Guys, Big Announcement!
We’ve officially hit 5 Lakh followers on WhatsApp and it’s time to level up together! ❤️
I've launched a Python Learning Series — designed for beginners to those preparing for technical interviews or building real-world projects.
This will be a step-by-step journey — from basics to advanced — with real examples and short quizzes after each topic to help you lock in the concepts.
Here’s what we’ll cover in the coming days:
Week 1: Python Fundamentals
- Variables & Data Types
- Operators & Expressions
- Conditional Statements (if, elif, else)
- Loops (for, while)
- Functions & Parameters
- Input/Output & Basic Formatting
Week 2: Core Python Skills
- Lists, Tuples, Sets, Dictionaries
- String Manipulation
- List Comprehensions
- File Handling
- Exception Handling
Week 3: Intermediate Python
- Lambda Functions
- Map, Filter, Reduce
- Modules & Packages
- Scope & Global Variables
- Working with Dates & Time
Week 4: OOP & Pythonic Concepts
- Classes & Objects
- Inheritance & Polymorphism
- Decorators (Intro level)
- Generators & Iterators
- Writing Clean & Readable Code
Week 5: Real-World & Interview Prep
- Web Scraping (BeautifulSoup)
- Working with APIs (Requests)
- Automating Tasks
- Data Analysis Basics (Pandas)
- Interview Coding Patterns
You can join our WhatsApp channel to access it for free: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1527
We’ve officially hit 5 Lakh followers on WhatsApp and it’s time to level up together! ❤️
I've launched a Python Learning Series — designed for beginners to those preparing for technical interviews or building real-world projects.
This will be a step-by-step journey — from basics to advanced — with real examples and short quizzes after each topic to help you lock in the concepts.
Here’s what we’ll cover in the coming days:
Week 1: Python Fundamentals
- Variables & Data Types
- Operators & Expressions
- Conditional Statements (if, elif, else)
- Loops (for, while)
- Functions & Parameters
- Input/Output & Basic Formatting
Week 2: Core Python Skills
- Lists, Tuples, Sets, Dictionaries
- String Manipulation
- List Comprehensions
- File Handling
- Exception Handling
Week 3: Intermediate Python
- Lambda Functions
- Map, Filter, Reduce
- Modules & Packages
- Scope & Global Variables
- Working with Dates & Time
Week 4: OOP & Pythonic Concepts
- Classes & Objects
- Inheritance & Polymorphism
- Decorators (Intro level)
- Generators & Iterators
- Writing Clean & Readable Code
Week 5: Real-World & Interview Prep
- Web Scraping (BeautifulSoup)
- Working with APIs (Requests)
- Automating Tasks
- Data Analysis Basics (Pandas)
- Interview Coding Patterns
You can join our WhatsApp channel to access it for free: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L/1527
👍2
Forwarded from Data Analysis Books | Python | SQL | Excel | Artificial Intelligence | Power BI | Tableau | AI Resources
𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗙𝗥𝗘𝗘 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍
Whether you’re a student, fresher, or professional looking to upskill — Microsoft has dropped a series of completely free courses to get you started.
Learn SQL ,Power BI & More In 2025
𝗟𝗶𝗻𝗸:-👇
https://pdlink.in/42FxnyM
Enroll For FREE & Get Certified 🎓
Whether you’re a student, fresher, or professional looking to upskill — Microsoft has dropped a series of completely free courses to get you started.
Learn SQL ,Power BI & More In 2025
𝗟𝗶𝗻𝗸:-👇
https://pdlink.in/42FxnyM
Enroll For FREE & Get Certified 🎓
👍3
COMMON TERMINOLOGIES IN PYTHON - PART 1
Have you ever gotten into a discussion with a programmer before? Did you find some of the Terminologies mentioned strange or you didn't fully understand them?
In this series, we would be looking at the common Terminologies in python.
