Please go through this top 10 SQL projects with Datasets that you can practice and can add in your resume
📌1. Social Media Analytics:
(https://www.kaggle.com/amanajmera1/framingham-heart-study-dataset)
🚀2. Web Analytics:
(https://www.kaggle.com/zynicide/wine-reviews)
📌3. HR Analytics:
(https://www.kaggle.com/pavansubhasht/ibm-hr-analytics-
attrition-dataset)
🚀4. Healthcare Data Analysis:
(https://www.kaggle.com/cdc/mortality)
📌5. E-commerce Analysis:
(https://www.kaggle.com/olistbr/brazilian-ecommerce)
🚀6. Inventory Management:
(https://www.kaggle.com/datasets?
search=inventory+management)
📌 7.Customer Relationship Management:
(https://www.kaggle.com/pankajjsh06/ibm-watson-
marketing-customer-value-data)
🚀8. Financial Data Analysis:
(https://www.kaggle.com/awaiskalia/banking-database)
📌9. Supply Chain Management:
(https://www.kaggle.com/shashwatwork/procurement-analytics)
🚀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
📌1. Social Media Analytics:
(https://www.kaggle.com/amanajmera1/framingham-heart-study-dataset)
🚀2. Web Analytics:
(https://www.kaggle.com/zynicide/wine-reviews)
📌3. HR Analytics:
(https://www.kaggle.com/pavansubhasht/ibm-hr-analytics-
attrition-dataset)
🚀4. Healthcare Data Analysis:
(https://www.kaggle.com/cdc/mortality)
📌5. E-commerce Analysis:
(https://www.kaggle.com/olistbr/brazilian-ecommerce)
🚀6. Inventory Management:
(https://www.kaggle.com/datasets?
search=inventory+management)
📌 7.Customer Relationship Management:
(https://www.kaggle.com/pankajjsh06/ibm-watson-
marketing-customer-value-data)
🚀8. Financial Data Analysis:
(https://www.kaggle.com/awaiskalia/banking-database)
📌9. Supply Chain Management:
(https://www.kaggle.com/shashwatwork/procurement-analytics)
🚀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
👍7❤5
Python Cryptography Roadmap
Stage 1 – Learn Python (Basics, File Handling)
Stage 2 – Understand Encryption/Decryption Basics (Symmetric, Asymmetric)
Stage 3 – Explore Python Libraries (cryptography, PyCrypto, hashlib)
Stage 4 – Implement Symmetric Ciphers (AES, DES)
Stage 5 – Use Asymmetric Ciphers (RSA, ECC)
Stage 6 – Learn Digital Signatures & Certificates
Stage 7 – Secure Data Transmission (SSL/TLS)
Stage 8 – Explore Hashing Algorithms (SHA, MD5)
🏆 – Python Cryptography Developer
Stage 1 – Learn Python (Basics, File Handling)
Stage 2 – Understand Encryption/Decryption Basics (Symmetric, Asymmetric)
Stage 3 – Explore Python Libraries (cryptography, PyCrypto, hashlib)
Stage 4 – Implement Symmetric Ciphers (AES, DES)
Stage 5 – Use Asymmetric Ciphers (RSA, ECC)
Stage 6 – Learn Digital Signatures & Certificates
Stage 7 – Secure Data Transmission (SSL/TLS)
Stage 8 – Explore Hashing Algorithms (SHA, MD5)
🏆 – Python Cryptography Developer
👍3
Python Data Science Roadmap
Stage 1 - Master Python basics (syntax, OOP).
Stage 2 - Learn data manipulation with Pandas and NumPy.
Stage 3 - Understand data visualization using Matplotlib & Seaborn.
Stage 4 - Study probability, statistics, and data distributions.
Stage 5 - Explore machine learning with Scikit-learn.
Stage 6 - Work with SQL databases and data querying.
Stage 7 - Implement big data tools like PySpark.
Stage 8 - Develop predictive models and deploy them.
🏆 – Python Data Scientist
Stage 1 - Master Python basics (syntax, OOP).
Stage 2 - Learn data manipulation with Pandas and NumPy.
Stage 3 - Understand data visualization using Matplotlib & Seaborn.
Stage 4 - Study probability, statistics, and data distributions.
Stage 5 - Explore machine learning with Scikit-learn.
Stage 6 - Work with SQL databases and data querying.
Stage 7 - Implement big data tools like PySpark.
Stage 8 - Develop predictive models and deploy them.
