𝐓𝐨𝐩 𝐌𝐍𝐂'𝐬 𝐇𝐢𝐫𝐢𝐧𝐠 𝐅𝐨𝐫 𝐌𝐮𝐥𝐭𝐢𝐩𝐥𝐞 𝐑𝐨𝐥𝐞𝐬 𝐀𝐜𝐫𝐨𝐬𝐬 𝐈𝐧𝐝𝐢𝐚

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Step 2:- Fill in your professional details like education & work experience (if any)

Step 3 :- Select your skills & preferred job role & location 

Apply To The Jobs That Match To Your Profile.

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Here is the list of Games learn css , html and javascript with fun.

1. CodeCombat

https://codecombat.com/

2. CSS Diner

https://flukeout.github.io/

3. Flexbox Froggy

https://flexboxfroggy.com/

4. CheckIO and Empire of Code

https://checkio.org/

5. Flexbox Defense

http://www.flexboxdefense.com/

6. Untrusted

https://alexnisnevich.github.io/untrusted/

7. CodeMonkey

https://www.codemonkey.com/

8. CodinGame

https://www.codingame.com/start/

Here's the website that have 10,000+ Tech internships with the government of India and top MNC's.

Link- https://internship.aicte-india.org/

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Here's the government job website's link.

Link- https://www.ncs.gov.in/

💥📚These SQL interview questions typically asked in a Data Analyst interview?

1.What distinguishes a Primary key from a Unique key?

Primary key uniquely identifies each record in a table and cannot contain null values, whereas a Unique key also uniquely identifies records but can contain null values and multiple unique keys can exist in a table.

2. Define Candidate key.

Candidate key is a key or set of keys that uniquely identifies each record in a table. It can be a combination of Primary and Alternate keys.

3.Explain the concept of Constraint in SQL.

A Constraint is a specific rule or limit defined in a table to enforce data integrity. Examples include NOT NULL and AUTO INCREMENT.

4. Differentiate between TRUNCATE and DELETE commands.

TRUNCATE is a DDL command that removes all data from a table while preserving the table's structure, and it is faster than DELETE. DELETE is a DML command that removes specific rows based on conditions and operates slower than TRUNCATE as it deletes data row by row.

5.Compare and contrast a 'View' and a 'Stored Procedure'.

A View is a virtual table derived from one or more base tables, often used to simplify complex queries, while a Stored Procedure is a precompiled collection of SQL statements stored on the database server, used to perform specific tasks or operations.

6.What sets apart a Common Table Expression from a temporary table?

A Common Table Expression (CTE) is a temporary result set defined within the execution scope of a single SELECT, DELETE, or UPDATE statement, while a temporary table is stored in TempDB and persists until the session ends.

7.Contrast a clustered index with a non-clustered index.

A clustered index determines the physical ordering of data in a table and there can be only one clustered index per table. In contrast, a non-clustered index is similar to an index in a book where data is stored separately from the index, and multiple non-clustered indexes can exist for a table.

8.Define triggers in SQL and their purpose.

Triggers are SQL codes that automatically execute in response to certain events on a table, such as INSERT, UPDATE, or DELETE operations. They are used to maintain data integrity and perform actions based on specific conditions.

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Here's free courses provided by Microsoft.

1. Microsoft azure AI foundation

Link- https://learn.microsoft.com/en-us/credentials/certifications/azure-ai-fundamentals/?practice-assessment-type=certification

2. Microsoft Certified: Azure Fundamentals

Link- https://learn.microsoft.com/en-us/credentials/certifications/azure-fundamentals/?practice-assessment-type=certification

3. Azure SQL fundamentals

Link- https://learn.microsoft.com/en-us/training/paths/azure-sql-fundamentals/

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Start your career in data analysis for freshers 😄👇

1. Learn the Basics: Begin with understanding the fundamental concepts of statistics, mathematics, and programming languages like Python or R.

2. Acquire Technical Skills: Develop proficiency in data analysis tools such as Excel, SQL, and data visualization tools like Tableau or Power BI.

3. Gain Knowledge in Statistics: A solid foundation in statistical concepts is crucial for data analysis. Learn about probability, hypothesis testing, and regression analysis.
Free course by Khan Academy will help you to enhance these skills.

4. Programming Proficiency: Enhance your programming skills, especially in languages commonly used in data analysis like Python or R. Familiarity with libraries such as Pandas and NumPy in Python is beneficial. Kaggle has amazing content to learn these skills.

5. Data Cleaning and Preprocessing: Understand the importance of cleaning and preprocessing data. Learn techniques to handle missing values, outliers, and transform data for analysis.

