You don’t need another course.

You need more action.

Stop learning, start doing.

10 Ways to Speed Up Your Python Code

1. List Comprehensions
numbers = [x**2 for x in range(100000) if x % 2 == 0]
instead of
numbers = []
for x in range(100000):
if x % 2 == 0:
numbers.append(x**2)

2. Use the Built-In Functions
Many of Python’s built-in functions are written in C, which makes them much faster than a pure python solution.

3. Function Calls Are Expensive
Function calls are expensive in Python. While it is often good practice to separate code into functions, there are times where you should be cautious about calling functions from inside of a loop. It is better to iterate inside a function than to iterate and call a function each iteration.

4. Lazy Module Importing
If you want to use the time.sleep() function in your code, you don't necessarily need to import the entire time package. Instead, you can just do from time import sleep and avoid the overhead of loading basically everything.

5. Take Advantage of Numpy
Numpy is a highly optimized library built with C. It is almost always faster to offload complex math to Numpy rather than relying on the Python interpreter.

6. Try Multiprocessing
Multiprocessing can bring large performance increases to a Python script, but it can be difficult to implement properly compared to other methods mentioned in this post.

7. Be Careful with Bulky Libraries
One of the advantages Python has over other programming languages is the rich selection of third-party libraries available to developers. But, what we may not always consider is the size of the library we are using as a dependency, which could actually decrease the performance of your Python code.

8. Avoid Global Variables
Python is slightly faster at retrieving local variables than global ones. It is simply best to avoid global variables when possible.

9. Try Multiple Solutions
Being able to solve a problem in multiple ways is nice. But, there is often a solution that is faster than the rest and sometimes it comes down to just using a different method or data structure.

10. Think About Your Data Structures
Searching a dictionary or set is insanely fast, but lists take time proportional to the length of the list. However, sets and dictionaries do not maintain order. If you care about the order of your data, you can’t make use of dictionaries or sets.

Best Programming Resources: https://topmate.io/coding/898340

All the best 👍👍

If you aspire to work in top product companies, here’s my advice:

👉 For SDE-1 or SWE positions, focus on:

✔️ Continuously upskilling and improving your abilities.
✔️ Developing strong problem-solving skills.
✔️Mastering DSA – trust me, you’ll be tested on it, so aim to excel.

Also, learn how to design scalable systems and understand how to build solutions that can handle growth in users and data.

👉 For higher-level roles (SDE-2 and SDE-3), focus on:

✔️ DSA + System Design (both LLD and HLD).
✔️ Building your leadership skills, as you’ll need to lead teams and projects.

🔸I know it’s challenging to do this while working full-time, but you’ll need to carve out time to consistently upskill yourself.

Remember, your learning plan should be sensible and well-organized.

Best Programming Resources: https://topmate.io/coding/886839

ENJOY LEARNING 👍👍

30-day roadmap to learn Java up to an intermediate level.

This roadmap is designed for beginners, so adjust your pace as needed.

Week 1: Java Basics
*Day 1-2:*
- Day 1: Get Java installed on your computer and set up your development environment.
- Day 2: Learn about Java's history, its role in programming, and write your first "Hello, World!" program.

*Day 3-4:*
- Day 3: Study Java syntax, data types, and variables.
- Day 4: Understand operators and perform basic arithmetic operations.

*Day 5-7:*
- Day 5: Explore control flow with if-else statements and loops (for and while).
- Day 6: Dive into switch statements and understand how to handle user choices.
- Day 7: Practice writing small programs that use conditions and loops.

Week 2: Functions and Object-Oriented Programming
*Day 8-9:*
- Day 8: Learn about functions (methods) and how to define your own functions in Java.
- Day 9: Study function parameters, return types, and method overloading.

*Day 10-12:*
- Day 10: Understand the basics of object-oriented programming (OOP) in Java.
- Day 11: Learn about classes, objects, and constructors.
- Day 12: Explore encapsulation, inheritance, and polymorphism.

*Day 13-14:*
- Day 13: Study Java packages and access modifiers (public, private, protected).
- Day 14: Practice creating classes and objects in real-world scenarios.

Week 3: Data Structures and Collections
*Day 15-17:*
- Day 15: Dive into arrays in Java and understand their usage.
- Day 16: Study Java's collection framework and ArrayList.
- Day 17: Learn about iterating through collections using loops and iterators.

*Day 18-19:*
- Day 18: Explore other collection types like LinkedList and HashMap.
- Day 19: Understand when to use different collection types in Java.

*Day 20-21:*
- Day 20: Study exception handling in Java and how to deal with errors.
- Day 21: Practice working with try-catch blocks and handling exceptions effectively.

