Here is the link for free AI Certification course by Microsoft
Link - https://www.linkedin.com/learning/paths/career-essentials-in-generative-ai-by-microsoft-and-linkedin
Link - https://www.linkedin.com/learning/paths/career-essentials-in-generative-ai-by-microsoft-and-linkedin
LinkedIn
Career Essentials in Generative AI by Microsoft and LinkedIn Learning Path | LinkedIn Learning, formerly Lynda.com
Generative AI is reshaping industries by transforming how work gets done. This learning path puts you at the forefront of this creative revolution, covering content creation, key models, future trends, ethical considerations, and tools like Microsoft Copilot.β¦
Here are Free CISCO courses with Badges for resume and LinkedIn
1. Introduction to Cybersecurity
link - https://skillsforall.com/course/introduction-to-cybersecurity
2. Data Analytics Essentials
link-https://skillsforall.com/course/data-analytics-essentials
3. Introduction to Data Science
link- https://skillsforall.com/course/introduction-data-science
4. Python Essentials 1
link- https://skillsforall.com/course/python-essentials-1
Python Essentials 2
link- https://skillsforall.com/course/python-essentials-2
5. Exploring Networking with Cisco Packet Tracer
link- https://skillsforall.com/course/exploring-networking-cisco-packet-tracer
1. Introduction to Cybersecurity
link - https://skillsforall.com/course/introduction-to-cybersecurity
2. Data Analytics Essentials
link-https://skillsforall.com/course/data-analytics-essentials
3. Introduction to Data Science
link- https://skillsforall.com/course/introduction-data-science
4. Python Essentials 1
link- https://skillsforall.com/course/python-essentials-1
Python Essentials 2
link- https://skillsforall.com/course/python-essentials-2
5. Exploring Networking with Cisco Packet Tracer
link- https://skillsforall.com/course/exploring-networking-cisco-packet-tracer
Netacad
Introduction to Cybersecurity
Learn cybersecurity basics to protect your personal digital life and the biggest security challenges companies face today.
π8β€7π₯1
Wipro is Hiring 2024
Role :- Developer
Qualification :- Bachelor's degree in Computer Science, Information Technology, or a related field
Job Location : Bengaluru
Salary Package:- Upto 6 LPA
Apply Link π:-
https://bit.ly/49Kku7J
Apply before the link expires
Role :- Developer
Qualification :- Bachelor's degree in Computer Science, Information Technology, or a related field
Job Location : Bengaluru
Salary Package:- Upto 6 LPA
Apply Link π:-
https://bit.ly/49Kku7J
Apply before the link expires
π4β€1
Data Analytics Internship Program 2024
Company Name:- Poshmark
Job Position:- Data Analytics Intern
Experience :- 0-1 years of analytics experience.
Apply Link π:-
https://bit.ly/4cb14uq
Apply before the link expires
Company Name:- Poshmark
Job Position:- Data Analytics Intern
Experience :- 0-1 years of analytics experience.
Apply Link π:-
https://bit.ly/4cb14uq
Apply before the link expires
π2β€1
Games to learn code .
1. Code combat
Link- https://codecombat.com/
2. CSS Diner
Link - https://flukeout.github.io/
3. Flexbox Froggy
Link- https://flexboxfroggy.com/
4. CheckIO and Empire of Code
Link- https://checkio.org/
5. Flexbox Defense
Link- http://www.flexboxdefense.com/
6. Untrusted
Link- https://www.playuntrusted.com/
7. CodeMonkey
Link- https://www.codemonkey.com/
8. CodinGame
Link- https://www.codingame.com/
1. Code combat
Link- https://codecombat.com/
2. CSS Diner
Link - https://flukeout.github.io/
3. Flexbox Froggy
Link- https://flexboxfroggy.com/
4. CheckIO and Empire of Code
Link- https://checkio.org/
5. Flexbox Defense
Link- http://www.flexboxdefense.com/
6. Untrusted
Link- https://www.playuntrusted.com/
7. CodeMonkey
Link- https://www.codemonkey.com/
8. CodinGame
Link- https://www.codingame.com/
CodeCombat
CodeCombat: Learn to Code by Playing a Game
Learn programming with a multiplayer live coding strategy game for beginners. Learn Python or JavaScript as you defeat ogres, solve mazes, and level up. Open source HTML5 game!
π11β€1
π React JS Roadmap:
1. Fundamental Building Blocks:
- Master JavaScript basics: Variables, Functions, Loops.
