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Repost from Coding Interview
5 Sites to Level Up Your Coding Skills 👨💻👩💻
🔹 leetcode.com
🔹 hackerrank.com
🔹 w3schools.com
🔹 datasimplifier.com
🔹 hackerearth.com
Repost from Coding Interview
Top 15 #AI websites for #Interview Preparations for #Jobseekers!
1) Huru.ai
AI-powered interview prep with tailored questions.
2) Talkberry.ai
Language learning with simulated English job interviews.
3) Interviewigniter.com
AI roleplay simulations for post-interview evaluations.
4) AI Mock Interview - (Sqlpad.io)
Tailored interview practice with personalized feedback.
5) Rightjoin.co
Customized mock interviews based on resumes and job postings.
6) Interviewsby.ai
Custom mock interviews with real-time voice feedback.
7) Jobinterview-ai.com
Real-time AI-assisted English interview practice.
8) Interview Coach
AI-generated job-specific interview questions and guidance.
9) InterviewGPT.ai
AI-powered practice sessions and personalized feedback.
10) Interviewai.me
AI-generated personalized cover letters and interview questions.
11) Interviewprep-ai.com
Streamlined CV integration and customized interview practice.
12) Interview warmup (grow.google)
Practice platform for answering interview questions with transcription.
13) Metaview.ai
Interview Notes
14) Applyish.com
Apply Automatically
15) Hnresumetojobs.com
Resume to jobs
16) Matchthaoleai.com
Job search
Repost from CYBER SPECTRUM 🩵
🤿 Here are this week's five freeCodeCamp resources that are worth your time 🤿
1. freeCodeCamp just published a comprehensive Python for Beginners course, taught by software engineer Dave Gray. You'll learn key Python concepts by building a series of mini projects. By the end of this course, you'll be familiar with Python Data Types, Loops, Modules, and even some Object-Oriented Programming. If you want to learn programming, or brush up on your fundamental skills, this course is an excellent place to start. (9 hour YouTube course): https://www.freecodecamp.org/news/ultimate-beginners-python-course/
2. Learn to build your own AI Software-as-a-Service platform. In this intermediate course, you'll code an app where your users can drag in a PDF and immediately start chatting with an AI about the document. Along the way, you'll learn how to use Next.js, Tailwind CSS, and OpenAI's API, and Stripe's API. And you'll even learn how to deploy your app using Vercel. (4 hour YouTube course): https://www.freecodecamp.org/news/build-and-deploy-an-ai-saas-with-paid-subscriptions/
3. And if you want to further improve your Front End Development skills, this course should do the trick. You'll code your own Search Engine-optimized blog, complete with custom fonts, light & dark themes, responsive design, and Markdown-based rendering. You'll learn modern tools like Next.js, Tailwind CSS, and Supabase. (6 hour YouTube course): https://www.freecodecamp.org/news/build-an-seo-optimized-blog-with-next-js
4. One of the most important design decisions you can make is picking the right font. This involves so many style and legibility considerations. But you also want to keep performance in mind. This guide will help you choose the right fonts for your next project, and ensure that they load as quickly as possible for your users. (16 minute read): https://www.freecodecamp.org/news/things-to-consider-when-picking-fonts/
5. People often ask me: what's the best way to get practical experience as a developer? And I answer: contribute to open source projects. But that's easier said than done. Not only do you need to understand a project's codebase, but you also need to familiarize yourself with open source culture. This guide will help you learn how to communicate with project maintainers. That way you can succeed in getting your contributions merged, so you can get your code running in production. (20 minute read): https://www.freecodecamp.org/news/how-to-contribute-to-open-source/
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Share nd support 🤟😉
@new_everything_free 😘
Repost from CYBER SPECTRUM 🩵
🌭 Free Books and Courses to Learn Artificial Intelligence 🌭
#AI
Introduction to AI Free Udacity Course
Introduction to Prolog programming for artificial intelligence Free Book
Introduction to AI for Business Free Course
Artificial Intelligence: Foundations of Computational Agents Free Book
Learn Basics about AI Free Udemy Course
(4.4 Star ratings out of 5)
Amazing AI Reverse Image Search
(4.7 Star ratings out of 5)
━━━━━━#Free_Course━━━━━━━
Share nd support 🤟😉
@new_everything_free 😘
30-day Roadmap plan for SQL covers beginner, intermediate, and advanced topics 😄👇
