Call for papers on AI to AI Journey* conference journal has started!
Prize for the best scientific paper - 1 million roubles!
Selected papers will be published in the scientific journal Doklady Mathematics.
📖 The journal:
• Indexed in the largest bibliographic databases of scientific citations
• Accessible to an international audience and published in the world’s digital libraries
Submit your article by August 20 and get the opportunity not only to publish your research the scientific journal, but also to present it at the AI Journey conference.
Prize for the best article - 1 million roubles!
More detailed information can be found in the Selection Rules -> AI Journey
*AI Journey - a major online conference in the field of AI technologies
Prize for the best scientific paper - 1 million roubles!
Selected papers will be published in the scientific journal Doklady Mathematics.
📖 The journal:
• Indexed in the largest bibliographic databases of scientific citations
• Accessible to an international audience and published in the world’s digital libraries
Submit your article by August 20 and get the opportunity not only to publish your research the scientific journal, but also to present it at the AI Journey conference.
Prize for the best article - 1 million roubles!
More detailed information can be found in the Selection Rules -> AI Journey
*AI Journey - a major online conference in the field of AI technologies
❤1
If you want to Excel at Frontend Development and build stunning user interfaces, master these essential skills:
Core Technologies:
• HTML5 & Semantic Tags – Clean and accessible structure
• CSS3 & Preprocessors (SASS, SCSS) – Advanced styling
• JavaScript ES6+ – Arrow functions, Promises, Async/Await
CSS Frameworks & UI Libraries:
• Bootstrap & Tailwind CSS – Speed up styling
• Flexbox & CSS Grid – Modern layout techniques
• Material UI, Ant Design, Chakra UI – Prebuilt UI components
JavaScript Frameworks & Libraries:
• React.js – Component-based UI development
• Vue.js / Angular – Alternative frontend frameworks
• Next.js & Nuxt.js – Server-side rendering (SSR) & static site generation
State Management:
• Redux / Context API (React) – Manage complex state
• Pinia / Vuex (Vue) – Efficient state handling
API Integration & Data Handling:
• Fetch API & Axios – Consume RESTful APIs
• GraphQL & Apollo Client – Query APIs efficiently
Frontend Optimization & Performance:
• Lazy Loading & Code Splitting – Faster load times
• Web Performance Optimization (Lighthouse, Core Web Vitals)
Version Control & Deployment:
• Git & GitHub – Track changes and collaborate
• CI/CD & Hosting – Deploy with Vercel, Netlify, Firebase
Like it if you need a complete tutorial on all these topics! 👍❤️
Web Development Best Resources
Share with credits: https://t.iss.one/webdevcoursefree
ENJOY LEARNING 👍👍
Core Technologies:
• HTML5 & Semantic Tags – Clean and accessible structure
• CSS3 & Preprocessors (SASS, SCSS) – Advanced styling
• JavaScript ES6+ – Arrow functions, Promises, Async/Await
CSS Frameworks & UI Libraries:
• Bootstrap & Tailwind CSS – Speed up styling
• Flexbox & CSS Grid – Modern layout techniques
• Material UI, Ant Design, Chakra UI – Prebuilt UI components
JavaScript Frameworks & Libraries:
• React.js – Component-based UI development
• Vue.js / Angular – Alternative frontend frameworks
• Next.js & Nuxt.js – Server-side rendering (SSR) & static site generation
State Management:
• Redux / Context API (React) – Manage complex state
• Pinia / Vuex (Vue) – Efficient state handling
API Integration & Data Handling:
• Fetch API & Axios – Consume RESTful APIs
• GraphQL & Apollo Client – Query APIs efficiently
Frontend Optimization & Performance:
• Lazy Loading & Code Splitting – Faster load times
• Web Performance Optimization (Lighthouse, Core Web Vitals)
Version Control & Deployment:
• Git & GitHub – Track changes and collaborate
• CI/CD & Hosting – Deploy with Vercel, Netlify, Firebase
Like it if you need a complete tutorial on all these topics! 👍❤️
Web Development Best Resources
Share with credits: https://t.iss.one/webdevcoursefree
ENJOY LEARNING 👍👍
❤3🥰1
Hey guys,
Here is the list of best curated Telegram Channels for free education 👇👇
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Here is the list of best curated Telegram Channels for free education 👇👇
Free Courses with Certificate
Web Development Free Resources
Data Science & Machine Learning
Programming Free Books
Python Free Courses
Python Interview Resources
Ethical Hacking & Cyber Security
English Speaking & Communication
Stock Marketing & Investment Banking
Coding Projects
Jobs & Internship Opportunities
Learn Digital Marketing
Crack your coding Interviews
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Java Programming Free Resources
Learn Blockchain & Crypto
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💡 Must Have Tools for Programmers
❤2
Here is an A-Z list of essential programming terms:
