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As AI revolutionises industries and transforms job markets, staying ahead means mastering essential skills.
Upskill with IIT Mandi's AI/ML course, taught by IIT professors, and secure :
✅ 24 Program Credits
✅ Assured Placement Assistance
✅ Live Lectures from IIT Mandi Professors
So what are you waiting for? This is your chance to stay ahead!
Apply now and secure your future:
https://epcw.short.gy/DPK_DataScience_AIML
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Forwarded from Python for Data Analysts
Infosys Python - Pandas Interview Q & A.pdf
56.8 KB
👉🏻 DO LIKE IF YOU WANT MORE CONTENT LIKE THIS FOR FREE 🆓
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Complete Roadmap to learn DSA in 30 days
Day 1-5: Introduction to Data Structures and Algorithms
- Understand the importance of DSA in programming
- Learn about different types of data structures (arrays, linked lists, stacks, queues, trees, graphs)
- Study basic algorithms like searching and sorting
Day 6-10: Arrays and Strings
- Dive deeper into arrays and strings
- Learn about common operations and algorithms on arrays and strings
- Practice solving problems related to arrays and strings
Day 11-15: Linked Lists
- Study linked lists and their variations (singly linked list, doubly linked list, circular linked list)
- Implement basic operations on linked lists
- Solve problems involving linked lists
Day 16-20: Stacks and Queues
- Learn about stacks and queues and their applications
- Implement stack and queue data structures
- Solve problems using stacks and queues
Day 21-25: Trees and Graphs
- Study binary trees, binary search trees, AVL trees, heaps, and graphs
- Understand traversal algorithms (inorder, preorder, postorder) for trees
- Implement basic graph algorithms (DFS, BFS)
- Solve problems related to trees and graphs
Day 26-30: Advanced Topics
- Study advanced data structures like hash tables, tries, segment trees
- Learn about dynamic programming, backtracking, and divide and conquer algorithms
- Practice solving complex problems that require a combination of data structures and algorithms
Throughout the 30 days, make sure to practice regularly by solving coding problems on platforms like LeetCode, HackerRank, or Codeforces. Additionally, review your concepts regularly and seek out resources like online tutorials, textbooks, and study groups to deepen your understanding of DSA.
5⃣ Free DSA resources to crack coding interview
👉 GeekforGeeks
👉 Leetcode
👉 Hackerrank
👉 DSA Resources
👉 FreeCodeCamp
Join for more free resources: https://t.iss.one/free4unow_backup
ENJOY LEARNING 👍👍
Day 1-5: Introduction to Data Structures and Algorithms
- Understand the importance of DSA in programming
- Learn about different types of data structures (arrays, linked lists, stacks, queues, trees, graphs)
- Study basic algorithms like searching and sorting
Day 6-10: Arrays and Strings
- Dive deeper into arrays and strings
- Learn about common operations and algorithms on arrays and strings
- Practice solving problems related to arrays and strings
Day 11-15: Linked Lists
- Study linked lists and their variations (singly linked list, doubly linked list, circular linked list)
- Implement basic operations on linked lists
- Solve problems involving linked lists
Day 16-20: Stacks and Queues
- Learn about stacks and queues and their applications
- Implement stack and queue data structures
- Solve problems using stacks and queues
Day 21-25: Trees and Graphs
- Study binary trees, binary search trees, AVL trees, heaps, and graphs
- Understand traversal algorithms (inorder, preorder, postorder) for trees
- Implement basic graph algorithms (DFS, BFS)
- Solve problems related to trees and graphs
Day 26-30: Advanced Topics
- Study advanced data structures like hash tables, tries, segment trees
- Learn about dynamic programming, backtracking, and divide and conquer algorithms
- Practice solving complex problems that require a combination of data structures and algorithms
Throughout the 30 days, make sure to practice regularly by solving coding problems on platforms like LeetCode, HackerRank, or Codeforces. Additionally, review your concepts regularly and seek out resources like online tutorials, textbooks, and study groups to deepen your understanding of DSA.