It is important to know these Terminologies to be able to professionally/properly explain your codes to people and/or to be able to understand what people say in an instant when these codes are mentioned. Below are a few:
IDLE (Integrated Development and Learning Environment) - this is an environment that allows you to easily write Python code. IDLE can be used to execute a single statements and create, modify, and execute Python scripts.
Python Shell - This is the interactive environment that allows you to type in python code and execute them immediately
System Python - This is the version of python that comes with your operating system
Prompt - usually represented by the symbol ">>>" and it simply means that python is waiting for you to give it some instructions
REPL (Read-Evaluate-Print-Loop) - this refers to the sequence of events in your interactive window in form of a loop (python reads the code inputted>the code is evaluated>output is printed)
Argument - this is a value that is passed to a function when called eg print("Hello World")... "Hello World" is the argument that is being passed.
Function - this is a code that takes some input, known as arguments, processes that input and produces an output called a return value. E.g print("Hello World")... print is the function
Return Value - this is the value that a function returns to the calling script or function when it completes its task (in other words, Output). E.g.
>>> print("Hello World")
Hello World
Where Hello World is your return value.
Note: A return value can be any of these variable types: handle, integer, object, or string
Script - This is a file where you store your python code in a text file and execute all of the code with a single command
Script files - this is a file containing a group of python scripts
Have you ever gotten into a discussion with a programmer before? Did you find some of the Terminologies mentioned strange or you didn't fully understand them?
In this series, we would be looking at the common Terminologies in python.
It is important to know these Terminologies to be able to professionally/properly explain your codes to people and/or to be able to understand what people say in an instant when these codes are mentioned. Below are a few:
IDLE (Integrated Development and Learning Environment) - this is an environment that allows you to easily write Python code. IDLE can be used to execute a single statements and create, modify, and execute Python scripts.
Python Shell - This is the interactive environment that allows you to type in python code and execute them immediately
System Python - This is the version of python that comes with your operating system
Prompt - usually represented by the symbol ">>>" and it simply means that python is waiting for you to give it some instructions
REPL (Read-Evaluate-Print-Loop) - this refers to the sequence of events in your interactive window in form of a loop (python reads the code inputted>the code is evaluated>output is printed)
Argument - this is a value that is passed to a function when called eg print("Hello World")... "Hello World" is the argument that is being passed.
Function - this is a code that takes some input, known as arguments, processes that input and produces an output called a return value. E.g print("Hello World")... print is the function
Return Value - this is the value that a function returns to the calling script or function when it completes its task (in other words, Output). E.g.
>>> print("Hello World")
Hello World
Where Hello World is your return value.
Note: A return value can be any of these variable types: handle, integer, object, or string
Script - This is a file where you store your python code in a text file and execute all of the code with a single command
Script files - this is a file containing a group of python scripts
👍3
𝟯 𝗙𝗿𝗲𝗲 𝗧𝗖𝗦 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗘𝘃𝗲𝗿𝘆 𝗙𝗿𝗲𝘀𝗵𝗲𝗿 𝗠𝘂𝘀𝘁 𝗧𝗮𝗸𝗲 𝘁𝗼 𝗚𝗲𝘁 𝗝𝗼𝗯-𝗥𝗲𝗮𝗱𝘆😍
🎯 If You’re a Fresher, These TCS Courses Are a Must-Do📄✔️
Stepping into the job market can be overwhelming—but what if you had certified, expert-backed training that actually prepares you?👨🎓✨️
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/42Nd9Do
Don’t wait. Get certified, get confident, and get closer to landing your first job✅️
🎯 If You’re a Fresher, These TCS Courses Are a Must-Do📄✔️
Stepping into the job market can be overwhelming—but what if you had certified, expert-backed training that actually prepares you?👨🎓✨️
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/42Nd9Do
Don’t wait. Get certified, get confident, and get closer to landing your first job✅️