1. Array: A data structure that stores a collection of elements of the same type in contiguous memory locations.
2. Boolean: A data type that represents true or false values.
3. Conditional Statement: A statement that executes different code based on a condition.
4. Debugging: The process of identifying and fixing errors or bugs in a program.
5. Exception: An event that occurs during the execution of a program that disrupts the normal flow of instructions.
6. Function: A block of code that performs a specific task and can be called multiple times in a program.
7. GUI (Graphical User Interface): A visual way for users to interact with a computer program using graphical elements like windows, buttons, and menus.
8. HTML (Hypertext Markup Language): The standard markup language used to create web pages.
9. Integer: A data type that represents whole numbers without any fractional part.
10. JSON (JavaScript Object Notation): A lightweight data interchange format commonly used for transmitting data between a server and a web application.
11. Loop: A programming construct that allows repeating a block of code multiple times.
12. Method: A function that is associated with an object in object-oriented programming.
13. Null: A special value that represents the absence of a value.
14. Object-Oriented Programming (OOP): A programming paradigm based on the concept of "objects" that encapsulate data and behavior.
15. Pointer: A variable that stores the memory address of another variable.
16. Queue: A data structure that follows the First-In-First-Out (FIFO) principle.
17. Recursion: A programming technique where a function calls itself to solve a problem.
18. String: A data type that represents a sequence of characters.
19. Tuple: An ordered collection of elements, similar to an array but immutable.
20. Variable: A named storage location in memory that holds a value.
21. While Loop: A loop that repeatedly executes a block of code as long as a specified condition is true.
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1. Array: A data structure that stores a collection of elements of the same type in contiguous memory locations.
2. Boolean: A data type that represents true or false values.
3. Conditional Statement: A statement that executes different code based on a condition.
4. Debugging: The process of identifying and fixing errors or bugs in a program.
5. Exception: An event that occurs during the execution of a program that disrupts the normal flow of instructions.
6. Function: A block of code that performs a specific task and can be called multiple times in a program.
7. GUI (Graphical User Interface): A visual way for users to interact with a computer program using graphical elements like windows, buttons, and menus.
8. HTML (Hypertext Markup Language): The standard markup language used to create web pages.
9. Integer: A data type that represents whole numbers without any fractional part.
10. JSON (JavaScript Object Notation): A lightweight data interchange format commonly used for transmitting data between a server and a web application.
11. Loop: A programming construct that allows repeating a block of code multiple times.
12. Method: A function that is associated with an object in object-oriented programming.
13. Null: A special value that represents the absence of a value.
14. Object-Oriented Programming (OOP): A programming paradigm based on the concept of "objects" that encapsulate data and behavior.
15. Pointer: A variable that stores the memory address of another variable.
16. Queue: A data structure that follows the First-In-First-Out (FIFO) principle.
17. Recursion: A programming technique where a function calls itself to solve a problem.
18. String: A data type that represents a sequence of characters.
19. Tuple: An ordered collection of elements, similar to an array but immutable.
20. Variable: A named storage location in memory that holds a value.
21. While Loop: A loop that repeatedly executes a block of code as long as a specified condition is true.
Best Programming Resources: https://topmate.io/coding/898340
Join for more: https://t.iss.one/programming_guide
ENJOY LEARNING 👍👍
❤1👍1🥰1
Working under a bad tech lead can slow you down in your career, even if you are the most talented
Here’s what you should do if you're stuck with a bad tech lead:
Ineffective Tech Lead:
- downplays the contributions of their team
- creates deadlines without talking to the team
- views team members as a tool to build and code
- doesn’t trust their team members to do their jobs
- gives no space or opportunities for personal / skill development
Effective Tech lead:
- sets a clear vision and direction
- communicates with the team & sets realistic goals
- empowers you to make decisions and take ownership
- inspires and helps you achieve your career milestones
- always looks to add value by sharing their knowledge and coaching
I've always grown the most when I've worked with the latter.