- Dive into ES6+ features: Arrow Functions, Promises, Async/Await.
- Understand HTML & CSS fundamentals: Tags, Styling, Flexbox.
2. Getting Started with React:
- Explore React's core concepts: Virtual DOM, Components, JSX.
- Set up your development environment: Node, NPM, Create React App.
3. Component & State Management:
- Learn about Components & Props: Functional vs. Class Components.
- Dive into State & Lifecycle management: useState, useEffect, useContext.
- Explore Context API for global state management.
4. Advanced React Techniques:
- Master React Hooks: useRef, useMemo, useCallback.
- Level up your Routing skills: React Router Setup, Nested Routing.
- Explore Higher Order Components (HOC) and Render Props patterns.
5. Styling & Design Patterns:
- Enhance UI with CSS-in-JS Libraries like Styled-components.
- Utilize CSS Frameworks: Bootstrap, Material-UI, Ant Design.
6. State Management Solutions:
- Understand Redux for predictable state management.
- Dive into MobX for simpler state management patterns.
- Explore local state management techniques: Lifting State Up, Container Components.
7. Testing & Optimization:
- Write and run tests with Jest and React Testing Library.
- Optimize performance using Virtualized Lists, Code Splitting.
- Implement lazy loading with React.lazy and Suspense.
8. Server-Side Rendering & Beyond:
- Explore Next.js for server-side rendering and better SEO.
9. Miscellaneous Topics:
- Integrate GraphQL with React using libraries like Apollo.
- Dive into TypeScript for better type safety.
- Add animations using libraries like Framer Motion.
- Implement Internationalization (i18n) & Localization in your React apps.
1. Fundamental Building Blocks:
- Master JavaScript basics: Variables, Functions, Loops.
- Dive into ES6+ features: Arrow Functions, Promises, Async/Await.
- Understand HTML & CSS fundamentals: Tags, Styling, Flexbox.
2. Getting Started with React:
- Explore React's core concepts: Virtual DOM, Components, JSX.
- Set up your development environment: Node, NPM, Create React App.
3. Component & State Management:
- Learn about Components & Props: Functional vs. Class Components.
- Dive into State & Lifecycle management: useState, useEffect, useContext.
- Explore Context API for global state management.
4. Advanced React Techniques:
- Master React Hooks: useRef, useMemo, useCallback.
- Level up your Routing skills: React Router Setup, Nested Routing.
- Explore Higher Order Components (HOC) and Render Props patterns.
5. Styling & Design Patterns:
- Enhance UI with CSS-in-JS Libraries like Styled-components.
- Utilize CSS Frameworks: Bootstrap, Material-UI, Ant Design.
6. State Management Solutions:
- Understand Redux for predictable state management.
- Dive into MobX for simpler state management patterns.
- Explore local state management techniques: Lifting State Up, Container Components.
7. Testing & Optimization:
- Write and run tests with Jest and React Testing Library.
- Optimize performance using Virtualized Lists, Code Splitting.
- Implement lazy loading with React.lazy and Suspense.
8. Server-Side Rendering & Beyond:
- Explore Next.js for server-side rendering and better SEO.
9. Miscellaneous Topics:
- Integrate GraphQL with React using libraries like Apollo.
- Dive into TypeScript for better type safety.
- Add animations using libraries like Framer Motion.
- Implement Internationalization (i18n) & Localization in your React apps.
π6β€1
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& crack pay after placement batch In Just 8 days
Get placed in top MNC's with highest package
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π 41 LPA Highest Package
Eligibility: BTech / BCA / BSc / MCA / MSc
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Hurry, limited seats available!
& crack pay after placement batch In Just 8 days
Get placed in top MNC's with highest package
π Trusted by 6000+ Students
π€ 450+ Hiring Partners
πΌ Avg. Rs. 7.2 LPA
π 41 LPA Highest Package
Eligibility: BTech / BCA / BSc / MCA / MSc
πππ π’π¬πππ« ππ¨π°π :-
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Hurry, limited seats available!
π7
πTips and Tricks on how to optimize your code [techniques]:
Code optimization is all about making your code run faster and use fewer resources without changing its functionality.
1. Choose the Right Data Structures:
- Use data structures that are efficient for your specific tasks. For example, use sets for membership checks and dictionaries for fast key-value lookups.
