๐ ๐๐ฅ๐๐ ๐๐ฟ๐ฒ๐๐ต๐ฒ๐ฟ ๐๐ถ๐ฟ๐ถ๐ป๐ด ๐๐ฟ๐ถ๐๐ฒ | ๐ง๐ฒ๐ฐ๐ต ๐ฅ๐ผ๐น๐ฒ๐ ๐จ๐ฝ ๐๐ผ โน๐ญ๐ฎ ๐๐ฃ๐!๐ฅ
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โค1
๐ ๐๐๐ ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐
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โค2๐1
๐ ๐ง๐ผ๐ฝ ๐ฃ๐ผ๐๐ฒ๐ฟ ๐๐ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ค๐๐ฒ๐๐๐ถ๐ผ๐ป๐ ๐๐๐ธ๐ฒ๐ฑ ๐ฏ๐ ๐๐ฒ๐ฎ๐ฑ๐ถ๐ป๐ด ๐๐ผ๐บ๐ฝ๐ฎ๐ป๐ถ๐ฒ๐ ๐
๐ผ Companies hiring Power BI professionals include: Microsoft, Deloitte, Accenture, Capgemini, TCS, Infosys, Cognizant, EY, PwC, KPMG, IBM, Wipro, and many more.
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โค1
๐ Complete SQL Roadmap ๐๐ฅ
๐ง STEP 1: Learn SQL Basics
โ What is SQL?
โ Databases & Tables
โ SELECT Statement
โ WHERE Clause
โ ORDER BY
๐ Databases to Practice:
โ MySQL
โ PostgreSQL
โ SQL Server
๐ STEP 2: Learn Filtering & Aggregation
โ DISTINCT
โ LIMIT & TOP
โ COUNT, SUM, AVG
โ MIN & MAX
โ GROUP BY & HAVING
โก STEP 3: Master SQL JOINS
โ INNER JOIN
โ LEFT JOIN
โ RIGHT JOIN
โ FULL JOIN
โ SELF JOIN
๐ Concepts to Learn:
โ Primary Key
โ Foreign Key
โ Relationships
๐ STEP 4: Learn Advanced SQL
โ Subqueries
โ Common Table Expressions (CTEs)
โ CASE WHEN
โ UNION & UNION ALL
โ EXISTS & IN
๐ฅ STEP 5: Learn Window Functions
โ ROW_NUMBER()
โ RANK()
โ DENSE_RANK()
โ LEAD() & LAG()
โ PARTITION BY
๐ง STEP 6: Learn Database Design
โ Normalization
โ Schema Design
โ Indexing
โ Constraints
โ Data Integrity
โ๏ธ STEP 7: Learn SQL Optimization
โ Query Optimization
โ Execution Plans
โ Index Optimization
โ Performance Tuning
๐ Tools to Learn:
โ DBeaver
โ pgAdmin
โ MySQL Workbench
๐ STEP 8: Build Real SQL Projects
โ Sales Database Analysis
โ Employee Management System
โ E-commerce Database
โ Customer Analytics
โ Inventory Management
๐ก SQL Notes: https://whatsapp.com/channel/0029VbCyzS02ZjCwoShXXc2j
๐ฌ Tap โค๏ธ if this helped you!
๐ง STEP 1: Learn SQL Basics
โ What is SQL?