Week 4: Intermediate Topics and Projects
*Day 22-23:*
- Day 22: Study file handling in Java, including reading and writing files.
- Day 23: Create a small project that involves file operations.

*Day 24-26:*
- Day 24: Learn about multithreading and how to create and manage threads in Java.
- Day 25: Study Java's built-in libraries for networking and socket programming.
- Day 26: Work on a project that involves multithreading or networking.

*Day 27-28:*
- Day 27: Explore more advanced Java topics like JavaFX for GUI development or JDBC for database connectivity.
- Day 28: Work on a more complex project that combines your knowledge from the past weeks.

*Day 29-30:*
- Day 29: Review and revisit any topics you found challenging.
- Day 30: Continue building projects and exploring areas of Java that interest you.

Consider joining Java communities and forums to seek help and advice. Java is a versatile language with many applications, so your learning journey can continue well beyond this roadmap. Good luck!

Beginner’s Roadmap to Learn Data Structures & Algorithms

1. Foundations: Start with the basics of programming and mathematical concepts to build a strong foundation.

2. Data Structure: Dive into essential data structures like arrays, linked lists, stacks, and queues to organise and store data efficiently.

3. Searching & Sorting: Learn various search and sort techniques to optimise data retrieval and organisation.

4. Trees & Graphs: Understand the concepts of binary trees and graph representation to tackle complex hierarchical data.

5. Recursion: Grasp the principles of recursion and how to implement recursive algorithms for problem-solving.

6. Advanced Data Structures: Explore advanced structures like hashing, heaps, and hash maps to enhance data manipulation.

7. Algorithms: Master algorithms such as greedy, divide and conquer, and dynamic programming to solve intricate problems.

8. Advanced Topics: Delve into backtracking, string algorithms, and bit manipulation for a deeper understanding.

9. Problem Solving: Practice on coding platforms like LeetCode to sharpen your skills and solve real-world algorithmic challenges.

10. Projects & Portfolio: Build real-world projects and showcase your skills on GitHub to create an impressive portfolio.

Best DSA RESOURCES: https://topmate.io/coding/886874

All the best 👍👍

Here's a good list of cheat sheets for programmers (all free):

Data Science Cheatsheet

https://github.com/aaronwangy/Data-Science-Cheatsheet

SQL Cheatsheet

sqltutorial.org/sql-cheat-sheet

t.iss.one/sqlspecialist/827

https://www.sqltutorial.org/wp-content/uploads/2016/04/SQL-cheat-sheet.pdf

Java Programming Cheatsheet

https://introcs.cs.princeton.edu/java/11cheatsheet/

Javascript Cheatsheet

quickref.me/javascript.html

t.iss.one/javascript_courses/532

Data Analytics Cheatsheets

https://dataanalytics.beehiiv.com/p/data

Python Cheat sheet

quickref.me/python.html

https://t.iss.one/pythondevelopersindia/314

GIT and Machine Learning Cheatsheet

https://t.iss.one/datasciencefun/714

HTML Cheatsheet

https://web.stanford.edu/group/csp/cs21/htmlcheatsheet.pdf

htmlcheatsheet.com

CSS Cheatsheet

htmlcheatsheet.com/css

jQuery Cheatsheet

t.iss.one/webdevelopmentbook/90

Data Visualization
t.iss.one/datasciencefun/698

Free entry to our WhatsApp channel

Join @free4unow_backup for more free resources

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ENJOY LEARNING👍👍

Sample email template to reach out to HR’s as fresher

Hi Jasneet,

I recently came across your LinkedIn post seeking a React.js developer intern, and I am writing to express my interest in the position at Airtel. As a recent graduate, I am eager to begin my career and am excited about the opportunity.

I am a quick learner and have developed a strong set of dynamic and user-friendly web applications using various technologies, including HTML, CSS, JavaScript, Bootstrap, React.js, Vue.js, PHP, and MySQL. I am also well-versed in creating reusable components, implementing responsive designs, and ensuring cross-browser compatibility.

I am confident that my eagerness to learn and strong work ethic will make me an asset to your team.

I have attached my resume for your review. Thank you for considering my application. I look forward to hearing from you soon.

Thanks!

I hope you will found this helpful 🙂

https://topmate.io/coding/898340

If you're a job seeker, these well structured resources will help you to know and learn all the real time Python Interview questions with their exact answer. Folks who are having 0-4 years of experience have cracked the interview using this guide!