2. Reduce Redundant Operations:
- Avoid repeating the same calculations or operations unnecessarily. Store the results of expensive operations and reuse them when needed.
3. Use Loops Wisely:
- Minimize the number of loops and iterations. Nested loops can quickly become inefficient. If possible, replace loops with built-in functions like map, filter, and list comprehensions.
4. Optimize Algorithm Complexity:
- Choose algorithms with lower time complexity for your problem. For example, if a linear search isn't efficient, consider using binary search for sorted data.
5. Avoid Global Variables:
- Minimize the use of global variables as they can lead to unexpected side effects and make your code harder to optimize.
6.Batch Database Queries:
- When working with databases, batch multiple queries into one instead of making individual queries. This reduces overhead.
7. Profiling Tools:
- Use profiling tools to identify bottlenecks in your code. These tools show you which parts of your code consume the most time and resources.
8. Memory Management:
- Be mindful of memory usage. Avoid unnecessary object creation and deallocate memory when it's no longer needed. Use generators instead of lists when processing large datasets.
9. Caching:
- Cache the results of expensive function calls if the output is constant for a given input. This can save time by preventing redundant calculations.
10. Lazy Evaluation:
- Use lazy evaluation where appropriate. In languages that support it, lazy evaluation allows you to defer calculations until the result is actually needed.
11. Vectorization:
- When working with numerical data, use vectorized operations provided by libraries like NumPy. These operations are highly optimized and can perform calculations on entire arrays at once.
12. Avoid Unnecessary I/O:
- Input/Output operations, like reading from/writing to files or databases, can be slow. Minimize these operations and consider using in-memory data structures.
13. Benchmarking:
- Compare the performance of different code versions or approaches using benchmarking tools. This helps you make informed optimization decisions.
14. Keep Code Readable:
- While optimizing, make sure your code remains readable and maintainable. Clear code is easier to understand and debug.
15. Profile and Test Again:
- After making optimizations, profile your code again to ensure your changes had the desired impact. Sometimes, optimizations can have unintended consequences.
Code optimization is all about making your code run faster and use fewer resources without changing its functionality.
1. Choose the Right Data Structures:
- Use data structures that are efficient for your specific tasks. For example, use sets for membership checks and dictionaries for fast key-value lookups.
2. Reduce Redundant Operations:
- Avoid repeating the same calculations or operations unnecessarily. Store the results of expensive operations and reuse them when needed.
3. Use Loops Wisely:
- Minimize the number of loops and iterations. Nested loops can quickly become inefficient. If possible, replace loops with built-in functions like map, filter, and list comprehensions.
4. Optimize Algorithm Complexity:
- Choose algorithms with lower time complexity for your problem. For example, if a linear search isn't efficient, consider using binary search for sorted data.
5. Avoid Global Variables:
- Minimize the use of global variables as they can lead to unexpected side effects and make your code harder to optimize.
6.Batch Database Queries:
- When working with databases, batch multiple queries into one instead of making individual queries. This reduces overhead.
7. Profiling Tools:
- Use profiling tools to identify bottlenecks in your code. These tools show you which parts of your code consume the most time and resources.
8. Memory Management:
- Be mindful of memory usage. Avoid unnecessary object creation and deallocate memory when it's no longer needed. Use generators instead of lists when processing large datasets.
9. Caching:
- Cache the results of expensive function calls if the output is constant for a given input. This can save time by preventing redundant calculations.
10. Lazy Evaluation:
- Use lazy evaluation where appropriate. In languages that support it, lazy evaluation allows you to defer calculations until the result is actually needed.
11. Vectorization:
- When working with numerical data, use vectorized operations provided by libraries like NumPy. These operations are highly optimized and can perform calculations on entire arrays at once.
12. Avoid Unnecessary I/O:
- Input/Output operations, like reading from/writing to files or databases, can be slow. Minimize these operations and consider using in-memory data structures.
13. Benchmarking:
- Compare the performance of different code versions or approaches using benchmarking tools. This helps you make informed optimization decisions.
14. Keep Code Readable:
- While optimizing, make sure your code remains readable and maintainable. Clear code is easier to understand and debug.
15. Profile and Test Again:
- After making optimizations, profile your code again to ensure your changes had the desired impact. Sometimes, optimizations can have unintended consequences.