โ Databases & Tables
โ SELECT Statement
โ WHERE Clause
โ ORDER BY
๐ Databases to Practice:
โ MySQL
โ PostgreSQL
โ SQL Server
๐ STEP 2: Learn Filtering & Aggregation
โ DISTINCT
โ LIMIT & TOP
โ COUNT, SUM, AVG
โ MIN & MAX
โ GROUP BY & HAVING
โก STEP 3: Master SQL JOINS
โ INNER JOIN
โ LEFT JOIN
โ RIGHT JOIN
โ FULL JOIN
โ SELF JOIN
๐ Concepts to Learn:
โ Primary Key
โ Foreign Key
โ Relationships
๐ STEP 4: Learn Advanced SQL
โ Subqueries
โ Common Table Expressions (CTEs)
โ CASE WHEN
โ UNION & UNION ALL
โ EXISTS & IN
๐ฅ STEP 5: Learn Window Functions
โ ROW_NUMBER()
โ RANK()
โ DENSE_RANK()
โ LEAD() & LAG()
โ PARTITION BY
๐ง STEP 6: Learn Database Design
โ Normalization
โ Schema Design
โ Indexing
โ Constraints
โ Data Integrity
โ๏ธ STEP 7: Learn SQL Optimization
โ Query Optimization
โ Execution Plans
โ Index Optimization
โ Performance Tuning
๐ Tools to Learn:
โ DBeaver
โ pgAdmin
โ MySQL Workbench
๐ STEP 8: Build Real SQL Projects
โ Sales Database Analysis
โ Employee Management System
โ E-commerce Database
โ Customer Analytics
โ Inventory Management
๐ก SQL Notes: https://whatsapp.com/channel/0029VbCyzS02ZjCwoShXXc2j
๐ฌ Tap โค๏ธ if this helped you!
โค4
๐๐ฅ๐๐ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ & ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐
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๐น Introduction to Data Science โ Cisco
๐น Python for Data Science โ IBM
๐น Azure Data Fundamentals โ Microsoft
๐น Google Analytics โ Google
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๐ฅ Start learning today and upgrade your resume with job-ready Data & Analytics skills!
๐ Top Coding Interview Concepts โ Part 4 ๐ป๐ฅ
31. Polymorphism
The ability of the same method or interface to behave differently depending on the object using it.
Example: Different classes can implement the same draw() method in different ways.
32. Abstraction
Hiding unnecessary implementation details and exposing only the essential functionality.
Example: You use a print() function without needing to know how the printer works internally.
33. Constructor
A special method that is automatically called when an object is created and is typically used to initialize its properties.
Example: A Car constructor can set the car's model and color when the object is created.
34. Interface
A contract that defines methods or behaviors a class must provide, without necessarily defining how they are implemented.
Example: A Payment interface may require pay() to be implemented by different payment methods.
35. Method Overloading
Defining multiple methods with the same name but different parameters.
Example: An add() method can accept two numbers or three numbers, depending on the language's support for overloading.
36. Method Overriding
When a child class provides its own implementation of a method already defined in its parent class.
Example: Dog can override an Animal class's sound() method.
37. Pointer
A variable that stores the memory address of another variable or object.
Example: Pointers are commonly used in C and C++ for direct memory manipulation.
38. Reference
A way to refer to an existing object or value without necessarily creating a separate copy of it.
Example: Multiple variables can reference the same object in memory.
39. Memory Management
The process of allocating, using, and releasing memory efficiently during program execution.
Example: Garbage collection automatically removes objects that are no longer needed in languages such as Java and Python.
40. Garbage Collection
An automatic memory-management process that identifies and frees memory occupied by objects that are no longer reachable or needed.
๐ฌ Double Tap โค๏ธ for Part 5!
31. Polymorphism
The ability of the same method or interface to behave differently depending on the object using it.
Example: Different classes can implement the same draw() method in different ways.
32. Abstraction
Hiding unnecessary implementation details and exposing only the essential functionality.
Example: You use a print() function without needing to know how the printer works internally.
33. Constructor
A special method that is automatically called when an object is created and is typically used to initialize its properties.
Example: A Car constructor can set the car's model and color when the object is created.
34. Interface
A contract that defines methods or behaviors a class must provide, without necessarily defining how they are implemented.
Example: A Payment interface may require pay() to be implemented by different payment methods.
35. Method Overloading
Defining multiple methods with the same name but different parameters.
Example: An add() method can accept two numbers or three numbers, depending on the language's support for overloading.
36. Method Overriding
When a child class provides its own implementation of a method already defined in its parent class.