Please use the above link to avail them!👆

NOTE: -Most data aspirants hoard resources without actually opening them even once! The reason for keeping a small price for these resources is to ensure that you value the content available inside this and encourage you to make the best out of it.

Hope this helps in your job search journey... All the best!👍✌️

How can you stand out as a software engineer?

Learn the skills that others avoid:

• Learn unit testing.
• Learn CI/CD pipelines.
• Learn automation tools.
• Learn performance tuning.
• Learn security best practices.
• Learn effective branching strategies.
• Learn cloud infrastructure management.

Most fall short here.

Free Resources to learn C & C++ Programming
👇👇

Fundamentals of Programming Languages Free Udacity course

https://imp.i115008.net/5bmnKL

C++ for Programmers Free Udacity Course

https://imp.i115008.net/kjoq9V

C++ Tutorial for Complete Beginners Free Udemy Course

https://bit.ly/3yDNoCV

C Programming documentation from Microsoft

https://docs.microsoft.com/en-us/cpp/c-language/?view=msvc-170&viewFallbackFrom=vs-2019

C Programming Free Book

https://books.goalkicker.com/CBook/CNotesForProfessionals.pdf

C++ Notes for Professional

https://books.goalkicker.com/CPlusPlusBook/CPlusPlusNotesForProfessionals.pdf

Join @free4unow_backup for more free courses

ENJOY LEARNING 👍👍

👉🏻 DO REACT IF YOU WANT MORE JOBS & INTERNSHIP OPPORTUNITIES LIKE THIS

👉🏻 DO REACT IF YOU WANT MORE RESOURCES LIKE THIS FOR 🆓

Don't overwhelm to learn Git,🙌

Git is only this much👇😇

1.Core:
• git init
• git clone
• git add
• git commit
• git status
• git diff
• git checkout
• git reset
• git log
• git show
• git tag
• git push
• git pull

2.Branching:
• git branch
• git checkout -b
• git merge
• git rebase
• git branch --set-upstream-to
• git branch --unset-upstream
• git cherry-pick

3.Merging:
• git merge
• git rebase

4.Stashing:
• git stash
• git stash pop
• git stash list
• git stash apply
• git stash drop

5.Remotes:
• git remote
• git remote add
• git remote remove
• git fetch
• git pull
• git push
• git clone --mirror

6.Configuration:
• git config
• git global config
• git reset config

7. Plumbing:
• git cat-file
• git checkout-index
• git commit-tree
• git diff-tree
• git for-each-ref
• git hash-object
• git ls-files
• git ls-remote
• git merge-tree
• git read-tree
• git rev-parse
• git show-branch
• git show-ref
• git symbolic-ref
• git tag --list
• git update-ref

8.Porcelain:
• git blame
• git bisect
• git checkout
• git commit
• git diff
• git fetch
• git grep
• git log
• git merge
• git push
• git rebase
• git reset
• git show
• git tag

9.Alias:
• git config --global alias.<alias> <command>

10.Hook:
• git config --local core.hooksPath <path>

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Essential Tools & Programming Languages for Software Developers

👉 Integrated Development Environments (IDEs):
- Visual Studio Code: A lightweight but powerful source code editor that supports various programming languages and extensions.
- IntelliJ IDEA: A popular IDE for Java development, also supporting other languages through plugins.
- Eclipse: Another widely used IDE for Java, with extensive plugin support for other languages.

👉 Version Control Systems:
- Git: A distributed version control system that allows developers to track changes in their codebase, collaborate with others, and manage project history. GitHub, GitLab, and Bitbucket are popular platforms that use Git.

👉 Programming Languages:
- JavaScript: Essential for web development, with frameworks like React, Angular, and Vue.js for front-end development and Node.js for server-side programming.
- Python: Known for its simplicity and versatility, used in web development (Django, Flask), data science (NumPy, Pandas), and automation.
- Java: Widely used for building enterprise-scale applications, Android app development, and backend systems.
- C#: A language developed by Microsoft, primarily used for building Windows applications and games using the Unity engine.
- C++: Known for its performance, used in system/software development, game development, and applications requiring real-time processing.
- Ruby: Known for its simplicity and productivity, often used in web development with the Ruby on Rails framework.

👉 Web Development Frameworks:
- React: A JavaScript library for building user interfaces, particularly single-page applications.
- Angular: A TypeScript-based framework for building dynamic web applications.
- Django: A high-level Python web framework that encourages rapid development and clean, pragmatic design.
- Spring: A comprehensive framework for Java that provides infrastructure support for developing Java applications.

👉 Database Management Systems:
- MySQL: An open-source relational database management system.
- PostgreSQL: An open-source object-relational database system with a strong emphasis on extensibility and standards compliance.
- MongoDB: A NoSQL database that uses a flexible, JSON-like format for storing data.