π7β€2
60-Day JavaScript Mastery Roadmap
*Foundational Skills*
π Day 1-5: Getting Started with JavaScript
- Introduction to JavaScript
- Understanding JavaScript Glossary
- JavaScript Syntax
- Lexical Structure and Expressions
- Types, Variables, and Math Operators
π Day 6-10: Functions and Control Flow
- Functions in JavaScript
- Scope and Closures
- Working with Loops
- Arrays and Array Methods
- Exploring IIFE and Arrow Functions
π Day 11-15: Advanced Concepts in JavaScript
- Understanding 'this' Keyword
- Introduction to ES6+ Features
- Template Literals and String Methods
- Working with Regular Expressions
- Exploring JavaScript Dates and Math Object
π Day 16-20: Asynchronous JavaScript
- Introduction to Asynchronous Programming
- Callback Functions
- Promises and Promise Chaining
- Async/Await Syntax
- Handling JavaScript Timers
π Day 21-25: Event Handling and DOM Manipulation
- Introduction to Events in JavaScript
- Event Bubbling and Capturing
- Handling User Interactions
- Working with Forms and Form Controls
- Document Object Model (DOM) Manipulation
*Advanced Techniques*
π Day 26-30: Functional Programming in JavaScript
- Understanding Functional Programming Paradigm
- Higher-Order Functions and Callbacks
- Working with Map, Filter, and Reduce
- Introduction to Currying and Composition
- Exploring Memoization and Immutability
π Day 31-35: Advanced JavaScript Patterns
- Module Pattern and Revealing Module Pattern
- Singleton Pattern
- Observer Pattern
- Factory and Constructor Patterns
- Prototype and Inheritance
π Day 36-40: Error Handling and Debugging
- Handling Errors in JavaScript
- Debugging Techniques and Tools
- Common Debugging Pitfalls
- Writing Robust Error-Handling Code
- Best Practices for Debugging
π Day 41-45: JavaScript Optimization and Performance
- Strategies for Improving Performance
- Optimizing Code Execution
- Minification and Compression Techniques
- Utilizing Browser DevTools for Performance Analysis
- Caching and Resource Management
π Day 46-50: Browser APIs and Interactions
- Introduction to Web APIs
- Working with Fetch API for AJAX Requests
- Geolocation API and Browser Storage
- Exploring Canvas and Web Workers
- Integrating Third-Party APIs
*Capstone Project and Beyond*
π Day 51-60: Capstone Project and Portfolio Development
- Building a Real-World JavaScript Application
- Version Control with Git and GitHub
- Creating a Professional Portfolio
- Showcasing Projects and Contributions
- Networking and Job Search Strategies
*Foundational Skills*
π Day 1-5: Getting Started with JavaScript
- Introduction to JavaScript
- Understanding JavaScript Glossary
- JavaScript Syntax
- Lexical Structure and Expressions
- Types, Variables, and Math Operators
π Day 6-10: Functions and Control Flow
- Functions in JavaScript
- Scope and Closures
- Working with Loops
- Arrays and Array Methods
- Exploring IIFE and Arrow Functions
π Day 11-15: Advanced Concepts in JavaScript
- Understanding 'this' Keyword
- Introduction to ES6+ Features
- Template Literals and String Methods
- Working with Regular Expressions
- Exploring JavaScript Dates and Math Object
π Day 16-20: Asynchronous JavaScript
- Introduction to Asynchronous Programming
- Callback Functions
- Promises and Promise Chaining
- Async/Await Syntax
- Handling JavaScript Timers
π Day 21-25: Event Handling and DOM Manipulation
- Introduction to Events in JavaScript
- Event Bubbling and Capturing
- Handling User Interactions
- Working with Forms and Form Controls
- Document Object Model (DOM) Manipulation
*Advanced Techniques*
π Day 26-30: Functional Programming in JavaScript
- Understanding Functional Programming Paradigm
- Higher-Order Functions and Callbacks
- Working with Map, Filter, and Reduce
- Introduction to Currying and Composition
- Exploring Memoization and Immutability
π Day 31-35: Advanced JavaScript Patterns
- Module Pattern and Revealing Module Pattern
- Singleton Pattern
- Observer Pattern
- Factory and Constructor Patterns
- Prototype and Inheritance
π Day 36-40: Error Handling and Debugging
- Handling Errors in JavaScript
- Debugging Techniques and Tools
- Common Debugging Pitfalls
- Writing Robust Error-Handling Code
- Best Practices for Debugging
π Day 41-45: JavaScript Optimization and Performance
- Strategies for Improving Performance
