Top LeetCode questions asked in ๐๐ฉ๐ฉ๐ฅ๐ ๐๐ง๐ญ๐๐ซ๐ฏ๐ข๐๐ฐ๐ฌ for ๐๐๐ Role โค๏ธ
- Move Zeroes
- https://lnkd.in/dWrM3guU
- 3Sum [7 times]
- https://lnkd.in/d_vhP7X8
- Reverse Integer
- https://lnkd.in/dakwsvz9
- Roman to Integer
- https://lnkd.in/d3wrkWAb
- Two Sum [32 times]
- https://lnkd.in/dz-nQabK
- Contains Duplicate
- https://lnkd.in/dSGzKSpr
- Word Break [9 times]
- https://lnkd.in/dTyrvmrd
- Trapping Rain Water
- https://lnkd.in/dseQCGsV
- Longest Common Prefix
- https://lnkd.in/dinx-Rxz
- Permutations [7 times]
- https://lnkd.in/gHzEEqw3
- First Missing Positive
- https://lnkd.in/dniF7c7g
- Search Insert Position
- https://lnkd.in/dZwwnapr
- Word Search II [7 times]
- https://lnkd.in/dAV9Xg24
- Merge Intervals [9 times]
- https://lnkd.in/dvQYHsQf
- Group Anagrams [11 times]
- https://lnkd.in/d9wXHgK9
- Maximum Subarray [8 times]
- https://lnkd.in/d8t24BMj
- Container With Most Water
- https://lnkd.in/d866PPSK
- Valid Parentheses [10 times]
- https://lnkd.in/d2qy5P9D
- Number of Islands [13 times]
- https://lnkd.in/dEcneG2G
- Product of Array Except Self
- https://lnkd.in/d4UZTW7G
- Reverse Linked List [11 times]
- https://lnkd.in/dVmKdqvP
- Search in Rotated Sorted Array
- https://lnkd.in/dAnewRjw
- Longest Common Prefix [7 times]
- https://lnkd.in/gG6J3N6v
- Median of Two Sorted Arrays [9 times]
- https://lnkd.in/dtF7QHsY
- Product of Array Except Self [8 times]
- https://lnkd.in/ddtJrVQX
- Longest Palindromic Substring [6 times]
- https://lnkd.in/dFpK7Vbu
- Longest Substring Without Repeating Characters [7 times]
- https://lnkd.in/dAr9a5Ny
If you find it useful, give it a like and save it. Feel free to comment with your thoughts and queries. Also share it with your friends and colleagues out there. Don't forget to save this Post.
Follow Mohit Sehrawat for more.
Happy learning! ๐
๐๐๐ฌ๐ก๐ญ๐๐ ๐ฌ:
#coding #datastructures #algorithms #apple #interview #leetcode #programming #interviewpreparation
- Move Zeroes
- https://lnkd.in/dWrM3guU
- 3Sum [7 times]
- https://lnkd.in/d_vhP7X8
- Reverse Integer
- https://lnkd.in/dakwsvz9
- Roman to Integer
- https://lnkd.in/d3wrkWAb
- Two Sum [32 times]
- https://lnkd.in/dz-nQabK
- Contains Duplicate
- https://lnkd.in/dSGzKSpr
- Word Break [9 times]
- https://lnkd.in/dTyrvmrd
- Trapping Rain Water
- https://lnkd.in/dseQCGsV
- Longest Common Prefix
- https://lnkd.in/dinx-Rxz
- Permutations [7 times]
- https://lnkd.in/gHzEEqw3
- First Missing Positive
- https://lnkd.in/dniF7c7g
- Search Insert Position
- https://lnkd.in/dZwwnapr
- Word Search II [7 times]
- https://lnkd.in/dAV9Xg24
- Merge Intervals [9 times]
- https://lnkd.in/dvQYHsQf
- Group Anagrams [11 times]
- https://lnkd.in/d9wXHgK9
- Maximum Subarray [8 times]
- https://lnkd.in/d8t24BMj
- Container With Most Water
- https://lnkd.in/d866PPSK
- Valid Parentheses [10 times]
- https://lnkd.in/d2qy5P9D
- Number of Islands [13 times]
- https://lnkd.in/dEcneG2G
- Product of Array Except Self
- https://lnkd.in/d4UZTW7G
- Reverse Linked List [11 times]
- https://lnkd.in/dVmKdqvP
- Search in Rotated Sorted Array
- https://lnkd.in/dAnewRjw
- Longest Common Prefix [7 times]
- https://lnkd.in/gG6J3N6v
- Median of Two Sorted Arrays [9 times]
- https://lnkd.in/dtF7QHsY
- Product of Array Except Self [8 times]
- https://lnkd.in/ddtJrVQX
- Longest Palindromic Substring [6 times]
- https://lnkd.in/dFpK7Vbu
- Longest Substring Without Repeating Characters [7 times]
- https://lnkd.in/dAr9a5Ny
If you find it useful, give it a like and save it. Feel free to comment with your thoughts and queries. Also share it with your friends and colleagues out there. Don't forget to save this Post.