Python Roadmap for 2025: Complete Guide
1. Python Fundamentals
1.1 Variables, constants, and comments.
1.2 Data types: int, float, str, bool, complex.
1.3 Input and output (input(), print(), formatted strings).
1.4 Python syntax: Indentation and code structure.
2. Operators
2.1 Arithmetic: +, -, *, /, %, //, **.
2.2 Comparison: ==, !=, <, >, <=, >=.
2.3 Logical: and, or, not.
2.4 Bitwise: &, |, ^, ~, <<, >>.
2.5 Identity: is, is not.
2.6 Membership: in, not in.
3. Control Flow
3.1 Conditional statements: if, elif, else.
3.2 Loops: for, while.
3.3 Loop control: break, continue, pass.
4. Data Structures
4.1 Lists: Indexing, slicing, methods (append(), pop(), sort(), etc.).
4.2 Tuples: Immutability, packing/unpacking.
4.3 Dictionaries: Key-value pairs, methods (get(), items(), etc.).
4.4 Sets: Unique elements, set operations (union, intersection).
4.5 Strings: Immutability, methods (split(), strip(), replace()).
5. Functions
5.1 Defining functions with def.
5.2 Arguments: Positional, keyword, default, *args, **kwargs.
5.3 Anonymous functions (lambda).
5.4 Recursion.
6. Modules and Packages
6.1 Importing: import, from ... import.
6.2 Standard libraries: math, os, sys, random, datetime, time.
6.3 Installing external libraries with pip.
7. File Handling
7.1 Open and close files (open(), close()).
7.2 Read and write (read(), write(), readlines()).
7.3 Using context managers (with open(...)).
8. Object-Oriented Programming (OOP)
8.1 Classes and objects.
8.2 Methods and attributes.
8.3 Constructor (init).
8.4 Inheritance, polymorphism, encapsulation.
8.5 Special methods (str, repr, etc.).
9. Error and Exception Handling
9.1 try, except, else, finally.
9.2 Raising exceptions (raise).
9.3 Custom exceptions.
10. Comprehensions
10.1 List comprehensions.
10.2 Dictionary comprehensions.
10.3 Set comprehensions.
11. Iterators and Generators
11.1 Creating iterators using iter() and next().
11.2 Generators with yield.
11.3 Generator expressions.
12. Decorators and Closures
12.1 Functions as first-class citizens.
12.2 Nested functions.
12.3 Closures.
12.4 Creating and applying decorators.
13. Advanced Topics
13.1 Context managers (with statement).
13.2 Multithreading and multiprocessing.
13.3 Asynchronous programming with async and await.
13.4 Python's Global Interpreter Lock (GIL).
14. Python Internals
14.1 Mutable vs immutable objects.
14.2 Memory management and garbage collection.
14.3 Python's name == "main" mechanism.
15. Libraries and Frameworks
15.1 Data Science: NumPy, Pandas, Matplotlib, Seaborn.
15.2 Web Development: Flask, Django, FastAPI.
15.3 Testing: unittest, pytest.
15.4 APIs: requests, http.client.
15.5 Automation: selenium, os.
15.6 Machine Learning: scikit-learn, TensorFlow, PyTorch.
16. Tools and Best Practices
16.1 Debugging: pdb, breakpoints.
16.2 Code style: PEP 8 guidelines.
16.3 Virtual environments: venv.
16.4 Version control: Git + GitHub.
👇 Python Interview 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀
https://t.me/dsabooks
📘 𝗣𝗿𝗲𝗺𝗶𝘂𝗺 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 : https://topmate.io/coding/914624
📙 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲: https://whatsapp.com/channel/0029VaxbzNFCxoAmYgiGTL3Z