- Optimizing Code Execution
- Minification and Compression Techniques
- Utilizing Browser DevTools for Performance Analysis
- Caching and Resource Management
π Day 46-50: Browser APIs and Interactions
- Introduction to Web APIs
- Working with Fetch API for AJAX Requests
- Geolocation API and Browser Storage
- Exploring Canvas and Web Workers
- Integrating Third-Party APIs
*Capstone Project and Beyond*
π Day 51-60: Capstone Project and Portfolio Development
- Building a Real-World JavaScript Application
- Version Control with Git and GitHub
- Creating a Professional Portfolio
- Showcasing Projects and Contributions
- Networking and Job Search Strategies
π15
5 SQL projects for a strong resume
1) SQL Data Exploration
https://youtu.be/qfyynHBFOsM
2) SQL Data Cleaning
https://youtu.be/8r07ztF4NtU
©© Here are the links to main projects:
1) E-commerce Project (Very Popular)
https://github.com/aaronzguan/Online-Shopping-
Cart-Database-Project.git
2) Railway management system
https://github.com/aaryanrr/RailwayMGMT.git
3) Road Safety Dataset
https://github.com/ptyadana/SQL-Data-Analysis-and-Visualization-Projects/
4) European Soccer Game Analysis
https://www.kaggle.com/dimarudov/data-analysis-using-sql/data
5) World Population Dataset
https://github.com/LoicChamplong/Data-Analysis-
SQL/tree/master/ Analysis_of_the_2015_World_population
Step 1: Use the datasets shared above
Step 2: Take time to understand the content and structure. Identify key variables and columns.
Step 3: Set up the database: Choose a relational database management system (RDBMS) such as MySQL, PostgreSQL, or SQLite.
Step 4: Import the data: Load the dataset into your database. Make sure to create appropriate tables that match the structure of the dataset.
Step 5: Decide the questions: Brainstorm a list of questions you'd like to answer. For example, you could ask about trends, comparisons, aggregations, or correlations in the data.
©© Here are the links to main projects:
1) E-commerce Project (Very Popular)
https://github.com/aaronzguan/Online-Shopping-
Cart-Database-Project.git
2) Railway management system
https://github.com/aaryanrr/RailwayMGMT.git
3) Road Safety Dataset
https://github.com/ptyadana/SQL-Data-Analysis-and-Visualization-Projects/
4) European Soccer Game Analysis
https://www.kaggle.com/dimarudov/data-analysis-using-sql/data
5) World Population Dataset
https://github.com/LoicChamplong/Data-Analysis-
SQL/tree/master/ Analysis_of_the_2015_World_population
Step 1: Use the datasets shared above
Step 2: Take time to understand the content and structure. Identify key variables and columns.
Step 3: Set up the database: Choose a relational database management system (RDBMS) such as MySQL, PostgreSQL, or SQLite.
Step 4: Import the data: Load the dataset into your database. Make sure to create appropriate tables that match the structure of the dataset.
Step 5: Decide the questions: Brainstorm a list of questions you'd like to answer. For example, you could ask about trends, comparisons, aggregations, or correlations in the data.
Step 6: Write SQL queries: Convert your questions into SQL queries, then test and refine.
Step 7: Upload your project on Github. Also create documentation and powerpoints to explain your project.
5 SQL projects for a strong resume!
1) SQL Data Exploration
https://youtu.be/qfyynHBFOsM
2) SQL Data Cleaning
https://youtu.be/8r07ztF4NtU
©© Here are the links to main projects:
1) E-commerce Project (Very Popular)
https://github.com/aaronzguan/Online-Shopping-
Cart-Database-Project.git
2) Railway management system
https://github.com/aaryanrr/RailwayMGMT.git
3) Road Safety Dataset
https://github.com/ptyadana/SQL-Data-Analysis-and-Visualization-Projects/
4) European Soccer Game Analysis
https://www.kaggle.com/dimarudov/data-analysis-using-sql/data
5) World Population Dataset
https://github.com/LoicChamplong/Data-Analysis-
SQL/tree/master/ Analysis_of_the_2015_World_population
Step 1: Use the datasets shared above
Step 2: Take time to understand the content and structure. Identify key variables and columns.
Step 3: Set up the database: Choose a relational database management system (RDBMS) such as MySQL, PostgreSQL, or SQLite.
Step 4: Import the data: Load the dataset into your database. Make sure to create appropriate tables that match the structure of the dataset.