Follow Mohit Sehrawat for more.
Happy learning! ๐
๐๐๐ฌ๐ก๐ญ๐๐ ๐ฌ:
#coding #datastructures #algorithms #apple #interview #leetcode #programming #interviewpreparation
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๐ฅ2
Rotate image.pdf
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DSA Problem (2): ๐๐จ๐๐ญ๐ ๐๐ฆ๐๐ ๐
This is a very important question had been asked in all the company's interviews including #google #meta #amazon #microsoft.
In this article I have covered the following things:
โ๏ธ Problem statements.
โ๏ธ Discuss all the approaches.
โ๏ธ Dry run with clean and proper diagrams.
โ๏ธ Clean & smooth code of each approach.
Tags:
#arrays #matrix #dsa #algorithms #dsacoding #coding
#articles #loadbalancers #systemdesign #fang #mang #datastructuresandalgorithms #datastructures #algorithms #arrays #notes #interview #share #help #jobs #placement #college #softwareengineers #design
This is a very important question had been asked in all the company's interviews including #google #meta #amazon #microsoft.
In this article I have covered the following things:
โ๏ธ Problem statements.
โ๏ธ Discuss all the approaches.
โ๏ธ Dry run with clean and proper diagrams.
โ๏ธ Clean & smooth code of each approach.
Tags:
#arrays #matrix #dsa #algorithms #dsacoding #coding
#articles #loadbalancers #systemdesign #fang #mang #datastructuresandalgorithms #datastructures #algorithms #arrays #notes #interview #share #help #jobs #placement #college #softwareengineers #design
Top LeetCode questions asked in Google Interviews for SDE role (PART-1) ๐
๐ Please don't ignore this post, it took a lot of effort & time to research & create this post. Many of us are preparing for the interviews to get placed in top product-based companies and #Leetcode is one of the good platforms to practice the #DSA questions.
๐Here is a list of questions (Part-1) which recently asked by Google during the interviews. The questions and their respective links are in the same order. The content source is the Internet and Leetcode.
โพQUESTIONS :-
- H-Index
- Poor Pigs
- Valid Square
- Decode String
- Text Justification
- Battleships in a Board
- Minimum Time Difference
- Longest Absolute File Path
- Student Attendance Record II
- Evaluate Reverse Polish Notation
- Longest Increasing Path in a Matrix
โพLinks:-
- https://lnkd.in/dVy49_Nr
- https://lnkd.in/daX_YFyX
- https://lnkd.in/dvq8H_2w
- https://lnkd.in/dDpYv6G5
- https://lnkd.in/dYNWn5N3
- https://lnkd.in/d29shXsD
- https://lnkd.in/dGAuhsvh
- https://lnkd.in/dHD-2TVZ
- https://lnkd.in/dbnqgbkA
- https://lnkd.in/dCX4BzSE
- https://lnkd.in/dmEWHdSd
๐ If you find it useful, give it a like and save it. Feel free to comment with your thoughts and queries. Don't forget to save this Post. Also share it with your friends and colleagues out there.๐ญ
tags-
#coding #datastructures #algorithms #google #interview #computerscience #softwareengineer #data #programming
๐ Please don't ignore this post, it took a lot of effort & time to research & create this post. Many of us are preparing for the interviews to get placed in top product-based companies and #Leetcode is one of the good platforms to practice the #DSA questions.
