π1π₯1
Some useful telegram channels to learn data analytics & data science
Python interview books
ππ
https://t.iss.one/dsabooks
Data Analyst Interviews
ππ
https://t.iss.one/DataAnalystInterview
SQL for data analysis
ππ
https://t.iss.one/sqlanalyst
Data Science & Machine Learning
ππ
https://t.iss.one/datasciencefun
Data Science Projects
ππ
https://t.iss.one/pythonspecialist
Python for data analysis
ππ
https://t.iss.one/pythonanalyst
Excel for data analysis
ππ
https://t.iss.one/excel_analyst
Power BI/ Tableau
ππ
https://t.iss.one/PowerBI_analyst
Data Analysis Books
ππ
https://t.iss.one/learndataanalysis
Python interview books
ππ
https://t.iss.one/dsabooks
Data Analyst Interviews
ππ
https://t.iss.one/DataAnalystInterview
SQL for data analysis
ππ
https://t.iss.one/sqlanalyst
Data Science & Machine Learning
ππ
https://t.iss.one/datasciencefun
Data Science Projects
ππ
https://t.iss.one/pythonspecialist
Python for data analysis
ππ
https://t.iss.one/pythonanalyst
Excel for data analysis
ππ
https://t.iss.one/excel_analyst
Power BI/ Tableau
ππ
https://t.iss.one/PowerBI_analyst
Data Analysis Books
ππ
https://t.iss.one/learndataanalysis
π6β€1π₯°1
π― Sites to practice programming and solve challenges to improve programming skills π―
1οΈβ£ https://edabit.com
2οΈβ£ https://codeforces.com
3οΈβ£ https://www.codechef.com
4οΈβ£ https://leetcode.com
5οΈβ£ https://www.codewars.com
6οΈβ£ https://www.pythonchallenge.com
7οΈβ£ https://coderbyte.com
8οΈβ£ https://www.codingame.com/start
9οΈβ£ https://www.freecodecamp.org/learn
ENJOY LEARNING ππ
1οΈβ£ https://edabit.com
2οΈβ£ https://codeforces.com
3οΈβ£ https://www.codechef.com
4οΈβ£ https://leetcode.com
5οΈβ£ https://www.codewars.com
6οΈβ£ https://www.pythonchallenge.com
7οΈβ£ https://coderbyte.com
8οΈβ£ https://www.codingame.com/start
9οΈβ£ https://www.freecodecamp.org/learn
ENJOY LEARNING ππ
π2β€1π1
Please go through this top 10 SQL projects with Datasets that you can practice and can add in your resume
π1. Social Media Analytics:
(https://www.kaggle.com/amanajmera1/framingham-heart-study-dataset)
π2. Web Analytics:
(https://www.kaggle.com/zynicide/wine-reviews)
π3. HR Analytics:
(https://www.kaggle.com/pavansubhasht/ibm-hr-analytics-
attrition-dataset)
π4. Healthcare Data Analysis:
(https://www.kaggle.com/cdc/mortality)
π5. E-commerce Analysis:
(https://www.kaggle.com/olistbr/brazilian-ecommerce)
π6. Inventory Management:
(https://www.kaggle.com/datasets?
search=inventory+management)
π 7.Customer Relationship Management:
(https://www.kaggle.com/pankajjsh06/ibm-watson-
marketing-customer-value-data)
π8. Financial Data Analysis:
(https://www.kaggle.com/awaiskalia/banking-database)
π9. Supply Chain Management:
(https://www.kaggle.com/shashwatwork/procurement-analytics)
π10. 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 itβs 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
π1. Social Media Analytics:
(https://www.kaggle.com/amanajmera1/framingham-heart-study-dataset)
π2. Web Analytics:
(https://www.kaggle.com/zynicide/wine-reviews)
π3. HR Analytics:
(https://www.kaggle.com/pavansubhasht/ibm-hr-analytics-
attrition-dataset)
π4. Healthcare Data Analysis:
(https://www.kaggle.com/cdc/mortality)
π5. E-commerce Analysis:
(https://www.kaggle.com/olistbr/brazilian-ecommerce)
π6. Inventory Management:
(https://www.kaggle.com/datasets?
search=inventory+management)
π 7.Customer Relationship Management:
(https://www.kaggle.com/pankajjsh06/ibm-watson-
marketing-customer-value-data)
π8. Financial Data Analysis:
(https://www.kaggle.com/awaiskalia/banking-database)
π9. Supply Chain Management:
(https://www.kaggle.com/shashwatwork/procurement-analytics)
π10. 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 itβs 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
π1