But I also have experience working with the former.
If you are in a team with a bad tech lead, it’s tough, I understand.
Here’s what you can do:
➥don’t waste your energy worrying about them
➥focus on your growth and what you can do in the environment
➥focus and try to fill the gap your lead has created by their behaviors
➥talk to your manager and share how you're feeling rather than complain about the lead
➥try and understand why they are behaving the way they behave, what’s important for them
And the most important:
Don’t get sucked into this behavior and become like one!
You will face both types of people in your career:
Some will teach you how to do things, and others will teach you how not to do things!
Coding Projects:👇
https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
ENJOY LEARNING 👍👍
Here’s what you should do if you're stuck with a bad tech lead:
Ineffective Tech Lead:
- downplays the contributions of their team
- creates deadlines without talking to the team
- views team members as a tool to build and code
- doesn’t trust their team members to do their jobs
- gives no space or opportunities for personal / skill development
Effective Tech lead:
- sets a clear vision and direction
- communicates with the team & sets realistic goals
- empowers you to make decisions and take ownership
- inspires and helps you achieve your career milestones
- always looks to add value by sharing their knowledge and coaching
I've always grown the most when I've worked with the latter.
But I also have experience working with the former.
If you are in a team with a bad tech lead, it’s tough, I understand.
Here’s what you can do:
➥don’t waste your energy worrying about them
➥focus on your growth and what you can do in the environment
➥focus and try to fill the gap your lead has created by their behaviors
➥talk to your manager and share how you're feeling rather than complain about the lead
➥try and understand why they are behaving the way they behave, what’s important for them
And the most important:
Don’t get sucked into this behavior and become like one!
You will face both types of people in your career:
Some will teach you how to do things, and others will teach you how not to do things!
Coding Projects:👇
https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502
ENJOY LEARNING 👍👍
❤3
Git Commands
🛠 git init – Initialize a new Git repository
📥 git clone <repo> – Clone a repository
📊 git status – Check the status of your repository
➕ git add <file> – Add a file to the staging area
📝 git commit -m "message" – Commit changes with a message
🚀 git push – Push changes to a remote repository
⬇️ git pull – Fetch and merge changes from a remote repository
Branching
📌 git branch – List all branches
🌱 git branch <name> – Create a new branch
🔄 git checkout <branch> – Switch to a branch
🔗 git merge <branch> – Merge a branch into the current branch
⚡️ git rebase <branch> – Apply commits on top of another branch
Undo & Fix Mistakes
⏪ git reset --soft HEAD~1 – Undo the last commit but keep changes
❌ git reset --hard HEAD~1 – Undo the last commit and discard changes
🔄 git revert <commit> – Create a new commit that undoes a specific commit
Logs & History
📖 git log – Show commit history
🌐 git log --oneline --graph --all – View commit history in a simple graph
Stashing
📥 git stash – Save changes without committing
🎭 git stash pop – Apply stashed changes and remove them from stash
Remote & Collaboration
🌍 git remote -v – View remote repositories
📡 git fetch – Fetch changes without merging
🕵️ git diff – Compare changes
Don’t forget to react ❤️ if you’d like to see more content like this!
🛠 git init – Initialize a new Git repository
📥 git clone <repo> – Clone a repository
📊 git status – Check the status of your repository
➕ git add <file> – Add a file to the staging area
📝 git commit -m "message" – Commit changes with a message
🚀 git push – Push changes to a remote repository
⬇️ git pull – Fetch and merge changes from a remote repository
Branching
📌 git branch – List all branches
🌱 git branch <name> – Create a new branch
🔄 git checkout <branch> – Switch to a branch
🔗 git merge <branch> – Merge a branch into the current branch
⚡️ git rebase <branch> – Apply commits on top of another branch
Undo & Fix Mistakes
⏪ git reset --soft HEAD~1 – Undo the last commit but keep changes
❌ git reset --hard HEAD~1 – Undo the last commit and discard changes
🔄 git revert <commit> – Create a new commit that undoes a specific commit
Logs & History
📖 git log – Show commit history
🌐 git log --oneline --graph --all – View commit history in a simple graph
Stashing
📥 git stash – Save changes without committing
🎭 git stash pop – Apply stashed changes and remove them from stash
Remote & Collaboration
🌍 git remote -v – View remote repositories
📡 git fetch – Fetch changes without merging
🕵️ git diff – Compare changes
Don’t forget to react ❤️ if you’d like to see more content like this!