🏆 – Python Data Scientist
👍3
Top 8 Github Repos to Learn Data Science and Python 👇👇
https://t.iss.one/github_coding/7
https://t.iss.one/github_coding/7
Best way to prepare for Python interviews 👇👇
1. Fundamentals: Strengthen your understanding of Python basics, including data types, control structures, functions, and object-oriented programming concepts.
2. Data Structures and Algorithms: Familiarize yourself with common data structures (lists, dictionaries, sets, etc.) and algorithms. Practice solving coding problems on platforms like LeetCode or HackerRank.
3. Problem Solving: Develop problem-solving skills by working on real-world scenarios. Understand how to approach and solve problems efficiently using Python.
4. Libraries and Frameworks: Be well-versed in popular Python libraries and frameworks relevant to the job, such as NumPy, Pandas, Flask, or Django. Demonstrate your ability to apply these tools in practical situations.
5. Web Development (if applicable): If the position involves web development, understand web frameworks like Flask or Django. Be ready to discuss your experience in building web applications using Python.
6. Database Knowledge: Have a solid understanding of working with databases in Python. Know how to interact with databases using SQLAlchemy or Django ORM.
7. Testing and Debugging: Showcase your proficiency in writing unit tests and debugging code. Understand testing frameworks like pytest and debugging tools available in Python.
8. Version Control: Familiarize yourself with version control systems, particularly Git, and demonstrate your ability to collaborate on projects using Git.
9. Projects: Showcase relevant projects in your portfolio. Discuss the challenges you faced, solutions you implemented, and the impact of your work.
10. Soft Skills: Highlight your communication and collaboration skills. Be ready to explain your thought process and decision-making during technical discussions.
Best Resource to learn Python
Python Interview Questions with Answers
Freecodecamp Python Course with FREE Certificate
Python for Data Analysis and Visualization
Python course for beginners by Microsoft
Python course by Google
Please give us credits while sharing: -> https://t.iss.one/free4unow_backup
ENJOY LEARNING 👍👍
1. Fundamentals: Strengthen your understanding of Python basics, including data types, control structures, functions, and object-oriented programming concepts.
2. Data Structures and Algorithms: Familiarize yourself with common data structures (lists, dictionaries, sets, etc.) and algorithms. Practice solving coding problems on platforms like LeetCode or HackerRank.
3. Problem Solving: Develop problem-solving skills by working on real-world scenarios. Understand how to approach and solve problems efficiently using Python.
4. Libraries and Frameworks: Be well-versed in popular Python libraries and frameworks relevant to the job, such as NumPy, Pandas, Flask, or Django. Demonstrate your ability to apply these tools in practical situations.
5. Web Development (if applicable): If the position involves web development, understand web frameworks like Flask or Django. Be ready to discuss your experience in building web applications using Python.
6. Database Knowledge: Have a solid understanding of working with databases in Python. Know how to interact with databases using SQLAlchemy or Django ORM.
7. Testing and Debugging: Showcase your proficiency in writing unit tests and debugging code. Understand testing frameworks like pytest and debugging tools available in Python.
8. Version Control: Familiarize yourself with version control systems, particularly Git, and demonstrate your ability to collaborate on projects using Git.
9. Projects: Showcase relevant projects in your portfolio. Discuss the challenges you faced, solutions you implemented, and the impact of your work.
10. Soft Skills: Highlight your communication and collaboration skills. Be ready to explain your thought process and decision-making during technical discussions.
Best Resource to learn Python
Python Interview Questions with Answers
Freecodecamp Python Course with FREE Certificate
Python for Data Analysis and Visualization
Python course for beginners by Microsoft
Python course by Google
Please give us credits while sharing: -> https://t.iss.one/free4unow_backup
ENJOY LEARNING 👍👍
👍4❤1
Explain the features of Python / Say something about the benefits of using Python?
Python is a MUST for students and working professionals to become a great Software Engineer specially when they are working in Web Development Domain. I will list down some of the key advantages of learning Python:
○ Simple and easy to learn:
* Learning python programming language is easy and fun.
* Compared to other language, like, Java or C++, its syntax is a way lot easier.
* You also don’t have to worry about the missing semicolons (;) in the end!
* It is more expressive means that it is more understandable and readable.
* Python is a great language for the beginner-level programmers.
* It supports the development of a wide range of applications from simple text processing to WWW browsers to games.