Step 5: Decide the questions: Brainstorm a list of questions you'd like to answer. For example, you could ask about trends, comparisons, aggregations, or correlations in the data.
©© Here are the links to main projects:
1) E-commerce Project (Very Popular)
https://github.com/aaronzguan/Online-Shopping-
Cart-Database-Project.git
2) Railway management system
https://github.com/aaryanrr/RailwayMGMT.git
3) Road Safety Dataset
https://github.com/ptyadana/SQL-Data-Analysis-and-Visualization-Projects/
4) European Soccer Game Analysis
https://www.kaggle.com/dimarudov/data-analysis-using-sql/data
5) World Population Dataset
https://github.com/LoicChamplong/Data-Analysis-
SQL/tree/master/ Analysis_of_the_2015_World_population
Step 1: Use the datasets shared above
Step 2: Take time to understand the content and structure. Identify key variables and columns.
Step 3: Set up the database: Choose a relational database management system (RDBMS) such as MySQL, PostgreSQL, or SQLite.
Step 4: Import the data: Load the dataset into your database. Make sure to create appropriate tables that match the structure of the dataset.
Step 5: Decide the questions: Brainstorm a list of questions you'd like to answer. For example, you could ask about trends, comparisons, aggregations, or correlations in the data.
Step 6: Write SQL queries: Convert your questions into SQL queries, then test and refine.
Step 7: Upload your project on Github. Also create documentation and powerpoints to explain your project.
5 SQL projects for a strong resume!
YouTube
Data Analyst Portfolio Project | SQL Data Exploration | Project 1/4
Take my Full MySQL Course Here: https://bit.ly/3tqOipr
Today we start our Data Analyst Portfolio Project Series. In our first project we will be using SQL to do some Data Exploration. We will then visualize the data in Tableau for our next project.
Linkβ¦
Today we start our Data Analyst Portfolio Project Series. In our first project we will be using SQL to do some Data Exploration. We will then visualize the data in Tableau for our next project.
Linkβ¦
π4
π
π«π¨π§πππ§π ππ«ππ’π§π’π§π & ππ§πππ«π§π¬π‘π’π© ππ«π¨π π«ππ¦ ππππ
Become an Industry Frontend Developer
Get real-time hands-on experience
Duration :- 2 Months
ππ’π π‘π₯π’π π‘ππ¬:-
- Internship Certificate
- Live Classes
- Projects
ππ©π©π₯π² ππ¨π°π:-
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( Few Seats Left )
Application closes soon
Become an Industry Frontend Developer
Get real-time hands-on experience
Duration :- 2 Months
ππ’π π‘π₯π’π π‘ππ¬:-
- Internship Certificate
- Live Classes
- Projects
ππ©π©π₯π² ππ¨π°π:-
https://bit.ly/3T8qCRg
( Few Seats Left )
Application closes soon
π1
IBM Work From Home Opportunity 2024
Company Name:- IBM
Job Position:- Associate System Engineer
Job Location :- PAN India
Salary:- Upto 6 LPA
Apply Link π:-
https://bit.ly/3TzbufO
Apply before the link expires
Company Name:- IBM
Job Position:- Associate System Engineer
Job Location :- PAN India
Salary:- Upto 6 LPA
Apply Link π:-
https://bit.ly/3TzbufO
Apply before the link expires
π2
Hereβs how you can land your first job in Tech as a Python Developer
β‘οΈBuild a Strong Foundation:
Master Python basics: variables, data types, control structures.
β‘οΈDevelop Projects:
Create practical Python projects (e.g., web apps, data analysis, automation scripts).
β‘οΈVersion Control:
Learn Git for code versioning and use platforms like GitHub for collaboration.
β‘οΈNetworking:
Attend tech events, conferences, and workshops.
Build an online presence on platforms like LinkedIn.
β‘οΈResume Optimization:
Highlight Python skills, relevant projects, problem-solving, teamwork.
β‘οΈApply Widely:
Apply to various entry-level positions in tech.
β‘οΈPrepare for Interviews:
Practice coding challenges on platforms like LeetCode or HackerRank.
β‘οΈSoft Skills:
Develop communication, teamwork, and adaptability skills.
β‘οΈPersonal Projects:
Work on personal Python projects to gain experience.
β‘οΈInternships:
Consider internships or freelance roles to enhance your resume.
β‘οΈOpen Source Contributions:
Contribute to open source projects to showcase your skills.