❤5👌2
🚀 Complete Roadmap to Become a Data Scientist in 5 Months
📅 Week 1-2: Fundamentals
✅ Day 1-3: Introduction to Data Science, its applications, and roles.
✅ Day 4-7: Brush up on Python programming 🐍.
✅ Day 8-10: Learn basic statistics 📊 and probability 🎲.
🔍 Week 3-4: Data Manipulation & Visualization
📝 Day 11-15: Master Pandas for data manipulation.
📈 Day 16-20: Learn Matplotlib & Seaborn for data visualization.
🤖 Week 5-6: Machine Learning Foundations
🔬 Day 21-25: Introduction to scikit-learn.
📊 Day 26-30: Learn Linear & Logistic Regression.
🏗 Week 7-8: Advanced Machine Learning
🌳 Day 31-35: Explore Decision Trees & Random Forests.
📌 Day 36-40: Learn Clustering (K-Means, DBSCAN) & Dimensionality Reduction.
🧠 Week 9-10: Deep Learning
🤖 Day 41-45: Basics of Neural Networks with TensorFlow/Keras.
📸 Day 46-50: Learn CNNs & RNNs for image & text data.
🏛 Week 11-12: Data Engineering
🗄 Day 51-55: Learn SQL & Databases.
🧹 Day 56-60: Data Preprocessing & Cleaning.
📊 Week 13-14: Model Evaluation & Optimization
📏 Day 61-65: Learn Cross-validation & Hyperparameter Tuning.
📉 Day 66-70: Understand Evaluation Metrics (Accuracy, Precision, Recall, F1-score).
🏗 Week 15-16: Big Data & Tools
🐘 Day 71-75: Introduction to Big Data Technologies (Hadoop, Spark).
☁️ Day 76-80: Learn Cloud Computing (AWS, GCP, Azure).
🚀 Week 17-18: Deployment & Production
🛠 Day 81-85: Deploy models using Flask or FastAPI.
📦 Day 86-90: Learn Docker & Cloud Deployment (AWS, Heroku).
🎯 Week 19-20: Specialization
📝 Day 91-95: Choose NLP or Computer Vision, based on your interest.
🏆 Week 21-22: Projects & Portfolio
📂 Day 96-100: Work on Personal Data Science Projects.
💬 Week 23-24: Soft Skills & Networking
🎤 Day 101-105: Improve Communication & Presentation Skills.
🌐 Day 106-110: Attend Online Meetups & Forums.
🎯 Week 25-26: Interview Preparation
💻 Day 111-115: Practice Coding Interviews (LeetCode, HackerRank).
📂 Day 116-120: Review your projects & prepare for discussions.
👨💻 Week 27-28: Apply for Jobs
📩 Day 121-125: Start applying for Entry-Level Data Scientist positions.
🎤 Week 29-30: Interviews
📝 Day 126-130: Attend Interviews & Practice Whiteboard Problems.
🔄 Week 31-32: Continuous Learning
📰 Day 131-135: Stay updated with the Latest Data Science Trends.
🏆 Week 33-34: Accepting Offers
📝 Day 136-140: Evaluate job offers & Negotiate Your Salary.
🏢 Week 35-36: Settling In
🎯 Day 141-150: Start your New Data Science Job, adapt & keep learning!
🎉 Enjoy Learning & Build Your Dream Career in Data Science! 🚀🔥
📅 Week 1-2: Fundamentals
✅ Day 1-3: Introduction to Data Science, its applications, and roles.
✅ Day 4-7: Brush up on Python programming 🐍.
✅ Day 8-10: Learn basic statistics 📊 and probability 🎲.
🔍 Week 3-4: Data Manipulation & Visualization
📝 Day 11-15: Master Pandas for data manipulation.
📈 Day 16-20: Learn Matplotlib & Seaborn for data visualization.
🤖 Week 5-6: Machine Learning Foundations
🔬 Day 21-25: Introduction to scikit-learn.
📊 Day 26-30: Learn Linear & Logistic Regression.
🏗 Week 7-8: Advanced Machine Learning
🌳 Day 31-35: Explore Decision Trees & Random Forests.
📌 Day 36-40: Learn Clustering (K-Means, DBSCAN) & Dimensionality Reduction.