๐Here is a list of questions (Part-1) which recently asked by Google during the interviews. The questions and their respective links are in the same order. The content source is the Internet and Leetcode.
โพQUESTIONS :-
- H-Index
- Poor Pigs
- Valid Square
- Decode String
- Text Justification
- Battleships in a Board
- Minimum Time Difference
- Longest Absolute File Path
- Student Attendance Record II
- Evaluate Reverse Polish Notation
- Longest Increasing Path in a Matrix
โพLinks:-
- https://lnkd.in/dVy49_Nr
- https://lnkd.in/daX_YFyX
- https://lnkd.in/dvq8H_2w
- https://lnkd.in/dDpYv6G5
- https://lnkd.in/dYNWn5N3
- https://lnkd.in/d29shXsD
- https://lnkd.in/dGAuhsvh
- https://lnkd.in/dHD-2TVZ
- https://lnkd.in/dbnqgbkA
- https://lnkd.in/dCX4BzSE
- https://lnkd.in/dmEWHdSd
๐ If you find it useful, give it a like and save it. Feel free to comment with your thoughts and queries. Don't forget to save this Post. Also share it with your friends and colleagues out there.๐ญ
tags-
#coding #datastructures #algorithms #google #interview #computerscience #softwareengineer #data #programming
LinkedIn
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Subarray.pdf
1.5 MB
DSA Problem (03): ๐๐ฎ๐-๐๐ซ๐ซ๐๐ฒ ๐๐ฎ๐ฆ ๐๐ฎ๐ช๐๐ฅ๐ฌ ๐ญ๐จ ๐
This is another important question that had been asked in all the company's interviews including:
#google #meta #amazon #microsoft.
In this article I have covered the following things:
โ๏ธ Problem statements.
โ๏ธ Discuss all the approaches.
โ๏ธ Very neat & clean dry run with proper diagrams.
โ๏ธ Clean & smooth code of each approaches.
I hope you'll like it. If you have any doubts or want to talk about this, please feel free to comment.
I have spent hours of my time preparing this one and I want to help as many people as I can. so kindly so show your support by sharing this with your connections.
Stay tuned for much more upcoming notes ๐
๐๐: Don't forget to checkout pinned comment ๐
Tags:
#arrays #matrix #dsa #algorithms #dsacoding #coding
#articles #loadbalancers #systemdesign #fang #mang #datastructuresandalgorithms #datastructures #algorithms #arrays #notes #interview #share #help #jobs #placement #college #softwareengineers #design
This is another important question that had been asked in all the company's interviews including:
#google #meta #amazon #microsoft.
In this article I have covered the following things:
โ๏ธ Problem statements.
โ๏ธ Discuss all the approaches.
โ๏ธ Very neat & clean dry run with proper diagrams.
โ๏ธ Clean & smooth code of each approaches.
I hope you'll like it. If you have any doubts or want to talk about this, please feel free to comment.
I have spent hours of my time preparing this one and I want to help as many people as I can. so kindly so show your support by sharing this with your connections.
Stay tuned for much more upcoming notes ๐
๐๐: Don't forget to checkout pinned comment ๐
Tags:
#arrays #matrix #dsa #algorithms #dsacoding #coding
#articles #loadbalancers #systemdesign #fang #mang #datastructuresandalgorithms #datastructures #algorithms #arrays #notes #interview #share #help #jobs #placement #college #softwareengineers #design
ALGORITHM YOU SHOULD KNOW for PREPARING SYSTEM DESIGN INTERVIEW ๐ก
๐บREQUIREMENTS :-
KNOW WHEN TO USE
KNOW HOW IT WORKS
โพ1) BLOOM FILTER
It is a data structure designed to tell you, rapidly and memory-efficiently, whether an element is present in a set.
- use case :: Build a Web crawler
โพ2) FRUGAL STREAMING
It uses only one unit of memory per group to compute a quantile for each group.
-use case :: Find the nth percentile of the data stream.