* Easy-to-learn − Python has few keywords, simple structure, and a clearly defined syntax. This makes it easy for Beginners to pick up the language quickly.
* Easy-to-read − Python code is more clearly defined and readable. It's almost like plain and simple English.
* Easy-to-maintain − Python's source code is fairly easy-to-maintain.
Features of Python
○ Python is Interpreted −
* Python is processed at runtime by the interpreter.
* You do not need to compile your program before executing it. This is similar to PERL and PHP.
○ Python is Interactive −
* Python has support for an interactive mode which allows interactive testing and debugging of snippets of code.
* You can open the interactive terminal also referred to as Python prompt and interact with the interpreter directly to write your programs.
○ Python is Object-Oriented −
* Python not only supports functional and structured programming methods, but Object Oriented Principles.
○ Scripting Language —
* Python can be used as a scripting language or it can be compliled to byte-code for building large applications.
○ Dynammic language —
* It provides very high-level dynamic data types and supports dynamic type checking.
○ Garbage collection —
* Garbage collection is a process where the objects that are no longer reachable are freed from memory.
* Memory management is very important while writing programs and python supports automatic garbage collection, which is one of the main problems in writing programs using C & C++.
○ Large Open Source Community —
* Python has a large open source community and which is one of its main strength.
* And its libraries, from open source 118 thousand plus and counting.
* If you are stuck with an issue, you don’t have to worry at all because python has a huge community for help. So, if you have any queries, you can directly seek help from millions of python community members.
* A broad standard library − Python's bulk of the library is very portable and cross-platform compatible on UNIX, Windows, and Macintosh.
* Extendable − You can add low-level modules to the Python interpreter. These modules enable programmers to add to or customize their tools to be more efficient.
○ Cross-platform Language —
* Python is a Cross-platform language or Portable language.
* Python can run on a wide variety of hardware platforms and has the same interface on all platforms.
* Python can run on different platforms such as Windows, Linux, Unix and Macintosh etc.
Python is a MUST for students and working professionals to become a great Software Engineer specially when they are working in Web Development Domain. I will list down some of the key advantages of learning Python:
○ Simple and easy to learn:
* Learning python programming language is easy and fun.
* Compared to other language, like, Java or C++, its syntax is a way lot easier.
* You also don’t have to worry about the missing semicolons (;) in the end!
* It is more expressive means that it is more understandable and readable.
* Python is a great language for the beginner-level programmers.
* It supports the development of a wide range of applications from simple text processing to WWW browsers to games.
* Easy-to-learn − Python has few keywords, simple structure, and a clearly defined syntax. This makes it easy for Beginners to pick up the language quickly.
* Easy-to-read − Python code is more clearly defined and readable. It's almost like plain and simple English.
* Easy-to-maintain − Python's source code is fairly easy-to-maintain.
Features of Python
○ Python is Interpreted −
* Python is processed at runtime by the interpreter.
* You do not need to compile your program before executing it. This is similar to PERL and PHP.
○ Python is Interactive −
* Python has support for an interactive mode which allows interactive testing and debugging of snippets of code.
* You can open the interactive terminal also referred to as Python prompt and interact with the interpreter directly to write your programs.
○ Python is Object-Oriented −
* Python not only supports functional and structured programming methods, but Object Oriented Principles.
○ Scripting Language —
* Python can be used as a scripting language or it can be compliled to byte-code for building large applications.
○ Dynammic language —
* It provides very high-level dynamic data types and supports dynamic type checking.
○ Garbage collection —
* Garbage collection is a process where the objects that are no longer reachable are freed from memory.
* Memory management is very important while writing programs and python supports automatic garbage collection, which is one of the main problems in writing programs using C & C++.
○ Large Open Source Community —
* Python has a large open source community and which is one of its main strength.
* And its libraries, from open source 118 thousand plus and counting.
* If you are stuck with an issue, you don’t have to worry at all because python has a huge community for help. So, if you have any queries, you can directly seek help from millions of python community members.
* A broad standard library − Python's bulk of the library is very portable and cross-platform compatible on UNIX, Windows, and Macintosh.
* Extendable − You can add low-level modules to the Python interpreter. These modules enable programmers to add to or customize their tools to be more efficient.
○ Cross-platform Language —
* Python is a Cross-platform language or Portable language.
* Python can run on a wide variety of hardware platforms and has the same interface on all platforms.
* Python can run on different platforms such as Windows, Linux, Unix and Macintosh etc.
👍9