🧠 Week 9-10: Deep Learning
🤖 Day 41-45: Basics of Neural Networks with TensorFlow/Keras.
📸 Day 46-50: Learn CNNs & RNNs for image & text data.
🏛 Week 11-12: Data Engineering
🗄 Day 51-55: Learn SQL & Databases.
🧹 Day 56-60: Data Preprocessing & Cleaning.
📊 Week 13-14: Model Evaluation & Optimization
📏 Day 61-65: Learn Cross-validation & Hyperparameter Tuning.
📉 Day 66-70: Understand Evaluation Metrics (Accuracy, Precision, Recall, F1-score).
🏗 Week 15-16: Big Data & Tools
🐘 Day 71-75: Introduction to Big Data Technologies (Hadoop, Spark).
☁️ Day 76-80: Learn Cloud Computing (AWS, GCP, Azure).
🚀 Week 17-18: Deployment & Production
🛠 Day 81-85: Deploy models using Flask or FastAPI.
📦 Day 86-90: Learn Docker & Cloud Deployment (AWS, Heroku).
🎯 Week 19-20: Specialization
📝 Day 91-95: Choose NLP or Computer Vision, based on your interest.
🏆 Week 21-22: Projects & Portfolio
📂 Day 96-100: Work on Personal Data Science Projects.
💬 Week 23-24: Soft Skills & Networking
🎤 Day 101-105: Improve Communication & Presentation Skills.
🌐 Day 106-110: Attend Online Meetups & Forums.
🎯 Week 25-26: Interview Preparation
💻 Day 111-115: Practice Coding Interviews (LeetCode, HackerRank).
📂 Day 116-120: Review your projects & prepare for discussions.
👨💻 Week 27-28: Apply for Jobs
📩 Day 121-125: Start applying for Entry-Level Data Scientist positions.
🎤 Week 29-30: Interviews
📝 Day 126-130: Attend Interviews & Practice Whiteboard Problems.
🔄 Week 31-32: Continuous Learning
📰 Day 131-135: Stay updated with the Latest Data Science Trends.
🏆 Week 33-34: Accepting Offers
📝 Day 136-140: Evaluate job offers & Negotiate Your Salary.
🏢 Week 35-36: Settling In
🎯 Day 141-150: Start your New Data Science Job, adapt & keep learning!
🎉 Enjoy Learning & Build Your Dream Career in Data Science! 🚀🔥
❤2🥰1
Common Programming Interview Questions
How do you reverse a string?
How do you determine if a string is a palindrome?
How do you calculate the number of numerical digits in a string?
How do you find the count for the occurrence of a particular character in a string?
How do you find the non-matching characters in a string?
How do you find out if the two given strings are anagrams?
How do you calculate the number of vowels and consonants in a string?
How do you total all of the matching integer elements in an array?
How do you reverse an array?
How do you find the maximum element in an array?
How do you sort an array of integers in ascending order?
How do you print a Fibonacci sequence using recursion?
How do you calculate the sum of two integers?
How do you find the average of numbers in a list?
How do you check if an integer is even or odd?
How do you find the middle element of a linked list?
How do you remove a loop in a linked list?
How do you merge two sorted linked lists?
How do you implement binary search to find an element in a sorted array?
How do you print a binary tree in vertical order?
Conceptual Coding Interview Questions
What is a data structure?
What is an array?
What is a linked list?
What is the difference between an array and a linked list?
What is LIFO?
What is FIFO?
What is a stack?
What are binary trees?
What are binary search trees?
What is object-oriented programming?
What is the purpose of a loop in programming?
What is a conditional statement?
What is debugging?
What is recursion?
What are the differences between linear and non-linear data structures?
General Coding Interview Questions
What programming languages do you have experience working with?
Describe a time you faced a challenge in a project you were working on and how you overcame it.
Walk me through a project you’re currently or have recently worked on.
Give an example of a project you worked on where you had to learn a new programming language or technology. How did you go about learning it?
How do you ensure your code is readable by other developers?
What are your interests outside of programming?
How do you keep your skills sharp and up to date?
How do you collaborate on projects with non-technical team members?
Tell me about a time when you had to explain a complex technical concept to a non-technical team member.
How do you get started on a new coding project?
Best Programming Resources: https://topmate.io/coding/886839
Join for more: https://t.iss.one/programming_guide
ENJOY LEARNING 👍👍
How do you reverse a string?