FREE SQL Guide: https://t.me/sqlanalyst/83
Week 1: Beginner Level
Day 1-3: Introduction and Setup
1. Day 1: Introduction to SQL, its importance, and various database systems.
2. Day 2: Installing a SQL database (e.g., MySQL, PostgreSQL).
3. Day 3: Setting up a sample database and practicing basic commands.
Day 4-7: Basic SQL Queries
4. Day 4: SELECT statement, retrieving data from a single table.
5. Day 5: WHERE clause and filtering data.
6. Day 6: Sorting data with ORDER BY.
7. Day 7: Aggregating data with GROUP BY and using aggregate functions (COUNT, SUM, AVG).
Week 2-3: Intermediate Level
Day 8-14: Working with Multiple Tables
8. Day 8: Introduction to JOIN operations.
9. Day 9: INNER JOIN and LEFT JOIN.
10. Day 10: RIGHT JOIN and FULL JOIN.
11. Day 11: Subqueries and correlated subqueries.
12. Day 12: Creating and modifying tables with CREATE, ALTER, and DROP.
13. Day 13: INSERT, UPDATE, and DELETE statements.
14. Day 14: Understanding indexes and optimizing queries.
Day 15-21: Data Manipulation
15. Day 15: CASE statements for conditional logic.
16. Day 16: Using UNION and UNION ALL.
17. Day 17: Data type conversions (CAST and CONVERT).
18. Day 18: Working with date and time functions.
19. Day 19: String manipulation functions.
20. Day 20: Error handling with TRY...CATCH.
21. Day 21: Practice complex queries and data manipulation tasks.
Week 4: Advanced Level
Day 22-28: Advanced Topics
22. Day 22: Working with Views.
23. Day 23: Stored Procedures and Functions.
24. Day 24: Triggers and transactions.
25. Day 25: Security and user privileges.
26. Day 26: Performance tuning and query optimization.
27. Day 27: Introduction to NoSQL databases (optional).
28. Day 28: Working with NoSQL databases (optional).
Day 29-30: Real-World Applications
29. Day 29: Building a simple application that uses SQL.
30. Day 30: Final review and practice, explore advanced topics in depth, or work on a personal project.
Remember to practice regularly, work on small projects, and use online resources and SQL platforms for hands-on experience. Adjust the plan based on your progress and interests, and you'll be well on your way to becoming proficient in SQL!
Share with credits: https://t.me/sqlspecialist
Hope it helps :)
SQL for Data Analysis
SQL Guide
Free Datasets to practice data science projects
1. Enron Email Dataset
Data Link: https://www.cs.cmu.edu/~enron/
2. Chatbot Intents Dataset
Data Link: https://github.com/katanaml/katana-assistant/blob/master/mlbackend/intents.json
3. Flickr 30k Dataset
Data Link: https://www.kaggle.com/hsankesara/flickr-image-dataset
4. Parkinson Dataset
Data Link: https://archive.ics.uci.edu/ml/datasets/parkinsons
5. Iris Dataset
Data Link: https://archive.ics.uci.edu/ml/datasets/Iris
6. ImageNet dataset
Data Link: http://www.image-net.org/
7. Mall Customers Dataset
Data Link: https://www.kaggle.com/shwetabh123/mall-customers
8. Google Trends Data Portal
Data Link: https://trends.google.com/trends/
9. The Boston Housing Dataset
Data Link: https://www.cs.toronto.edu/~delve/data/boston/bostonDetail.html
10. Uber Pickups Dataset
Data Link: https://www.kaggle.com/fivethirtyeight/uber-pickups-in-new-york-city
11. Recommender Systems Dataset
Data Link: https://cseweb.ucsd.edu/~jmcauley/datasets.html
Source Code: https://bit.ly/37iBDEp
12. UCI Spambase Dataset
Data Link: https://archive.ics.uci.edu/ml/datasets/Spambase
13. GTSRB (German traffic sign recognition benchmark) Dataset
Data Link: http://benchmark.ini.rub.de/?section=gtsrb&subsection=dataset
Source Code: https://bit.ly/39taSyH
14. Cityscapes Dataset
Data Link: https://www.cityscapes-dataset.com/
15. Kinetics Dataset
Data Link: https://deepmind.com/research/open-source/kinetics
16. IMDB-Wiki dataset
Data Link: https://data.vision.ee.ethz.ch/cvl/rrothe/imdb-wiki/
17. Color Detection Dataset
Data Link: https://github.com/codebrainz/color-names/blob/master/output/colors.csv
18. Urban Sound 8K dataset
Data Link: https://urbansounddataset.weebly.com/urbansound8k.html
19. Librispeech Dataset
Data Link: http://www.openslr.org/12
20. Breast Histopathology Images Dataset
Data Link: https://www.kaggle.com/paultimothymooney/breast-histopathology-images
21. Youtube 8M Dataset
Data Link: https://research.google.com/youtube8m/
katana-assistant/mlbackend/intents.json at master · katanaml/katana-assistant
Text based assistant powered by Machine Learning and NLP - katanaml/katana-assistant
Top Platforms for Building Data Science Portfolio
Build an irresistible portfolio that hooks recruiters with these free platforms.
Landing a job as a data scientist begins with building your portfolio with a comprehensive list of all your projects. To help you get started with building your portfolio, here is the list of top data science platforms. Remember the stronger your portfolio, the better chances you have of landing your dream job.
1. GitHub
2. Kaggle
3. LinkedIn
4. Medium
5. MachineHack
6. DagsHub
7. HuggingFace
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Top Platforms for Building Data Science Portfolio
Build an irresistible portfolio that hooks recruiters with these free platforms.
Landing a job as a data scientist begins with building your portfolio with a comprehensive list of all your projects. To help you get started with building your portfolio, here is the list of top data science platforms. Remember the stronger your portfolio, the better chances you have of landing your dream job.
1. GitHub
2. Kaggle
3. LinkedIn
4. Medium
5. MachineHack
6. DagsHub
7. HuggingFace
Фото недоступноПоказать в Telegram
AI for beginners
https://t.co/eUddKb3Ftp
IOT
https://t.co/zj4Eiu82ZK
Machine Learning
https://t.co/XNl4P1GtJn
Data Science
https://t.co/JPasEGBo5O