👉 Containerization and Orchestration:
- Docker: A platform that allows developers to package applications into containers, ensuring consistency across multiple environments.
- Kubernetes: An open-source system for automating deployment, scaling, and management of containerized applications.

👉 Cloud Platforms:
- Amazon Web Services (AWS): A comprehensive cloud platform offering a wide range of services, including computing power, storage, and databases.
- Microsoft Azure: A cloud computing service created by Microsoft for building, testing, deploying, and managing applications.
- Google Cloud Platform (GCP): A suite of cloud computing services provided by Google.

👉 CI/CD Tools:
- Jenkins: An open-source automation server that helps automate the parts of software development related to building, testing, and deploying.
- Travis CI: A continuous integration service used to build and test software projects hosted on GitHub.

👉 Project Management and Collaboration:
- Jira: A tool developed by Atlassian for bug tracking, issue tracking, and project management.
- Trello: A visual tool for organizing tasks and projects into boards.

Programming & Data Analytics Resources: https://t.iss.one/free4unow_backup/796

Best Programming Resources: https://topmate.io/coding/886839

Join @free4unow_backup for more free courses

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ENJOY LEARNING👍👍

AI/ML (Daily Schedule) 👨🏻‍💻

Morning:
- 9:00 AM - 10:30 AM: ML Algorithms Practice
- 10:30 AM - 11:00 AM: Break
- 11:00 AM - 12:30 PM: AI/ML Theory Study

Lunch:
- 12:30 PM - 1:30 PM: Lunch and Rest

Afternoon:
- 1:30 PM - 3:00 PM: Project Development
- 3:00 PM - 3:30 PM: Break
- 3:30 PM - 5:00 PM: Model Training/Testing

Evening:
- 5:00 PM - 6:00 PM: Review and Debug
- 6:00 PM - 7:00 PM: Dinner and Rest

Late Evening:
- 7:00 PM - 8:00 PM: Research and Reading
- 8:00 PM - 9:00 PM: Reflect and Plan

Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624

ENJOY LEARNING 👍👍

If I were to start Computer Science in 2024,

- Harvard - Stanford
- MIT - IBM - Telegram
- Microsoft - Google

❯ CS50 from Harvard
https://cs50.harvard.edu/x/2023/certificate/

❯ C/C++
https://ocw.mit.edu/courses/6-s096-effective-programming-in-c-and-c-january-iap-2014/

❯ Python
https://cs50.harvard.edu/python/2022/

https://t.iss.one/dsabooks

❯ SQL
https://online.stanford.edu/courses/soe-ydatabases0005-databases-relational-databases-and-sql

https://t.iss.one/sqlanalyst

❯ DSA
https://techdevguide.withgoogle.com/paths/data-structures-and-algorithms/

https://t.iss.one/crackingthecodinginterview/290

❯ Java
https://learn.microsoft.com/shows/java-for-beginners/

https://t.iss.one/Java_Programming_Notes

❯ JavaScript
https://learn.microsoft.com/training/paths/web-development-101/

https://t.iss.one/javascript_courses

❯ TypeScript
https://learn.microsoft.com/training/paths/build-javascript-applications-typescript/

❯ C#
https://learn.microsoft.com/users/dotnet/collections/yz26f8y64n7k07

❯ Mathematics (incl. Statistics)
ocw.mit.edu/search/?d=Mathematics&s=department_course_numbers.sort_coursenum

❯ Data Science
cognitiveclass.ai/courses/data-science-101

https://t.iss.one/datasciencefun/1141

❯ Machine Learning
https://developers.google.com/machine-learning/crash-course

❯ Deep Learning
introtodeeplearning.com

t.iss.one/machinelearning_deeplearning/

❯ Full Stack Web (HTML/CSS)
pll.harvard.edu/course/cs50s-web-programming-python-and-javascript/2023-05

t.iss.one/webdevcoursefree/594

❯ OS, Networking
ocw.mit.edu/courses/6-033-computer-system-engineering-spring-2018/

❯ Compiler Design
online.stanford.edu/courses/soe-ycscs1-compilers

Please give us credits while sharing: -> https://t.iss.one/free4unow_backup

ENJOY LEARNING 👍👍

𝗧𝗼𝗽 𝟭𝟭 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗶𝗻 2025 🧑‍💻:

1. Java
2. JavaScript
3. Python
4. C++
5. Swift
6. Golang (Go)
7. Kotlin
8. Rust
9. TypeScript
10. PHP
11. Ruby