How do you determine if a string is a palindrome?
How do you calculate the number of numerical digits in a string?
How do you find the count for the occurrence of a particular character in a string?
How do you find the non-matching characters in a string?
How do you find out if the two given strings are anagrams?
How do you calculate the number of vowels and consonants in a string?
How do you total all of the matching integer elements in an array?
How do you reverse an array?
How do you find the maximum element in an array?
How do you sort an array of integers in ascending order?
How do you print a Fibonacci sequence using recursion?
How do you calculate the sum of two integers?
How do you find the average of numbers in a list?
How do you check if an integer is even or odd?
How do you find the middle element of a linked list?
How do you remove a loop in a linked list?
How do you merge two sorted linked lists?
How do you implement binary search to find an element in a sorted array?
How do you print a binary tree in vertical order?
Conceptual Coding Interview Questions
What is a data structure?
What is an array?
What is a linked list?
What is the difference between an array and a linked list?
What is LIFO?
What is FIFO?
What is a stack?
What are binary trees?
What are binary search trees?
What is object-oriented programming?
What is the purpose of a loop in programming?
What is a conditional statement?
What is debugging?
What is recursion?
What are the differences between linear and non-linear data structures?
General Coding Interview Questions
What programming languages do you have experience working with?
Describe a time you faced a challenge in a project you were working on and how you overcame it.
Walk me through a project you’re currently or have recently worked on.
Give an example of a project you worked on where you had to learn a new programming language or technology. How did you go about learning it?
How do you ensure your code is readable by other developers?
What are your interests outside of programming?
How do you keep your skills sharp and up to date?
How do you collaborate on projects with non-technical team members?
Tell me about a time when you had to explain a complex technical concept to a non-technical team member.
How do you get started on a new coding project?
Best Programming Resources: https://topmate.io/coding/886839
Join for more: https://t.iss.one/programming_guide
ENJOY LEARNING 👍👍
❤5
- Learn JavaScript before React.
- Learn Git before CI/CD pipelines.
- Learn Docker before Kubernetes.
- Learn Vanilla DOM before jQuery
- Learn REST APIs before GraphQL.
- Learn Linux Basics before Docker.
- Learn Algorithms before LeetCode
- Learn HTML/CSS before JavaScript.
- Learn TCP/IP Basics before WebSocket
- Learn Data Structures before Algorithms.
- Learn Monolithic before Microservices Architecture.
- Learn SQL before ORMs (Object-Relational Mapping).
- Learn Manual Testing before Test-Driven Development
- Learn MVC Pattern before MVVM
(Model-View-ViewModel) or SPA (Single-Page Application) frameworks.
It all starts with the basics & fundamentals.
Have the patience to master them and then move to languages & fundamentals.
Good core knowledge allows you to adapt & learn any technologies you need to do your job.
I have curated Best Web Development Resources: https://topmate.io/coding/930165
ENJOY LEARNING 👍👍
- Learn Git before CI/CD pipelines.
- Learn Docker before Kubernetes.
- Learn Vanilla DOM before jQuery
- Learn REST APIs before GraphQL.
- Learn Linux Basics before Docker.
- Learn Algorithms before LeetCode
- Learn HTML/CSS before JavaScript.
- Learn TCP/IP Basics before WebSocket
- Learn Data Structures before Algorithms.
- Learn Monolithic before Microservices Architecture.
- Learn SQL before ORMs (Object-Relational Mapping).
- Learn Manual Testing before Test-Driven Development
- Learn MVC Pattern before MVVM
(Model-View-ViewModel) or SPA (Single-Page Application) frameworks.
It all starts with the basics & fundamentals.
Have the patience to master them and then move to languages & fundamentals.
Good core knowledge allows you to adapt & learn any technologies you need to do your job.
I have curated Best Web Development Resources: https://topmate.io/coding/930165
ENJOY LEARNING 👍👍
❤4
To join Microsoft as a Data Engineer or Software Development Engineer (SDE), here are the key skills you should focus on preparing:
1. Programming Languages
- Python: Essential for data manipulation and ETL tasks.
- SQL: Strong command over writing queries for data retrieval, manipulation, and performance tuning.
- Java/Scala: Important for working with big data frameworks and building scalable systems.
2. Big Data Technologies
- Apache Hadoop: Understanding of distributed data storage and processing.