Example: Dog can override an Animal class's sound() method.
37. Pointer
A variable that stores the memory address of another variable or object.
Example: Pointers are commonly used in C and C++ for direct memory manipulation.
38. Reference
A way to refer to an existing object or value without necessarily creating a separate copy of it.
Example: Multiple variables can reference the same object in memory.
39. Memory Management
The process of allocating, using, and releasing memory efficiently during program execution.
Example: Garbage collection automatically removes objects that are no longer needed in languages such as Java and Python.
40. Garbage Collection
An automatic memory-management process that identifies and frees memory occupied by objects that are no longer reachable or needed.
๐ฌ Double Tap โค๏ธ for Part 5!
โค1
๐ ๐ ๐ถ๐ฐ๐ฟ๐ผ๐๐ผ๐ณ๐ ๐๐ฅ๐๐ ๐๐ฎ๐๐ฎ ๐๐ป๐ฎ๐น๐๐๐ถ๐ฐ๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐๐ฅ
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๐ฅ Start learning today and take your first step toward a career in Data Analytics & Business Intelligence
Build in-demand Data Analytics skills with Microsoft and strengthen your resume with FREE learning opportunities.
โ Beginner-Friendly
โ Learn at Your Own Pace
โ Build Job-Ready Data Skills
โ Improve Your Resume & LinkedIn Profile
โ Prepare for Data Analyst & BI Careers
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๐ฅ Start learning today and take your first step toward a career in Data Analytics & Business Intelligence
โค1
๐ ๐๐ฅ๐๐ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐ ๐ฏ๐ ๐ง๐ผ๐ฝ ๐๐ผ๐บ๐ฝ๐ฎ๐ป๐ถ๐ฒ๐๐ฅ
Get FREE access to company-specific interview kits, previous questions, preparation strategies, and important resources! ๐
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๐ share it with friends preparing for placements
Get FREE access to company-specific interview kits, previous questions, preparation strategies, and important resources! ๐
Google :- https://pdlink.in/4xtUyIG
Amazon :- https://pdlink.in/45Q0YWR
Microsoft :- https://pdlink.in/3Up1bha
Wipro :- https://pdlink.in/4fMo1rA
Infosys :- https://pdlink.in/3TRn8p0
๐ share it with friends preparing for placements
If you want to get a job as a machine learning engineer, donโt start by diving into the hottest libraries like PyTorch,TensorFlow, Langchain, etc.
Yes, you might hear a lot about them or some other trending technology of the year...but guess what!
Technologies evolve rapidly, especially in the age of AI, but core concepts are always seen as more valuable than expertise in any particular tool. Stop trying to perform a brain surgery without knowing anything about human anatomy.
Instead, here are basic skills that will get you further than mastering any framework:
๐๐๐ญ๐ก๐๐ฆ๐๐ญ๐ข๐๐ฌ ๐๐ง๐ ๐๐ญ๐๐ญ๐ข๐ฌ๐ญ๐ข๐๐ฌ - My first exposure to probability and statistics was in college, and it felt abstract at the time, but these concepts are the backbone of ML.
You can start here: Khan Academy Statistics and Probability - https://www.khanacademy.org/math/statistics-probability
๐๐ข๐ง๐๐๐ซ ๐๐ฅ๐ ๐๐๐ซ๐ ๐๐ง๐ ๐๐๐ฅ๐๐ฎ๐ฅ๐ฎ๐ฌ - Concepts like matrices, vectors, eigenvalues, and derivatives are fundamental to understanding how ml algorithms work. These are used in everything from simple regression to deep learning.
๐๐ซ๐จ๐ ๐ซ๐๐ฆ๐ฆ๐ข๐ง๐ - Should you learn Python, Rust, R, Julia, JavaScript, etc.? The best advice is to pick the language that is most frequently used for the type of work you want to do. I started with Python due to its simplicity and extensive library support, and it remains my go-to language for machine learning tasks.