Join What's app channel for jobs updates: t.me/getjobss
1. Python Fundamentals
1.1 Variables, constants, and comments.
1.2 Data types: int, float, str, bool, complex.
1.3 Input and output (input(), print(), formatted strings).
1.4 Python syntax: Indentation and code structure.
2. Operators
2.1 Arithmetic: +, -, *, /, %, //, **.
2.2 Comparison: ==, !=, <, >, <=, >=.
2.3 Logical: and, or, not.
2.4 Bitwise: &, |, ^, ~, <<, >>.
2.5 Identity: is, is not.
2.6 Membership: in, not in.
3. Control Flow
3.1 Conditional statements: if, elif, else.
3.2 Loops: for, while.
3.3 Loop control: break, continue, pass.
4. Data Structures
4.1 Lists: Indexing, slicing, methods (append(), pop(), sort(), etc.).
4.2 Tuples: Immutability, packing/unpacking.
4.3 Dictionaries: Key-value pairs, methods (get(), items(), etc.).
4.4 Sets: Unique elements, set operations (union, intersection).
4.5 Strings: Immutability, methods (split(), strip(), replace()).
5. Functions
5.1 Defining functions with def.
5.2 Arguments: Positional, keyword, default, *args, **kwargs.
5.3 Anonymous functions (lambda).
5.4 Recursion.
6. Modules and Packages
6.1 Importing: import, from ... import.
6.2 Standard libraries: math, os, sys, random, datetime, time.
6.3 Installing external libraries with pip.
7. File Handling
7.1 Open and close files (open(), close()).
7.2 Read and write (read(), write(), readlines()).
7.3 Using context managers (with open(...)).
8. Object-Oriented Programming (OOP)
8.1 Classes and objects.
8.2 Methods and attributes.
8.3 Constructor (init).
8.4 Inheritance, polymorphism, encapsulation.
8.5 Special methods (str, repr, etc.).
9. Error and Exception Handling
9.1 try, except, else, finally.
9.2 Raising exceptions (raise).
9.3 Custom exceptions.
10. Comprehensions
10.1 List comprehensions.
10.2 Dictionary comprehensions.
10.3 Set comprehensions.
11. Iterators and Generators
11.1 Creating iterators using iter() and next().
11.2 Generators with yield.
11.3 Generator expressions.
12. Decorators and Closures
12.1 Functions as first-class citizens.
12.2 Nested functions.
12.3 Closures.
12.4 Creating and applying decorators.
13. Advanced Topics
13.1 Context managers (with statement).
13.2 Multithreading and multiprocessing.
13.3 Asynchronous programming with async and await.
13.4 Python's Global Interpreter Lock (GIL).
14. Python Internals
14.1 Mutable vs immutable objects.
14.2 Memory management and garbage collection.
14.3 Python's name == "main" mechanism.
15. Libraries and Frameworks
15.1 Data Science: NumPy, Pandas, Matplotlib, Seaborn.
15.2 Web Development: Flask, Django, FastAPI.
15.3 Testing: unittest, pytest.
15.4 APIs: requests, http.client.
15.5 Automation: selenium, os.
15.6 Machine Learning: scikit-learn, TensorFlow, PyTorch.
16. Tools and Best Practices
16.1 Debugging: pdb, breakpoints.
16.2 Code style: PEP 8 guidelines.
16.3 Virtual environments: venv.
16.4 Version control: Git + GitHub.
👇 Python Interview 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀
https://t.me/dsabooks
📘 𝗣𝗿𝗲𝗺𝗶𝘂𝗺 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 : https://topmate.io/coding/914624
📙 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲: https://whatsapp.com/channel/0029VaxbzNFCxoAmYgiGTL3Z
Join What's app channel for jobs updates: t.me/getjobss
👍2
Forwarded from Artificial Intelligence
𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲 𝘄𝗶𝘁𝗵 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗲 𝗯𝘆 𝗚𝗼𝗼𝗴𝗹𝗲 – 𝗟𝗲𝗮𝗿𝗻 𝗣𝘆𝘁𝗵𝗼𝗻 𝗳𝗼𝗿 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀😍
If you’re starting your journey into data analytics, Python is the first skill you need to master👨🎓
A free, beginner-friendly course by Google on Kaggle, designed to take you from zero to data-ready with hands-on coding practice👨💻📝
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/4k24zGl
Just start coding right in your browser✅️
If you’re starting your journey into data analytics, Python is the first skill you need to master👨🎓
A free, beginner-friendly course by Google on Kaggle, designed to take you from zero to data-ready with hands-on coding practice👨💻📝
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/4k24zGl
Just start coding right in your browser✅️
What for what?