- Apache Spark: Experience with batch and real-time data processing.
- Kafka: Knowledge of data streaming technologies.
3. Cloud Platforms
- Microsoft Azure: Especially services like Azure Data Factory, Azure Databricks, Azure Synapse, and Azure Blob Storage.
- AWS or Google Cloud: Familiarity with cloud infrastructure is valuable, but Azure expertise will be a plus.
4. ETL Tools and Data Pipelines
- Understanding how to build and manage ETL (Extract, Transform, Load) pipelines.
- Knowledge of tools like Airflow, Talend, Azure Data Factory, or similar platforms.
5. Databases and Data Warehousing
- Relational Databases: MySQL, PostgreSQL, SQL Server.
- NoSQL Databases: MongoDB, Cassandra, DynamoDB.
- Data Warehousing: Familiarity with tools like Snowflake, Redshift, or Azure Synapse.
6. Version Control and CI/CD
- Git: Proficient in version control systems.
- Continuous Integration/Continuous Deployment (CI/CD): Familiarity with Jenkins, GitHub Actions, or Azure DevOps.
7. Data Modeling and Architecture
- Experience in designing scalable data models and database architectures.
- Understanding Data Lakes and Data Warehouses concepts.
8. System Design & Algorithms
- Knowledge of data structures and algorithms for solving system design problems.
- Ability to design large-scale distributed systems, an important part of the interview process.
9. Analytics Tools
- Power BI or Tableau: Useful for data visualization.
- Pandas, NumPy for data manipulation in Python.
10. Problem-Solving and Coding
Focus on practicing on platforms like LeetCode, HackerRank, or Codeforces to improve problem-solving skills, which are critical for technical interviews.
11. Soft Skills
- Collaboration and Communication: Working in teams and effectively communicating technical concepts.
- Adaptability: Ability to work in a fast-paced and evolving technical environment.
By preparing in these areas, you'll be in a strong position to apply for roles at Microsoft, especially in data engineering or SDE roles. Keep Learning!!
1. Programming Languages
- Python: Essential for data manipulation and ETL tasks.
- SQL: Strong command over writing queries for data retrieval, manipulation, and performance tuning.
- Java/Scala: Important for working with big data frameworks and building scalable systems.
2. Big Data Technologies
- Apache Hadoop: Understanding of distributed data storage and processing.
- Apache Spark: Experience with batch and real-time data processing.
- Kafka: Knowledge of data streaming technologies.
3. Cloud Platforms
- Microsoft Azure: Especially services like Azure Data Factory, Azure Databricks, Azure Synapse, and Azure Blob Storage.
- AWS or Google Cloud: Familiarity with cloud infrastructure is valuable, but Azure expertise will be a plus.
4. ETL Tools and Data Pipelines
- Understanding how to build and manage ETL (Extract, Transform, Load) pipelines.
- Knowledge of tools like Airflow, Talend, Azure Data Factory, or similar platforms.
5. Databases and Data Warehousing
- Relational Databases: MySQL, PostgreSQL, SQL Server.
- NoSQL Databases: MongoDB, Cassandra, DynamoDB.
- Data Warehousing: Familiarity with tools like Snowflake, Redshift, or Azure Synapse.
6. Version Control and CI/CD
- Git: Proficient in version control systems.
- Continuous Integration/Continuous Deployment (CI/CD): Familiarity with Jenkins, GitHub Actions, or Azure DevOps.
7. Data Modeling and Architecture
- Experience in designing scalable data models and database architectures.
- Understanding Data Lakes and Data Warehouses concepts.
8. System Design & Algorithms
- Knowledge of data structures and algorithms for solving system design problems.
- Ability to design large-scale distributed systems, an important part of the interview process.
9. Analytics Tools
- Power BI or Tableau: Useful for data visualization.
- Pandas, NumPy for data manipulation in Python.
10. Problem-Solving and Coding
Focus on practicing on platforms like LeetCode, HackerRank, or Codeforces to improve problem-solving skills, which are critical for technical interviews.
11. Soft Skills
- Collaboration and Communication: Working in teams and effectively communicating technical concepts.
- Adaptability: Ability to work in a fast-paced and evolving technical environment.
By preparing in these areas, you'll be in a strong position to apply for roles at Microsoft, especially in data engineering or SDE roles. Keep Learning!!
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