โพ3) GEOHASH/ S2 GEOMETRY
A collection of efficient yet exact mathematical predicates for testing relationships among geometric primitives.
-use case :: Location-based search results with DynamoDb and Geohash.
โพ4) HYPERLOGLOG
It is an algorithm for the count-distinct problem, approximating the number of distinct elements in a multiset.
-use case :: privacy-preserving traffic heat map for the city.
โพ5) LEAKY BUCKET/ TOKEN BUCKET
A mechanism to control the amount and the rate of the traffic sent to the network.
-use case :: Design a scalable rate-limiting algorithm.
โพ6) LOSSY COUNT
It is used to identify elements in a data stream whose frequency count exceeds a user-given threshold.
-use case :: Frequency count over the data streams.
โพ7) OPERATIONAL TRANSFORMATION
It is used for supporting a range of collaboration functionalities in advanced collaborative software systems.
-use case :: Handling editing collision in Google docs.
โพ8) QUADTREE/ RTREE
It is a two-dimensional analog of octrees and is most often used to partition a two-dimensional space by recursively subdividing it into four quadrants or regions.
-use case :: Find nearby interest points
โพ9) RAY CASTING
It is the most basic of many computer graphics rendering algo that uses geometric algo of ray tracing.
-use case :: Using longitude and latitude, return the Country of the point.
โพ10) REVERSE INDEX
It is an index of keywords that stores records of documents that contain keywords in the list.
-use case: Building a complete Tweet index.
โพ11) RSYNC ALGORITHM
Used for reducing the cost of a file transfer by avoiding the transfer of blocks that are already at the destination.
-use case :: Streaming file Sync
โพ12) TRIE ALGORITHM
Trie is an efficient information reTrieval data structure. Using Trie, search complexities can be brought to optimal limit (key length)
-use case :: Autocomplete features using Trie
13) STRING BUFFER
-use case :: Banking transactions because it follows thread synchronisation
13) STRING BUILDER
-use case :: BOOKMYSHOW OR IRCTC ticket booking because it NOT following thread synchronisation
collab credit - windsoon / ansh /Aman
#software #design #google #systemdesign #backend #backenddeveloper #softwareengineer #algorithms
๐บREQUIREMENTS :-
KNOW WHEN TO USE
KNOW HOW IT WORKS
โพ1) BLOOM FILTER
It is a data structure designed to tell you, rapidly and memory-efficiently, whether an element is present in a set.
- use case :: Build a Web crawler
โพ2) FRUGAL STREAMING
It uses only one unit of memory per group to compute a quantile for each group.
-use case :: Find the nth percentile of the data stream.
โพ3) GEOHASH/ S2 GEOMETRY
A collection of efficient yet exact mathematical predicates for testing relationships among geometric primitives.
-use case :: Location-based search results with DynamoDb and Geohash.
โพ4) HYPERLOGLOG
It is an algorithm for the count-distinct problem, approximating the number of distinct elements in a multiset.
-use case :: privacy-preserving traffic heat map for the city.
โพ5) LEAKY BUCKET/ TOKEN BUCKET
A mechanism to control the amount and the rate of the traffic sent to the network.
-use case :: Design a scalable rate-limiting algorithm.
โพ6) LOSSY COUNT
It is used to identify elements in a data stream whose frequency count exceeds a user-given threshold.
-use case :: Frequency count over the data streams.
โพ7) OPERATIONAL TRANSFORMATION
It is used for supporting a range of collaboration functionalities in advanced collaborative software systems.
-use case :: Handling editing collision in Google docs.
โพ8) QUADTREE/ RTREE
It is a two-dimensional analog of octrees and is most often used to partition a two-dimensional space by recursively subdividing it into four quadrants or regions.
-use case :: Find nearby interest points
โพ9) RAY CASTING
It is the most basic of many computer graphics rendering algo that uses geometric algo of ray tracing.
-use case :: Using longitude and latitude, return the Country of the point.
โพ10) REVERSE INDEX
It is an index of keywords that stores records of documents that contain keywords in the list.
-use case: Building a complete Tweet index.