You can start here: Automate the Boring Stuff with Python - https://automatetheboringstuff.com/
๐๐ฅ๐ ๐จ๐ซ๐ข๐ญ๐ก๐ฆ ๐๐ง๐๐๐ซ๐ฌ๐ญ๐๐ง๐๐ข๐ง๐ - Understand the fundamental algorithms before jumping to deep learning. This includes linear regression, decision trees, SVMs, and clustering algorithms.
๐๐๐ฉ๐ฅ๐จ๐ฒ๐ฆ๐๐ง๐ญ ๐๐ง๐ ๐๐ซ๐จ๐๐ฎ๐๐ญ๐ข๐จ๐ง:
Knowing how to take a model from development to production is invaluable. This includes understanding APIs, model optimization, and monitoring. Tools like Docker and Flask are often used in this process.
๐๐ฅ๐จ๐ฎ๐ ๐๐จ๐ฆ๐ฉ๐ฎ๐ญ๐ข๐ง๐ ๐๐ง๐ ๐๐ข๐ ๐๐๐ญ๐:
Familiarity with cloud platforms (AWS, Google Cloud, Azure) and big data tools (Spark) is increasingly important as datasets grow larger. These skills help you manage and process large-scale data efficiently.
You can start here: Google Cloud Machine Learning - https://cloud.google.com/learn/training/machinelearning-ai
I love frameworks and libraries, and they can make anyone's job easier.
But the more solid your foundation, the easier it will be to pick up any new technologies and actually validate whether they solve your problems.
Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
All the best ๐๐
Yes, you might hear a lot about them or some other trending technology of the year...but guess what!
Technologies evolve rapidly, especially in the age of AI, but core concepts are always seen as more valuable than expertise in any particular tool. Stop trying to perform a brain surgery without knowing anything about human anatomy.
Instead, here are basic skills that will get you further than mastering any framework:
๐๐๐ญ๐ก๐๐ฆ๐๐ญ๐ข๐๐ฌ ๐๐ง๐ ๐๐ญ๐๐ญ๐ข๐ฌ๐ญ๐ข๐๐ฌ - My first exposure to probability and statistics was in college, and it felt abstract at the time, but these concepts are the backbone of ML.
You can start here: Khan Academy Statistics and Probability - https://www.khanacademy.org/math/statistics-probability
๐๐ข๐ง๐๐๐ซ ๐๐ฅ๐ ๐๐๐ซ๐ ๐๐ง๐ ๐๐๐ฅ๐๐ฎ๐ฅ๐ฎ๐ฌ - Concepts like matrices, vectors, eigenvalues, and derivatives are fundamental to understanding how ml algorithms work. These are used in everything from simple regression to deep learning.
๐๐ซ๐จ๐ ๐ซ๐๐ฆ๐ฆ๐ข๐ง๐ - Should you learn Python, Rust, R, Julia, JavaScript, etc.? The best advice is to pick the language that is most frequently used for the type of work you want to do. I started with Python due to its simplicity and extensive library support, and it remains my go-to language for machine learning tasks.
You can start here: Automate the Boring Stuff with Python - https://automatetheboringstuff.com/
๐๐ฅ๐ ๐จ๐ซ๐ข๐ญ๐ก๐ฆ ๐๐ง๐๐๐ซ๐ฌ๐ญ๐๐ง๐๐ข๐ง๐ - Understand the fundamental algorithms before jumping to deep learning. This includes linear regression, decision trees, SVMs, and clustering algorithms.
๐๐๐ฉ๐ฅ๐จ๐ฒ๐ฆ๐๐ง๐ญ ๐๐ง๐ ๐๐ซ๐จ๐๐ฎ๐๐ญ๐ข๐จ๐ง:
Knowing how to take a model from development to production is invaluable. This includes understanding APIs, model optimization, and monitoring. Tools like Docker and Flask are often used in this process.