6. Database Knowledge: Acquire knowledge about databases and SQL for efficient data retrieval and manipulation.

7. Data Visualization: Master the art of presenting insights through visualizations. Learn tools like Matplotlib, Seaborn, or ggplot2 for creating meaningful charts and graphs. If you are from non-technical background, learn Tableau or Power BI.

8. Machine Learning Basics: Familiarize yourself with basic machine learning concepts. This knowledge can be beneficial for advanced analytics tasks.

9. Build a Portfolio: Work on projects that showcase your skills. This could be personal projects, contributions to open-source projects, or challenges from platforms like Kaggle.

10. Networking and Continuous Learning: Engage with the data science community, attend meetups, webinars, and conferences. Build your strong Linkedin profile and enhance your network.

11. Apply for Internships or Entry-Level Positions: Gain practical experience by applying for internships or entry-level positions in data analysis. Real-world projects contribute significantly to your learning.

12. Effective Communication: Develop strong communication skills. Being able to convey your findings and insights in a clear and understandable manner is crucial.

Here are your links for free AI COURSES provided by Nvidia 👇

Generative AI Explained -
https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-07+V1

Augment your LLM Using Retrieval Augmented Generation - https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-16+V1

Building RAG Agents with LLMs - https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-FX-15+V1

Getting Started with AI on Jetson Nano - https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-RX-02+V2

Building Video AI Applications at the Edge on Jetson Nano - https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-IV-02+V2

Essentials of Developing Omniverse Kit Applications - https://learn.nvidia.com/courses/course-detail?course_id=course-v1:DLI+S-OV-11+V1

Here's the website link which have cheet sheets for CODERS GAMERS and STUDENTS.


Link- https://cheatography.com/

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ROADMAP TO LEARN FRONTEND WEB DEVELOPMENT

By following this roadmap, you'll gain a solid understanding of frontend web development, equipping you with the skills needed to build modern, responsive, and dynamic web applications:


1. Foundational Skills

I. HTML (HyperText Markup Language)
○ Structure of a webpage
○ Semantic HTML elements
○ Forms and input elements
○ Accessibility basics

II. CSS (Cascading Style Sheets)
○ Styling elements
○ Layout techniques (Box Model, Flexbox, Grid)
○ Responsive design (Media Queries)
○ CSS preprocessors (Sass, LESS)

III. JavaScript
○ Syntax and basics (variables, data types, loops, functions)
○ DOM manipulation
○ Event handling
○ ES6+ features (let, const, arrow functions, template literals)

2. Version Control Systems

I. Git
○ Basic commands (init, clone, add, commit, push, pull)
○ Branching and merging
○ Using platforms like GitHub, GitLab, or Bitbucket

3. Development Tools

I. Text Editors/IDEs

○ VSCode, Sublime Text, Atom

II. Browser Developer Tools
○ Inspecting and debugging HTML, CSS, and JavaScript

III. Command Line Basics
○ Navigating the filesystem
○ Running scripts

4. Advanced JavaScript

I. Asynchronous JavaScript

○ Callbacks, Promises, Async/Await

II. JavaScript Modules
○ Import/export syntax
○ Module bundlers (Webpack, Parcel)

III. APIs and AJAX
○ Fetch API, XMLHttpRequest
○ Working with JSON
○ RESTful services

5. Frontend Frameworks and Libraries

I. React
○ Components, JSX
○ State and Props
○ Hooks and Lifecycle methods
○ React Router for navigation

II. Vue.js
○ Vue instance, directives
○ Components, Vue Router, Vuex for state management

III. Angular
○ TypeScript, Components, Modules
○ Services and Dependency Injection
○ Angular Router

6. State Management
I. Redux (for React)
○ Store, Actions, Reducers
○ Middleware (Redux Thunk, Redux Saga)
II. Vuex (for Vue.js)
III. NgRx (for Angular)

7. Styling Frameworks and Libraries

I. CSS Frameworks
○ Bootstrap, Bulma, Tailwind CSS
II. CSS-in-JS
○ Styled-components, Emotion

8. Build Tools and Automation

I. Task Runners
○ npm scripts, Gulp

II. Module Bundlers
○ Webpack, Parcel, Rollup

III. Code Quality Tools
○ Linters (ESLint, Stylelint)
○ Formatters (Prettier)

9. Testing
I. Unit Testing
○ Jest, Mocha, Jasmine
II. Integration Testing
○ React Testing Library, Enzyme
III. End-to-End Testing
○ Cypress, Selenium

10. Progressive Web Apps (PWAs)

I. Service Workers
○ Caching strategies
○ Offline functionality
II. Web App Manifest
○ Metadata for the app

11. Performance Optimization

I. Code Splitting
II. Lazy Loading
III. Image Optimization
IV. Minification and Compression

12. Deployment and Hosting

I. Static Site Generators
○ Next.js, Nuxt.js, Gatsby
II. Hosting Platforms
○ Netlify, Vercel, GitHub Pages
III. CI/CD
○ Setting up continuous integration and deployment pipelines