โพ11) RSYNC ALGORITHM
Used for reducing the cost of a file transfer by avoiding the transfer of blocks that are already at the destination.
-use case :: Streaming file Sync
โพ12) TRIE ALGORITHM
Trie is an efficient information reTrieval data structure. Using Trie, search complexities can be brought to optimal limit (key length)
-use case :: Autocomplete features using Trie
13) STRING BUFFER
-use case :: Banking transactions because it follows thread synchronisation
13) STRING BUILDER
-use case :: BOOKMYSHOW OR IRCTC ticket booking because it NOT following thread synchronisation
collab credit - windsoon / ansh /Aman
#software #design #google #systemdesign #backend #backenddeveloper #softwareengineer #algorithms
ALGORITHM YOU SHOULD KNOW for PREPARING SYSTEM DESIGN INTERVIEW ๐ก
๐บREQUIREMENTS :-
KNOW WHEN TO USE
KNOW HOW IT WORKS
โพ1) BLOOM FILTER
It is a data structure designed to tell you, rapidly and memory-efficiently, whether an element is present in a set.
- use case :: Build a Web crawler
โพ2) FRUGAL STREAMING
It uses only one unit of memory per group to compute a quantile for each group.
-use case :: Find the nth percentile of the data stream.
โพ3) GEOHASH/ S2 GEOMETRY
A collection of efficient yet exact mathematical predicates for testing relationships among geometric primitives.
-use case :: Location-based search results with DynamoDb and Geohash.
โพ4) HYPERLOGLOG
It is an algorithm for the count-distinct problem, approximating the number of distinct elements in a multiset.
-use case :: privacy-preserving traffic heat map for the city.
โพ5) LEAKY BUCKET/ TOKEN BUCKET
A mechanism to control the amount and the rate of the traffic sent to the network.
-use case :: Design a scalable rate-limiting algorithm.
โพ6) LOSSY COUNT
It is used to identify elements in a data stream whose frequency count exceeds a user-given threshold.
-use case :: Frequency count over the data streams.
โพ7) OPERATIONAL TRANSFORMATION
It is used for supporting a range of collaboration functionalities in advanced collaborative software systems.
-use case :: Handling editing collision in Google docs.
โพ8) QUADTREE/ RTREE
It is a two-dimensional analog of octrees and is most often used to partition a two-dimensional space by recursively subdividing it into four quadrants or regions.
-use case :: Find nearby interest points
โพ9) RAY CASTING
It is the most basic of many computer graphics rendering algo that uses geometric algo of ray tracing.
-use case :: Using longitude and latitude, return the Country of the point.
โพ10) REVERSE INDEX
It is an index of keywords that stores records of documents that contain keywords in the list.
-use case: Building a complete Tweet index.
โพ11) RSYNC ALGORITHM
Used for reducing the cost of a file transfer by avoiding the transfer of blocks that are already at the destination.
-use case :: Streaming file Sync
โพ12) TRIE ALGORITHM
Trie is an efficient information reTrieval data structure. Using Trie, search complexities can be brought to optimal limit (key length)
-use case :: Autocomplete features using Trie
13) STRING BUFFER
-use case :: Banking transactions because it follows thread synchronisation
13) STRING BUILDER
-use case :: BOOKMYSHOW OR IRCTC ticket booking because it NOT following thread synchronisation
collab credit - windsoon / ansh /Aman
#software #design #google #systemdesign #backend #backenddeveloper #softwareengineer #algorithms
๐บREQUIREMENTS :-
KNOW WHEN TO USE
KNOW HOW IT WORKS
โพ1) BLOOM FILTER
It is a data structure designed to tell you, rapidly and memory-efficiently, whether an element is present in a set.
- use case :: Build a Web crawler
โพ2) FRUGAL STREAMING
It uses only one unit of memory per group to compute a quantile for each group.
-use case :: Find the nth percentile of the data stream.
โพ3) GEOHASH/ S2 GEOMETRY
A collection of efficient yet exact mathematical predicates for testing relationships among geometric primitives.
-use case :: Location-based search results with DynamoDb and Geohash.