🖼️ Frontend
HTML + CSS
Javascript
React
VueJs
Angular
Svelte
🔙 Backend:
Nodejs/Express
Python/Django
PHP/Laravel
Java
C#
💽 Database
MongoDB
MySQL
Postgres
Redis
🖥️ Desktop
Electron
Tairi
PyQt
📱Phones:
React Native
Flutter
Swift
Kotlin
🖥️ System
Go
C++
Rust
🖼️ Frontend
HTML + CSS
Javascript
React
VueJs
Angular
Svelte
🔙 Backend:
Nodejs/Express
Python/Django
PHP/Laravel
Java
C#
💽 Database
MongoDB
MySQL
Postgres
Redis
🖥️ Desktop
Electron
Tairi
PyQt
📱Phones:
React Native
Flutter
Swift
Kotlin
🖥️ System
Go
C++
Rust
👍4
𝟱 𝗙𝗿𝗲𝗲 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗬𝗼𝘂 𝗖𝗮𝗻’𝘁 𝗠𝗶𝘀𝘀😍
Microsoft Learn is offering 5 must-do courses for aspiring data scientists, absolutely free🔥📊
These self-paced learning modules are designed by industry experts and cover everything from Python and ML to Microsoft Fabric and Azure🎯
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/4iSWjaP
Job-ready content that gets you results✅️
Microsoft Learn is offering 5 must-do courses for aspiring data scientists, absolutely free🔥📊
These self-paced learning modules are designed by industry experts and cover everything from Python and ML to Microsoft Fabric and Azure🎯
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/4iSWjaP
Job-ready content that gets you results✅️
👍1
Python For Everything!🐍
Python, the versatile language, can be combined with various libraries to build amazing things:🚀
1. Python + Pandas = Data Manipulation
2. Python + Scikit-Learn = Machine Learning
3. Python + TensorFlow = Deep Learning
4. Python + Matplotlib = Data Visualization
5. Python + Seaborn = Advanced Visualization
6. Python + Flask = Web Development
7. Python + Pygame = Game Development
8. Python + Kivy = Mobile App Development
#Python
Python, the versatile language, can be combined with various libraries to build amazing things:🚀
1. Python + Pandas = Data Manipulation
2. Python + Scikit-Learn = Machine Learning
3. Python + TensorFlow = Deep Learning
4. Python + Matplotlib = Data Visualization
5. Python + Seaborn = Advanced Visualization
6. Python + Flask = Web Development
7. Python + Pygame = Game Development
8. Python + Kivy = Mobile App Development
#Python
👍3
Forwarded from Artificial Intelligence
𝗕𝗼𝗼𝘀𝘁 𝗬𝗼𝘂𝗿 𝗦𝗸𝗶𝗹𝗹𝘀 𝘄𝗶𝘁𝗵 𝗧𝗵𝗲𝘀𝗲 𝗙𝗿𝗲𝗲 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀😍
Ready to take your career to the next level?📊📌
These free certification courses offer a golden opportunity to build expertise in tech, programming, AI, and more—all for free!🔥💻
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/4gPNbDc
These courses are your stepping stones to success✅️
Ready to take your career to the next level?📊📌
These free certification courses offer a golden opportunity to build expertise in tech, programming, AI, and more—all for free!🔥💻
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/4gPNbDc
These courses are your stepping stones to success✅️
🔟 unique web development project ideas for freshers
1. Freelance Client Management System:
Build a system for freelancers to track client details, project timelines, invoices, and payments. Incorporate features like task lists, payment reminders, and time tracking. You’ll get hands-on experience with CRUD operations and secure user authentication.