13. Soft Skills and Collaboration

I. Agile/Scrum Methodologies
II. Communication Skills
III. Problem-Solving and Debugging

Additional Resources
I. Online Courses and Tutorials
○ FreeCodeCamp, Codecademy, Coursera, Udemy
II. Documentation and Books
○ MDN Web Docs, W3Schools, "You Don’t Know JS" series
III. Community and Networking
○ Join developer communities (Reddit, Stack Overflow, Dev.to)
○ Attend webinars and conferences

Coding Projects That Will Actually Get You Hired

1. 3D Engine

David Rousset: write a 3D soft engine from scratch

Link- https://www.davrous.com/2013/06/13/tutorial-series-learning-how-to-write-a-3d-soft-engine-from-scratch-in-c-typescript-or-javascript/

2. Neural Networks

Victor Zhou: Introduction to neural networks

Link- https://victorzhou.com/blog/intro-to-neural-networks/

3. Build A Web Browser

Chris Harrelson: Web browser engineering

Link- https://browser.engineering/

4. Build A Framework

Paul Shannessy: Building React from Scratch

Link- https://youtu.be/_MAD4Oly9yg?si=Hj2tmWWQl9u5Hu2X

Top MNCs Hiring Data Analysts & Business Analysts

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BEST WAY TO START LEARNING PYTHON- A COMPLETE ROADMAP

By following this roadmap, you'll be able to build a solid foundation in Python and advance to more complex topics and projects over time.

1. Getting Started

I. Install Python: Download and install Python from the official website.

II. Setup IDE: Use an Integrated Development Environment (IDE) like PyCharm, VS Code, or Jupyter Notebook.

2. Basic Concepts

I. Syntax and Semantics: Learn the basic syntax (print statements, variables, comments).

II. Data Types: Understand different data types like integers, floats, strings, and booleans.

III. Operators: Learn about arithmetic, comparison, logical, and bitwise operators.

IV. Control Structures: Master if-else statements, loops (for, while), and list comprehensions.

3. Data Structures

I. Lists: Creation, indexing, slicing, and methods.
II. Tuples: Immutable sequences and their usage.
III. Dictionaries: Key-value pairs and dictionary methods.
IV. Sets: Unique collections and set operations.

4. Functions and Modules

I. Functions: Defining functions, arguments, return values, and scope.
II. Lambda Functions: Anonymous functions and use cases.
III. Modules and Packages: Importing modules, standard library, and creating your own modules.

5. Object-Oriented Programming (OOP)

I. Classes and Objects: Define classes, create objects, and understand self.

II. Inheritance: Learn about single and multiple inheritance.
III. Polymorphism: Methods overriding and magic methods.
IV. Encapsulation: Private and public attributes
.
6. Error and Exception Handling
I. Try-Except Block: Handle exceptions and use finally.
II. Custom Exceptions: Creating and raising custom exceptions.

7. File Handling

I. Reading and Writing: Open, read, write, and close files.
II. File Methods: Learn about various file methods.

8. Libraries and Frameworks

I. Standard Libraries: Learn about math, datetime, os, and sys.
II. Data Science Libraries: Introduction to NumPy, Pandas, Matplotlib, and SciPy.
III. Web Development: Basics of Flask or Django.
IV. Automation: Learn about Selenium or Scrapy.

9. Advanced Topics

I. Decorators: Functions that modify other functions.
II. Generators: Yield keyword and generator functions.
III. Context Managers: Using with statement.
IV. Concurrency: Threads, async programming with asyncio.

10. Projects and Practice

I. Mini Projects: Start with small projects like a calculator, to-do list app, or a web scraper.
II. Contribute to Open Source: Contribute to projects on GitHub.
III. Coding Challenges: Solve problems on platforms like LeetCode, HackerRank, or CodeSignal.

11. Resources

I. Books: "Automate the Boring Stuff with Python" by Al Sweigart, "Python Crash Course" by Eric Matthes.
II. Online Courses: Coursera, Udemy, edX, freeCodeCamp, W3School, geeksforgeeks, etc.
III. Documentation: Python Official Documentation.

12. Community and Support

I. Forums and Q&A: Engage with communities on Stack Overflow, Reddit, and Python Discord.
II. Meetups and Conferences: Attend local Python meetups or international conferences like PyCon.

13. Continuous Learning

I. Stay updated with the latest Python versions and features.

II. Regularly read Python-related blogs, articles, and tutorials.