5⃣ Free DSA resources to crack coding interview
👉 GeekforGeeks
👉 Leetcode
👉 Hackerrank
👉 DSA Resources
👉 FreeCodeCamp
Join for more free resources: https://t.iss.one/free4unow_backup
ENJOY LEARNING 👍👍
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Here are some of the most popular python project ideas: 💡
Simple Calculator
Text-Based Adventure Game
Number Guessing Game
Password Generator
Dice Rolling Simulator
Mad Libs Generator
Currency Converter
Leap Year Checker
Word Counter
Quiz Program
Email Slicer
Rock-Paper-Scissors Game
Web Scraper (Simple)
Text Analyzer
Interest Calculator
Unit Converter
Simple Drawing Program
File Organizer
BMI Calculator
Tic-Tac-Toe Game
To-Do List Application
Inspirational Quote Generator
Task Automation Script
Simple Weather App
Automate data cleaning and analysis (EDA)
Sales analysis
Sentiment analysis
Price prediction
Customer Segmentation
Time series forecasting
Image classification
Spam email detection
Credit card fraud detection
Market basket analysis
NLP, etc
These are just starting points. Feel free to explore, combine ideas, and personalize your projects based on your interest and skills. 🎯
Simple Calculator
Text-Based Adventure Game
Number Guessing Game
Password Generator
Dice Rolling Simulator
Mad Libs Generator
Currency Converter
Leap Year Checker
Word Counter
Quiz Program
Email Slicer
Rock-Paper-Scissors Game
Web Scraper (Simple)
Text Analyzer
Interest Calculator
Unit Converter
Simple Drawing Program
File Organizer
BMI Calculator
Tic-Tac-Toe Game
To-Do List Application
Inspirational Quote Generator
Task Automation Script
Simple Weather App
Automate data cleaning and analysis (EDA)
Sales analysis
Sentiment analysis
Price prediction
Customer Segmentation
Time series forecasting
Image classification
Spam email detection
Credit card fraud detection
Market basket analysis
NLP, etc
These are just starting points. Feel free to explore, combine ideas, and personalize your projects based on your interest and skills. 🎯
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6. Vue ➝ https://vueschool.io
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➡️ Give Reactions 🙌
1. HTML ➝ https://t.iss.one/webdevcoursefree/870
2. CSS ➝ https://css-tricks.com
3. JavaScript ➝ https://t.iss.one/javascript_courses/309
4. React ➝ https://react-tutorial.app
5. Tailwind CSS ➝ https://scrimba.com
6. Vue ➝ https://vueschool.io
7. Python ➝ https://t.iss.one/pythonanalyst
8. SQL ➝ https://t.iss.one/sqlanalyst
9. Git and GitHub ➝ https://GitFluence.com
10. Blockchain ➝ https://Cryptozombies.io
11. Mongo DB ➝ https://mongodb.com
12. Node JS ➝ https://nodejsera.com
➡️ Give Reactions 🙌
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Check out the list of top 10 Python projects on GitHub given below.
1. Magenta: Explore the artist inside you with this python project. A Google Brain’s brainchild, it leverages deep learning and reinforcement learning algorithms to create drawings, music, and other similar artistic products.
2. Photon: Designing web crawlers can be fun with the Photon project. It is a fast crawler designed for open-source intelligence tools. Photon project helps you perform data crawling functions, which include extracting data from URLs, e-mails, social media accounts, XML and pdf files, and Amazon buckets.
3. Mail Pile: Want to learn some encrypting tricks? This project on GitHub can help you learn to send and receive PGP encrypted electronic mails. Powered by Bayesian classifiers, it is capable of automatic tagging and handling huge volumes of email data, all organized in a clean web interface.