โพ4) HYPERLOGLOG
It is an algorithm for the count-distinct problem, approximating the number of distinct elements in a multiset.
-use case :: privacy-preserving traffic heat map for the city.
โพ5) LEAKY BUCKET/ TOKEN BUCKET
A mechanism to control the amount and the rate of the traffic sent to the network.
-use case :: Design a scalable rate-limiting algorithm.
โพ6) LOSSY COUNT
It is used to identify elements in a data stream whose frequency count exceeds a user-given threshold.
-use case :: Frequency count over the data streams.
โพ7) OPERATIONAL TRANSFORMATION
It is used for supporting a range of collaboration functionalities in advanced collaborative software systems.
-use case :: Handling editing collision in Google docs.
โพ8) QUADTREE/ RTREE
It is a two-dimensional analog of octrees and is most often used to partition a two-dimensional space by recursively subdividing it into four quadrants or regions.
-use case :: Find nearby interest points
โพ9) RAY CASTING
It is the most basic of many computer graphics rendering algo that uses geometric algo of ray tracing.
-use case :: Using longitude and latitude, return the Country of the point.
โพ10) REVERSE INDEX
It is an index of keywords that stores records of documents that contain keywords in the list.
-use case: Building a complete Tweet index.
โพ11) RSYNC ALGORITHM
Used for reducing the cost of a file transfer by avoiding the transfer of blocks that are already at the destination.
-use case :: Streaming file Sync
โพ12) TRIE ALGORITHM
Trie is an efficient information reTrieval data structure. Using Trie, search complexities can be brought to optimal limit (key length)
-use case :: Autocomplete features using Trie
13) STRING BUFFER
-use case :: Banking transactions because it follows thread synchronisation
13) STRING BUILDER
-use case :: BOOKMYSHOW OR IRCTC ticket booking because it NOT following thread synchronisation
collab credit - windsoon / ansh /Aman
#software #design #google #systemdesign #backend #backenddeveloper #softwareengineer #algorithms
๐ Empower your career with data engineering skills and secure your dream job in this growing fieldโ๏ธ
โ๏ธ After receiving a lot of queries, I've made some revisions to my original suggestion and I highly recommend following this exact sequence. Trust me, it will make things much easier for you.
โป๏ธ It's easy to get lost in the vast amount of information available when it comes to learning new skills, especially in the field of data engineering.
๐ However, with a solid roadmap and some dedication, it is possible to enter the field of data engineering in 2023.
Here are some steps you can follow to make sure you're on the right track -
๐ถ Learn RDBMS, NoSQL databases, SQL, and data warehousing concepts :
As a data engineer, you'll be working with large amounts of data stored in databases. Familiarize yourself with different types of databases and how to query them using SQL. Learn one RDBMS and one NoSQL database, then familiarize yourself with data warehousing concepts.
1. Learn Data Warehousing concepts - https://lnkd.in/eKnVbFAB
2. Learn MySql - https://lnkd.in/efk-Mi3c
3. Learn and practice SQL - https://lnkd.in/efMKFkfX
4. Learn Azure Cosmos DB - https://lnkd.in/eNVyc6Mq
๐ถ Learn Python and PySpark :
These are essential tools for data engineers.
1. Python: https://lnkd.in/e5rCbvP8
2. PySpark : https://bit.ly/3Vu34Ev
๐ถ Learn Bash, Airflow and Kafka :
These tools will help you automate and streamline data processing tasks. You will also lear how to create data pipelines.๐ฉ
https://lnkd.in/eyN6u2yd
๐ถ Learn Git and the basics of CICD :
These skills will help you work collaboratively on data engineering projects and ensure smooth deployment.
Git - https://lnkd.in/eX_Q8s99
Basics of CICD - https://lnkd.in/epKGivFY
๐ถ Learn Azure Databricks and Data Lakes :
Azure Databricks - https://lnkd.in/eBij4akJ
Learn Data Lakes - https://lnkd.in/eQ9xxAJT
๐ Create a standout resume by showcasing your skills and experience in data engineering.
๐ Enhance your portfolio by completing various data engineering projects and sharing them on GitHub.
๐ Seek out opportunities in data engineering by applying to relevant positions
Optional Learning -
1. Learn Data Structure and Algorithms
2. Learn AWS or Azure services dedicated for data engineering works.
By following these steps and dedicating yourself to learning and gaining experience, you can become a data engineer in 2023. Good luck on your journey!
