Coding Interview Resources

Turkey and the EU. Who needs who?  ✔️Turkey has been striving to join the European Union for many years. But the EU is making more and more demands on the country. Ankara has repeatedly asked how long this will last. Asked Turkey and present the entire list of requirements.  " Now Erdogan says that the security of Europe without Turkey is impossible against the background of the weakening of the European Union. The EU is transforming it from a subject of world politics into an object whose future architecture is being worked on by world powers. Turkey is also trying to grab its own piece of the pie in this process." For a long time, Europe kept Turkey at the door, not allowing it to join the European Union. But in the current circumstances, the situation may change." And if Turkey is still accepted in the EU, it will play a dominant role in the new European subsystem." Players like France, Poland, and many other countries will not want this. But in many ways, the possibility or impossibility of Turkey's accession to the EU (as well as the preservation of the EU itself) depends on the United States. ✔️Turkey remains a non-EU entry country. For the European Union – it is a Muslim country with a large number of inhabitants (mostly poor) and a foreign aggressive culture. The absence of the principle of homogeneity also remains valid. Therefore, Turkey will not be accepted in the EU. Speaking about joining the EU, Erdogan has other goals. He sees that there is a sharp rise in right-wing sentiment in Europe, and the European supranational ideology is in a deep crisis. Caricature figures from the European Commission imposed an ultra-liberal agenda on Europe, which led to the strengthening of ultra-right forces. And right-wing Europeans are mostly anti-Muslim. Right-wing Europe will be hostile to Erdogan, so he offers protection to Muslim minorities.  ✔️He says that if Turkey joins the EU, it could solve the problem of labor shortage, give an economic incentive, etc. With him, the Muslims of Europe will receive strong support, and Erdogan at their expense, since these people are also voters, will have an influence on internal European affairs.  Erdogan makes it clear that he will use the levers of pressure he already has on the EU. This is also the gas issue (Erdogan managed to concentrate a significant part of gas transit flows to Europe).And immigration (ability to open / close floodgates for refugees). And in the very distant future, this influence can be converted into Turkey's membership in the EU. #Turkey #EU #Erdogan #Muslim #crisis 🇪🇺 Keep up with the latest Star Union News  🖥

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List vs Tuple

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Recursion is a problem-solving technique in which the solution is dependent on solutions to smaller instances of the same problem. Computing factorials is a classic example of recursive programming. Every recursive program follows the same basic sequence of steps: Set up the algorithm. Recursive programs frequently require a seed value, to begin with. This is accomplished by either using a parameter passed to the function or by providing a non-recursive gateway function that sets up the seed values for the recursive calculation. Check to see if the current value(s) being processed correspond to the base case. If so, process the value and return it. Rephrase the solution in terms of a smaller or simpler sub-problem or sub-problems. Apply the algorithm to the sub-problem. In order to formulate an answer, combine the results. Return the results.

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Starting a career in coding involves learning programming languages, practicing problem-solving, and building real-world projects. Here's a step-by-step guide to help you get started: 1. Choose a Programming Language For Web Development: HTML, CSS, JavaScript For Data Science: Python, R For Software Development: Python, Java, C++, C# For Mobile Development: Java/Kotlin (Android), Swift (iOS), Flutter If unsure, start with Python—it’s beginner-friendly and widely used. 2. Learn the Fundamentals Variables, Data Types Loops, Conditionals Functions, Object-Oriented Programming Data Structures (Lists, Arrays, Dictionaries) Algorithms (Sorting, Searching, Recursion) 3. Practice with Hands-on Projects Web: Portfolio website, To-Do List app, Weather app Python: Calculator, Data analysis projects, Web scraping Game Dev: Simple 2D game (Pygame, Unity) Mobile: Expense tracker, Notes app Use GitHub to store projects and build a portfolio. 4. Solve Coding Challenges LeetCode – Best for coding interviews HackerRank – Beginner-friendly challenges CodeWars – Fun coding puzzles 5. Learn Version Control (Git & GitHub) Creating repositories Pushing and pulling code Branching and merging 6. Explore Development Tools VS Code (Best for beginners) PyCharm (For Python) Eclipse/IntelliJ (For Java) Android Studio (For Android development) 7. Get Certified (Optional) Google IT Automation with Python AWS Certified Developer Microsoft Certified: Azure Developer Associate 8. Apply for Internships & Freelance Work Look for internships or entry-level jobs Contribute to open-source projects Offer freelance work on Upwork, Fiverr, Freelancer 9. Network & Join Coding Communities Join LinkedIn, Reddit (r/learnprogramming), and Stack Overflow Contribute to GitHub open-source projects Attend hackathons and meetups 10. Keep Learning & Growing Explore cloud computing (AWS, Google Cloud, Azure) Learn machine learning & AI Stay updated with cybersecurity best practices You can check these resources for Coding interview Preparation Join our WhatsApp channel for more resources: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X All the best 👍👍