4. XS Strike: XS Strike helps you design a vulnerability to check your network’s security. It is a security suite developed to detect vulnerability attacks. XSS attacks inject malicious scripts into web pages. XSS’s features include four handwritten parsers, a payload generator, a fuzzing engine, and a fast crawler.
5. Google Images Download: It is a script that looks for keywords and phrases to optionally download the image files. All you need to do is, replicate the source code of this project to get a sense of how it works in practice.
6. Pandas Project: Pandas library is a collection of data structures that can be used for flexible data analysis and data manipulation. Compared to other libraries, its flexibility, intuitiveness, and automated data manipulation processes make it a better choice for data manipulation.
7. Xonsh: Used for designing interactive applications without the need for command-line interpreters like Unix. It is a Python-powered Shell language that commands promptly. An easily scriptable application that comes with a standard library, and various types of variables and has its own virtual environment management system.
8. Manim: The Mathematical Animation Engine, Manim, can create video explainers. Using Python 3.7, it produces animated videos, with added illustrations and display graphs. Its source code is freely available on GitHub and for tutorials and installation guides, you can refer to their 3Blue1Brown YouTube channel.
9. AI Basketball Analysis: It is an artificial intelligence application that analyses basketball shots using an object detection concept. All you need to do is upload the files or submit them as a post requests to the API. Then the OpenPose library carries out the calculations to generate the results.
10. Rebound: A great project to put Python to use in building Stackoverflow content, this tool is built on the Urwid console user interface, and solves compiler errors. Using this tool, you can learn how the Beautiful Soup package scrapes StackOverflow and how subprocesses work to find compiler errors.
1. Magenta: Explore the artist inside you with this python project. A Google Brain’s brainchild, it leverages deep learning and reinforcement learning algorithms to create drawings, music, and other similar artistic products.
2. Photon: Designing web crawlers can be fun with the Photon project. It is a fast crawler designed for open-source intelligence tools. Photon project helps you perform data crawling functions, which include extracting data from URLs, e-mails, social media accounts, XML and pdf files, and Amazon buckets.
3. Mail Pile: Want to learn some encrypting tricks? This project on GitHub can help you learn to send and receive PGP encrypted electronic mails. Powered by Bayesian classifiers, it is capable of automatic tagging and handling huge volumes of email data, all organized in a clean web interface.
4. XS Strike: XS Strike helps you design a vulnerability to check your network’s security. It is a security suite developed to detect vulnerability attacks. XSS attacks inject malicious scripts into web pages. XSS’s features include four handwritten parsers, a payload generator, a fuzzing engine, and a fast crawler.
5. Google Images Download: It is a script that looks for keywords and phrases to optionally download the image files. All you need to do is, replicate the source code of this project to get a sense of how it works in practice.
6. Pandas Project: Pandas library is a collection of data structures that can be used for flexible data analysis and data manipulation. Compared to other libraries, its flexibility, intuitiveness, and automated data manipulation processes make it a better choice for data manipulation.
7. Xonsh: Used for designing interactive applications without the need for command-line interpreters like Unix. It is a Python-powered Shell language that commands promptly. An easily scriptable application that comes with a standard library, and various types of variables and has its own virtual environment management system.
8. Manim: The Mathematical Animation Engine, Manim, can create video explainers. Using Python 3.7, it produces animated videos, with added illustrations and display graphs. Its source code is freely available on GitHub and for tutorials and installation guides, you can refer to their 3Blue1Brown YouTube channel.
9. AI Basketball Analysis: It is an artificial intelligence application that analyses basketball shots using an object detection concept. All you need to do is upload the files or submit them as a post requests to the API. Then the OpenPose library carries out the calculations to generate the results.
10. Rebound: A great project to put Python to use in building Stackoverflow content, this tool is built on the Urwid console user interface, and solves compiler errors. Using this tool, you can learn how the Beautiful Soup package scrapes StackOverflow and how subprocesses work to find compiler errors.
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