quickly refer back to the tasks you have done.
πŸ”Ή Document what you have learned. Documentation is a good resource to help you look up the
algorithm/solution and repetitive tasks easily and increase your productivity rapidly.

3. Try to create, then build your own program
πŸ”Ή Apply what you have learned to a real-life example.
πŸ”Ή Building your own program brings you to the next level of program abstract and will help you feel
satisfied and accomplished with what you have learned.
πŸ”Ή When you come up with a solution, try a different approach. There is more than one right way to
do something, and searching for different solutions will help you develop your problem solving
skills.

4. Learn how to research and solve problems
πŸ”Ή Search for topics by specific keywords.
πŸ”Ή Learn how to research your problem when you get stuck. Some websites may help, such as
stackoverflow, stackexchange, github, and forums.
πŸ”Ή If you find a solution online, make sure you understand every line of code. You will learn more this
way rather than just copying and pasting it into your project.

5. Take a break while debugging
πŸ”Ή Consider taking break to clear your mind when you encounter difficult bug.
πŸ”Ή Stepping away for a few hours will allow you to return with a fresh perspective.

6. Things to avoid
πŸ”Ή Perfection: As a beginner, improving your coding skills and problem solving are more important
than making your code perfect. Seeking perfection will cause you to procrastinate instead of
progress. Remember that mistakes are opportunities to learn.
πŸ”Ή Comparison: Never compare your code style/knowledge with anyone else. You will end up being
disappointed and demotivated. Practice and trust yourself.
πŸ”Ή Complexity: Learn how to break a problem into smaller problems, so you can conquer it more
easily.
A good programmer is able to make a program simpler and less complex. Make it work first, then
make it right, finally make it fast. β€œSimplicity is the ultimate sophistication,” said Leonardo Da Vinci.
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NumPy_SciPy_Pandas_Quandl_Cheat_Sheet.pdf
134.6 KB
Cheatsheet on Numpy and pandas for easy viewing πŸ‘€
ibm_machine_learning_for_dummies.pdf
1.8 MB
Short Machine Learning guide on industry applications and how it’s used to resolve problems πŸ’‘
1663243982009.pdf
349.9 KB
All SQL solutions for leetcode, good luck grinding 🫣
git-cheat-sheet-education.pdf
97.8 KB
Git commands cheatsheets for anyone working on personal projects on GitHub! πŸ‘Ύ
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