β‘οΈContinuous Learning:
Stay updated with Python libraries, frameworks, and industry trends.
β‘οΈInterview Etiquette:
Dress appropriately, be punctual, and show enthusiasm during interviews.
β‘οΈShow Problem Solving:
Explain your approach to problem-solving in interviews.
β‘οΈStay Persistent:
Donβt lose motivation during the competitive tech job search. Keep improving and learning from each experience.
Each step contributes to your growth as a Python developer and increases your chances of landing your first tech job
β‘οΈBuild a Strong Foundation:
Master Python basics: variables, data types, control structures.
β‘οΈDevelop Projects:
Create practical Python projects (e.g., web apps, data analysis, automation scripts).
β‘οΈVersion Control:
Learn Git for code versioning and use platforms like GitHub for collaboration.
β‘οΈNetworking:
Attend tech events, conferences, and workshops.
Build an online presence on platforms like LinkedIn.
β‘οΈResume Optimization:
Highlight Python skills, relevant projects, problem-solving, teamwork.
β‘οΈApply Widely:
Apply to various entry-level positions in tech.
β‘οΈPrepare for Interviews:
Practice coding challenges on platforms like LeetCode or HackerRank.
β‘οΈSoft Skills:
Develop communication, teamwork, and adaptability skills.
β‘οΈPersonal Projects:
Work on personal Python projects to gain experience.
β‘οΈInternships:
Consider internships or freelance roles to enhance your resume.
β‘οΈOpen Source Contributions:
Contribute to open source projects to showcase your skills.
β‘οΈContinuous Learning:
Stay updated with Python libraries, frameworks, and industry trends.
β‘οΈInterview Etiquette:
Dress appropriately, be punctual, and show enthusiasm during interviews.
β‘οΈShow Problem Solving:
Explain your approach to problem-solving in interviews.
β‘οΈStay Persistent:
Donβt lose motivation during the competitive tech job search. Keep improving and learning from each experience.
Each step contributes to your growth as a Python developer and increases your chances of landing your first tech job
π5β€1
50 MOST ASKED INTERVIEW QUESTIONS FOR JAVASCRIPT.pdf
140.3 KB
I am sharing '50 MOST ASKED INTERVIEW QUESTIONS FOR JAVASCRIPT' with you
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https://www.instagram.com/reel/C4iCLzFvkIp/?igsh=MWg0bmxzY2lydm82bg==
Here is how project based learning can me game changing for you .
1. Hands-on Experience: Project-based learning offers practical coding experience.
2. Enhanced Understanding: Learners apply theory to real-world situations, deepening comprehension.
3. Problem-Solving: Projects develop problem-solving skills through challenges.
4. Collaboration: Teamwork is encouraged, fostering collaboration.
5. Research and Growth: Learners research, experiment, and grow their skills.
6. Accomplishment: Completing projects boosts confidence and provides a sense of achievement.
7. Portfolio Building: Projects contribute to a diverse portfolio showcasing skills.
8. Creativity: Encourages creativity and innovation in finding solutions.
Link - https://github.com/practical-tutorials/project-based-learning?tpclid=facebook.PAAabomU9Szh7vQMnIHyCYix3EcsPObQnrNSn9z57RBOzZ4XlTQ24YW9DY-bY
Here is how project based learning can me game changing for you .
1. Hands-on Experience: Project-based learning offers practical coding experience.
2. Enhanced Understanding: Learners apply theory to real-world situations, deepening comprehension.
3. Problem-Solving: Projects develop problem-solving skills through challenges.
4. Collaboration: Teamwork is encouraged, fostering collaboration.
5. Research and Growth: Learners research, experiment, and grow their skills.
6. Accomplishment: Completing projects boosts confidence and provides a sense of achievement.
7. Portfolio Building: Projects contribute to a diverse portfolio showcasing skills.
8. Creativity: Encourages creativity and innovation in finding solutions.
Link - https://github.com/practical-tutorials/project-based-learning?tpclid=facebook.PAAabomU9Szh7vQMnIHyCYix3EcsPObQnrNSn9z57RBOzZ4XlTQ24YW9DY-bY
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Python interview questions.pdf
46.1 KB
I am sharing 'Python interview questions' with you
πPros and Cons of different programming languages
Python:
Pros:
Easy to learn, versatile, large community, many libraries and tools.
Cons:
Slow performance, not as efficient as compiled languages.
JAVA:
Pros:
Portable, secure, large community, many libraries and tools.