2. Nonprofit Donation Platform:
Develop a platform for nonprofit organizations where users can donate to causes. You can include a donation tracker, goal setting, and integration with payment gateways like Stripe or PayPal. This will involve front-end design and server-side payment processing.
3. Interactive Educational Platform for Kids:
Create a platform where kids can learn basic subjects like math, spelling, or coding through fun, interactive games. Add features like badges, scoreboards, and quizzes to keep them engaged. This will give you experience in animations, gamification, and user experience design.
4. Real Estate Listings Website:
Build a platform where agents or homeowners can list properties for rent or sale. Include features like advanced search, map integration, and filters for property type, price, and location. You’ll get exposure to working with APIs and map services like Google Maps.
5. Virtual Art Gallery:
Design a virtual space where artists can display their work. Use animations to simulate a walk-through gallery, allowing users to explore and click on individual pieces for more details. You’ll explore 3D rendering, animations, and responsive design in this project.
6. Job Application Tracker:
Help job seekers keep track of job applications by building a dashboard that organizes companies, positions, interview stages, and deadlines. This app could send automated reminders for follow-ups, giving you experience with notifications and task scheduling.
7. Music Streaming Player:
Develop a personalized music player where users can create and share playlists. Integrate it with a music API like Spotify or Apple Music to pull in tracks. This project will introduce you to audio streaming, user authentication, and data storage for playlists.
8. Mental Health Tracker:
Create a web app where users can log daily moods, set mental health goals, and track progress over time. Incorporate features like journaling, breathing exercises, and visual data charts. This would involve data collection, chart visualization, and user interface design.
9. Sustainable Shopping Guide:
Build a platform where users can discover eco-friendly products and businesses. You can integrate a rating system for users to rate brands on sustainability practices. The project will teach you about APIs, user-generated content, and social proof.
10. Virtual Study Group App:
Create an app where students can join or form virtual study groups, chat in real-time, and share resources like notes and flashcards. You can add video integration or virtual whiteboards to make the platform more collaborative. This project will help you understand real-time data transfer, group authentication, and video/chat APIs.
Web Development Best Resources: https://topmate.io/coding/930165
ENJOY LEARNING 👍👍
1. Freelance Client Management System:
Build a system for freelancers to track client details, project timelines, invoices, and payments. Incorporate features like task lists, payment reminders, and time tracking. You’ll get hands-on experience with CRUD operations and secure user authentication.
2. Nonprofit Donation Platform:
Develop a platform for nonprofit organizations where users can donate to causes. You can include a donation tracker, goal setting, and integration with payment gateways like Stripe or PayPal. This will involve front-end design and server-side payment processing.
3. Interactive Educational Platform for Kids:
Create a platform where kids can learn basic subjects like math, spelling, or coding through fun, interactive games. Add features like badges, scoreboards, and quizzes to keep them engaged. This will give you experience in animations, gamification, and user experience design.
4. Real Estate Listings Website:
Build a platform where agents or homeowners can list properties for rent or sale. Include features like advanced search, map integration, and filters for property type, price, and location. You’ll get exposure to working with APIs and map services like Google Maps.
5. Virtual Art Gallery:
Design a virtual space where artists can display their work. Use animations to simulate a walk-through gallery, allowing users to explore and click on individual pieces for more details. You’ll explore 3D rendering, animations, and responsive design in this project.
6. Job Application Tracker:
Help job seekers keep track of job applications by building a dashboard that organizes companies, positions, interview stages, and deadlines. This app could send automated reminders for follow-ups, giving you experience with notifications and task scheduling.
7. Music Streaming Player:
Develop a personalized music player where users can create and share playlists. Integrate it with a music API like Spotify or Apple Music to pull in tracks. This project will introduce you to audio streaming, user authentication, and data storage for playlists.
8. Mental Health Tracker:
Create a web app where users can log daily moods, set mental health goals, and track progress over time. Incorporate features like journaling, breathing exercises, and visual data charts. This would involve data collection, chart visualization, and user interface design.