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Coding and Aptitude Round before interview Coding challenges are meant to test your coding skills (especially if you are applying for ML engineer role). The coding challenges can contain algorithm and data structures problems of varying difficulty. These challenges will be timed based on how complicated the questions are. These are intended to test your basic algorithmic thinking. Sometimes, a complicated data science question like making predictions based on twitter data are also given. These challenges are hosted on HackerRank, HackerEarth, CoderByte etc. In addition, you may even be asked multiple-choice questions on the fundamentals of data science and statistics. This round is meant to be a filtering round where candidates whose fundamentals are little shaky are eliminated. These rounds are typically conducted without any manual intervention, so it is important to be well prepared for this round. Sometimes a separate Aptitude test is conducted or along with the technical round an aptitude test is also conducted to assess your aptitude skills. A Data Scientist is expected to have a good aptitude as this field is continuously evolving and a Data Scientist encounters new challenges every day. If you have appeared for GMAT / GRE or CAT, this should be easy for you. Resources for Prep: For algorithms and data structures prep,Leetcode and Hackerrank are good resources. For aptitude prep, you can refer to IndiaBixand Practice Aptitude. With respect to data science challenges, practice well on GLabs and Kaggle. Brilliant is an excellent resource for tricky math and statistics questions. For practising SQL, SQL Zoo and Mode Analytics are good resources that allow you to solve the exercises in the browser itself. Things to Note: Ensure that you are calm and relaxed before you attempt to answer the challenge. Read through all the questions before you start attempting the same. Let your mind go into problem-solving mode before your fingers do! In case, you are finished with the test before time, recheck your answers and then submit. Sometimes these rounds don’t go your way, you might have had a brain fade, it was not your day etc. Don’t worry! Shake if off for there is always a next time and this is not the end of the world. Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624 Credits: https://t.me/datasciencefun Like if you need similar content 😄👍 Hope this helps you 😊 #datascience

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Python Loops ✅

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Python List Methods

PREPARATION GUIDE FOR DATA ANALYST INTERVIEW 👉 Review the job description and requirements: Carefully review the job description and requirements for the data analyst position to understand the specific skills and knowledge required. 👉 Brush up on data analysis concepts and techniques: Make sure you have a solid understanding of data analysis concepts, such as data cleaning, data visualization, and statistical analysis. Review the basics of these techniques, and be familiar with the tools and software used for data analysis. 👉 Study data visualization tools: Familiarize yourself with data visualization tools like Tableau, PowerBI, and others, and be able to explain how to use them to analyze and present data. 👉 Brush up on SQL: SQL is a key tool for data analysts, so be sure to review basic SQL commands and be familiar with more advanced concepts such as joining tables and aggregating data. 👉 Practice your communication skills: Data analysts need to be able to effectively communicate their findings to others, so make sure you have strong written and verbal communication skills. 👉 Be prepared to discuss real-life examples: Be prepared to discuss specific examples of data analysis projects you have worked on, and be able to explain the methods and techniques you used to complete them. 👉 Review the company's data and analytics strategy: Research the company's data and analytics strategy, and be prepared to discuss how your skills and experience align with their goals and objectives. 👉 Free learning resources https://t.me/free4unow_backup/361 ENJOY LEARNING 👍👍

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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.me/free4unow_backup ENJOY LEARNING 👍👍