Cons:
Can be verbose, not as fast as compiled languages.
C++:
Pros:
High performance, flexible, powerful, large community.
Cons:
Complex, difficult to learn, not as portable as interpreted languages.
C#:
Pros:
Portable, concise, large community, many libraries and tools.
Cons:
Not as fast as C++, not as flexible as Python.
JAVA Script:
Pros:
Easy to learn, versatile, large community, many libraries and tools.
Cons:
Can be slow, not as powerful as compiled languages.
Python:
Pros:
Easy to learn, versatile, large community, many libraries and tools.
Cons:
Slow performance, not as efficient as compiled languages.
JAVA:
Pros:
Portable, secure, large community, many libraries and tools.
Cons:
Can be verbose, not as fast as compiled languages.
C++:
Pros:
High performance, flexible, powerful, large community.
Cons:
Complex, difficult to learn, not as portable as interpreted languages.
C#:
Pros:
Portable, concise, large community, many libraries and tools.
Cons:
Not as fast as C++, not as flexible as Python.
JAVA Script:
Pros:
Easy to learn, versatile, large community, many libraries and tools.
Cons:
Can be slow, not as powerful as compiled languages.
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Deloitte is Hiring for 2024
Role:- Consulting - Internship
Job Location:- Delhi
Qualification:- BE/B.Tech/MCA/MBA
Experience:- Fresher
Apply Link π:-
https://bit.ly/3x4i316
Apply before the link expires
Role:- Consulting - Internship
Job Location:- Delhi
Qualification:- BE/B.Tech/MCA/MBA
Experience:- Fresher
Apply Link π:-
https://bit.ly/3x4i316
Apply before the link expires
β€1
These Universities provide free online courses that can benefit those pursuing engineering careers.
1. Stanford University:
Stanford Online offers complimentary engineering courses such as 'Machine Learning' and 'Introduction to Artificial Intelligence.'
Link: https://online.stanford.edu/courses
2. Massachusetts Institute of Technology (MIT):
MIT OpenCourseWare offers a wide array of no-cost engineering and related courses, including 'Introduction to Computer Science and Programming' and 'Introduction to Electrical Engineering and Computer Science.' Link: https://ocw.mit.edu/index.htm
3. University of California, Berkeley:
UC Berkeley provides free courses on the edX platform, including 'CS50's Introduction to Artificial Intelligence with Python.' Link: https://www.edx.org/school/uc-berkeley
4. Harvard University:
Harvard Online Learning offers free computer science and data science courses, with the most popular being 'CS50's Introduction to Computer Science.
Link: https://online-learning.harvard.edu/
5. Carnegie Mellon University:
Carnegie Mellon's Open Learning Initiative offers no-cost online courses covering subjects such as computer science and programming. Link: https://oli.cmu.edu/
1. Stanford University:
Stanford Online offers complimentary engineering courses such as 'Machine Learning' and 'Introduction to Artificial Intelligence.'
Link: https://online.stanford.edu/courses
2. Massachusetts Institute of Technology (MIT):
MIT OpenCourseWare offers a wide array of no-cost engineering and related courses, including 'Introduction to Computer Science and Programming' and 'Introduction to Electrical Engineering and Computer Science.' Link: https://ocw.mit.edu/index.htm
3. University of California, Berkeley:
UC Berkeley provides free courses on the edX platform, including 'CS50's Introduction to Artificial Intelligence with Python.' Link: https://www.edx.org/school/uc-berkeley
4. Harvard University:
Harvard Online Learning offers free computer science and data science courses, with the most popular being 'CS50's Introduction to Computer Science.
Link: https://online-learning.harvard.edu/
5. Carnegie Mellon University:
Carnegie Mellon's Open Learning Initiative offers no-cost online courses covering subjects such as computer science and programming. Link: https://oli.cmu.edu/
MIT OpenCourseWare
MIT OpenCourseWare | Free Online Course Materials
MIT OpenCourseWare is a web based publication of virtually all MIT course content. OCW is open and available to the world and is a permanent MIT activity
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Here's the link for Microsoft's free web development course with projects
Link - https://learn.microsoft.com/en-us/training/paths/web-development-101/
Link - https://learn.microsoft.com/en-us/training/paths/web-development-101/
Docs
Browse all training - Training
Learn new skills and discover the power of Microsoft products with step-by-step guidance. Start your journey today by exploring our learning paths and modules.
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