9. Sustainable Shopping Guide:
Build a platform where users can discover eco-friendly products and businesses. You can integrate a rating system for users to rate brands on sustainability practices. The project will teach you about APIs, user-generated content, and social proof.
10. Virtual Study Group App:
Create an app where students can join or form virtual study groups, chat in real-time, and share resources like notes and flashcards. You can add video integration or virtual whiteboards to make the platform more collaborative. This project will help you understand real-time data transfer, group authentication, and video/chat APIs.
Web Development Best Resources: https://topmate.io/coding/930165
ENJOY LEARNING 👍👍
👍3
𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗻𝘀𝗵𝗶𝗽 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝘀 𝗜𝗻 𝗧𝗼𝗽 𝗖𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀😍
1️⃣ BCG Data Science & Analytics Virtual Experience
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Enroll for FREE & Get Certified 🎓
1️⃣ BCG Data Science & Analytics Virtual Experience
2️⃣ TATA Data Visualization Internship
3️⃣ Accenture Data Analytics Virtual Internship
𝐋𝐢𝐧𝐤👇:-
https://pdlink.in/409RHXN
Enroll for FREE & Get Certified 🎓
👍1
Forwarded from Artificial Intelligence
𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝟭𝟬𝟬% 𝗙𝗿𝗲𝗲 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 𝗳𝗼𝗿 𝗔𝘇𝘂𝗿𝗲, 𝗔𝗜, 𝗖𝘆𝗯𝗲𝗿𝘀𝗲𝗰𝘂𝗿𝗶𝘁𝘆 & 𝗠𝗼𝗿𝗲😍
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Enjoy Learning ✅️
Want to upskill in Azure, AI, Cybersecurity, or App Development—without spending a single rupee?👨💻🎯
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Enjoy Learning ✅️
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Data Science & Machine Learning
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ChatGPT Hacks
SQL
Tableau & Power BI
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👍1
If you're serious about getting into Data Science with Python, follow this 5-step roadmap.
Each phase builds on the previous one, so don’t rush.
Take your time, build projects, and keep moving forward.
Step 1: Python Fundamentals
Before anything else, get your hands dirty with core Python.
This is the language that powers everything else.
✅ What to learn:
type(), int(), float(), str(), list(), dict()
if, elif, else, for, while, range()
def, return, function arguments
List comprehensions: [x for x in list if condition]
– Mini Checkpoint:
Build a mini console-based data calculator (inputs, basic operations, conditionals, loops).
Step 2: Data Cleaning with Pandas
Pandas is the tool you'll use to clean, reshape, and explore data in real-world scenarios.
✅ What to learn:
Cleaning: df.dropna(), df.fillna(), df.replace(), df.drop_duplicates()
Merging & reshaping: pd.merge(), df.pivot(), df.melt()
Grouping & aggregation: df.groupby(), df.agg()
– Mini Checkpoint:
Build a data cleaning script for a messy CSV file. Add comments to explain every step.
Step 3: Data Visualization with Matplotlib
Nobody wants raw tables.
Learn to tell stories through charts.
✅ What to learn:
Basic charts: plt.plot(), plt.scatter()
Advanced plots: plt.hist(), plt.kde(), plt.boxplot()
Subplots & customizations: plt.subplots(), fig.add_subplot(), plt.title(), plt.legend(), plt.xlabel()
– Mini Checkpoint:
Create a dashboard-style notebook visualizing a dataset, include at least 4 types of plots.
Step 4: Exploratory Data Analysis (EDA)
This is where your analytical skills kick in.
You’ll draw insights, detect trends, and prepare for modeling.
✅ What to learn:
Descriptive stats: df.mean(), df.median(), df.mode(), df.std(), df.var(), df.min(), df.max(), df.quantile()
Correlation analysis: df.corr(), plt.imshow(), scipy.stats.pearsonr()
— Mini Checkpoint:
Write an EDA report (Markdown or PDF) based on your findings from a public dataset.
Step 5: Intro to Machine Learning with Scikit-Learn
Now that your data skills are sharp, it's time to model and predict.