๐๐ฅ๐จ๐ฎ๐ ๐๐จ๐ฆ๐ฉ๐ฎ๐ญ๐ข๐ง๐ ๐๐ง๐ ๐๐ข๐ ๐๐๐ญ๐:
Familiarity with cloud platforms (AWS, Google Cloud, Azure) and big data tools (Spark) is increasingly important as datasets grow larger. These skills help you manage and process large-scale data efficiently.
You can start here: Google Cloud Machine Learning - https://cloud.google.com/learn/training/machinelearning-ai
I love frameworks and libraries, and they can make anyone's job easier.
But the more solid your foundation, the easier it will be to pick up any new technologies and actually validate whether they solve your problems.
Best Data Science & Machine Learning Resources: https://topmate.io/coding/914624
All the best ๐๐
โค1
๐ ๐๐ผ๐ผ๐ด๐น๐ฒ ๐๐ฅ๐๐ ๐๐ฒ๐ฟ๐๐ถ๐ณ๐ถ๐ฐ๐ฎ๐๐ถ๐ผ๐ป ๐๐ผ๐๐ฟ๐๐ฒ๐ ๐ฎ๐ฌ๐ฎ๐ฒ ๐
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๐ฅ Don't just collect certificates โ build skills that can help you stand out in 2026!
Want to upgrade your resume with Google skills and certifications Explore FREE learning opportunities and build in-demand skills for today's job market.
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๐ Data Analytics
โ๏ธ Cloud Computing
๐ข Digital Marketing
๐ Cybersecurity
๐ป Tech & Career Skills
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๐ฅ Don't just collect certificates โ build skills that can help you stand out in 2026!
๐ Top Coding Interview Concepts โ Part 5 ๐ป๐ฅ
41. API โ A set of rules and protocols that allows different software applications to communicate with each other.
42. REST API โ An API architecture that uses HTTP methods and resources to enable communication between client and server.
43. HTTP Methods โ Actions used to interact with resources through HTTP.
Example:
44. JSON โ A lightweight text-based format commonly used to exchange structured data between applications.
Example:
45. Authentication โ The process of verifying who a user or system is.
Example: Logging in with a username and password.
46. Authorization โ The process of determining what an authenticated user is allowed to access or do.
Example: An admin can delete users, while a regular user cannot.
47. JWT (JSON Web Token) โ A compact token format commonly used to securely transmit claims between systems and authenticate API requests.
48. Session โ Information maintained by a server or application to keep track of a user's interaction over a period of time.
Example: Staying logged in while navigating between pages.
49. Cookie โ A small piece of data stored by a browser and sent with requests to help websites remember information about a user or session.
50. Cache โ Temporary storage used to keep frequently accessed data so it can be retrieved faster.
Example: A browser caches images so they load faster when you revisit a website.
๐ฌ Double Tap โค๏ธ for Part 6!
41. API โ A set of rules and protocols that allows different software applications to communicate with each other.
42. REST API โ An API architecture that uses HTTP methods and resources to enable communication between client and server.
43. HTTP Methods โ Actions used to interact with resources through HTTP.
Example:
GET โ retrieve data, POST โ create data, PUT โ update data, DELETE โ remove data.44. JSON โ A lightweight text-based format commonly used to exchange structured data between applications.
Example:
{"name": "John", "age": 25}45. Authentication โ The process of verifying who a user or system is.
Example: Logging in with a username and password.
46. Authorization โ The process of determining what an authenticated user is allowed to access or do.
Example: An admin can delete users, while a regular user cannot.
47. JWT (JSON Web Token) โ A compact token format commonly used to securely transmit claims between systems and authenticate API requests.
48. Session โ Information maintained by a server or application to keep track of a user's interaction over a period of time.
Example: Staying logged in while navigating between pages.
49. Cookie โ A small piece of data stored by a browser and sent with requests to help websites remember information about a user or session.
50. Cache โ Temporary storage used to keep frequently accessed data so it can be retrieved faster.
Example: A browser caches images so they load faster when you revisit a website.
๐ฌ Double Tap โค๏ธ for Part 6!
โค3