✅ What to learn:
Training & evaluation: train_test_split(), .fit(), .predict(), cross_val_score()
Regression: LinearRegression(), mean_squared_error(), r2_score()
Classification: LogisticRegression(), accuracy_score(), confusion_matrix()
Clustering: KMeans(), silhouette_score()
– Final Checkpoint:
Build your first ML project end-to-end
✅ Load data
✅ Clean it
✅ Visualize it
✅ Run EDA
✅ Train & test a model
✅ Share the project with visuals and explanations on GitHub
Don’t just complete tutorialsm create things.
Explain your work.
Build your GitHub.
Write a blog.
That’s how you go from “learning” to “landing a job
Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
All the best 👍👍
Each phase builds on the previous one, so don’t rush.
Take your time, build projects, and keep moving forward.
Step 1: Python Fundamentals
Before anything else, get your hands dirty with core Python.
This is the language that powers everything else.
✅ What to learn:
type(), int(), float(), str(), list(), dict()
if, elif, else, for, while, range()
def, return, function arguments
List comprehensions: [x for x in list if condition]
– Mini Checkpoint:
Build a mini console-based data calculator (inputs, basic operations, conditionals, loops).
Step 2: Data Cleaning with Pandas
Pandas is the tool you'll use to clean, reshape, and explore data in real-world scenarios.
✅ What to learn:
Cleaning: df.dropna(), df.fillna(), df.replace(), df.drop_duplicates()
Merging & reshaping: pd.merge(), df.pivot(), df.melt()
Grouping & aggregation: df.groupby(), df.agg()
– Mini Checkpoint:
Build a data cleaning script for a messy CSV file. Add comments to explain every step.
Step 3: Data Visualization with Matplotlib
Nobody wants raw tables.
Learn to tell stories through charts.
✅ What to learn:
Basic charts: plt.plot(), plt.scatter()
Advanced plots: plt.hist(), plt.kde(), plt.boxplot()
Subplots & customizations: plt.subplots(), fig.add_subplot(), plt.title(), plt.legend(), plt.xlabel()
– Mini Checkpoint:
Create a dashboard-style notebook visualizing a dataset, include at least 4 types of plots.
Step 4: Exploratory Data Analysis (EDA)
This is where your analytical skills kick in.
You’ll draw insights, detect trends, and prepare for modeling.
✅ What to learn:
Descriptive stats: df.mean(), df.median(), df.mode(), df.std(), df.var(), df.min(), df.max(), df.quantile()
Correlation analysis: df.corr(), plt.imshow(), scipy.stats.pearsonr()
— Mini Checkpoint:
Write an EDA report (Markdown or PDF) based on your findings from a public dataset.
Step 5: Intro to Machine Learning with Scikit-Learn
Now that your data skills are sharp, it's time to model and predict.
✅ What to learn:
Training & evaluation: train_test_split(), .fit(), .predict(), cross_val_score()
Regression: LinearRegression(), mean_squared_error(), r2_score()
Classification: LogisticRegression(), accuracy_score(), confusion_matrix()
Clustering: KMeans(), silhouette_score()
– Final Checkpoint:
Build your first ML project end-to-end
✅ Load data
✅ Clean it
✅ Visualize it
✅ Run EDA
✅ Train & test a model
✅ Share the project with visuals and explanations on GitHub
Don’t just complete tutorialsm create things.
Explain your work.
Build your GitHub.
Write a blog.
That’s how you go from “learning” to “landing a job
Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
All the best 👍👍
👍5
Forwarded from Artificial Intelligence
𝗙𝗥𝗘𝗘 𝗠𝗶𝗰𝗿𝗼𝘀𝗼𝗳𝘁 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲𝘀 😍
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𝐋𝐢𝐧𝐤👇:-
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Essential skills for today’s tech-driven world✅️
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𝐋𝐢𝐧𝐤👇:-
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Essential skills for today’s tech-driven world✅️
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