I have created a Telegram channel for sharing knowledge and have included the link in the comments section.
๐ If you like my posts, please follow https://www.linkedin.com/groups/14161672 ๐บ๐ธ ๐๐ and hit the ๐ on my profile to get a notification for all my new posts.
๏ปฟ#dataengineering #nosql #hadoop #datastructures #sql #algorithms #bigdata #business #python #data #programming #mysql #database #aws #spark #github #azure #job #career #learning #opportunities #experience #resume #engineer #warehousing
โ๏ธ After receiving a lot of queries, I've made some revisions to my original suggestion and I highly recommend following this exact sequence. Trust me, it will make things much easier for you.
โป๏ธ It's easy to get lost in the vast amount of information available when it comes to learning new skills, especially in the field of data engineering.
๐ However, with a solid roadmap and some dedication, it is possible to enter the field of data engineering in 2023.
Here are some steps you can follow to make sure you're on the right track -
๐ถ Learn RDBMS, NoSQL databases, SQL, and data warehousing concepts :
As a data engineer, you'll be working with large amounts of data stored in databases. Familiarize yourself with different types of databases and how to query them using SQL. Learn one RDBMS and one NoSQL database, then familiarize yourself with data warehousing concepts.
1. Learn Data Warehousing concepts - https://lnkd.in/eKnVbFAB
2. Learn MySql - https://lnkd.in/efk-Mi3c
3. Learn and practice SQL - https://lnkd.in/efMKFkfX
4. Learn Azure Cosmos DB - https://lnkd.in/eNVyc6Mq
๐ถ Learn Python and PySpark :
These are essential tools for data engineers.
1. Python: https://lnkd.in/e5rCbvP8
2. PySpark : https://bit.ly/3Vu34Ev
๐ถ Learn Bash, Airflow and Kafka :
These tools will help you automate and streamline data processing tasks. You will also lear how to create data pipelines.๐ฉ
https://lnkd.in/eyN6u2yd
๐ถ Learn Git and the basics of CICD :
These skills will help you work collaboratively on data engineering projects and ensure smooth deployment.
Git - https://lnkd.in/eX_Q8s99
Basics of CICD - https://lnkd.in/epKGivFY
๐ถ Learn Azure Databricks and Data Lakes :
Azure Databricks - https://lnkd.in/eBij4akJ
Learn Data Lakes - https://lnkd.in/eQ9xxAJT
๐ Create a standout resume by showcasing your skills and experience in data engineering.
๐ Enhance your portfolio by completing various data engineering projects and sharing them on GitHub.
๐ Seek out opportunities in data engineering by applying to relevant positions
Optional Learning -
1. Learn Data Structure and Algorithms
2. Learn AWS or Azure services dedicated for data engineering works.
By following these steps and dedicating yourself to learning and gaining experience, you can become a data engineer in 2023. Good luck on your journey!
I have created a Telegram channel for sharing knowledge and have included the link in the comments section.
๐ If you like my posts, please follow https://www.linkedin.com/groups/14161672 ๐บ๐ธ ๐๐ and hit the ๐ on my profile to get a notification for all my new posts.
๏ปฟ#dataengineering #nosql #hadoop #datastructures #sql #algorithms #bigdata #business #python #data #programming #mysql #database #aws #spark #github #azure #job #career #learning #opportunities #experience #resume #engineer #warehousing
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LinkedIn
This link will take you to a page thatโs not on LinkedIn
Instead of learning solutions of LeetCode questions, understand patterns! ๐
๐ด๐๐๐ ๐บ๐๐๐ ๐๐๐ ๐บ๐๐๐๐ !!!!
For ex.
If input array is sorted then
- Binary search
- Two pointers
If asked for all permutations/subsets then
- Backtracking
If given a tree then
- DFS
- BFS
If given a graph then
- DFS
- BFS
If given a linked list then
- Two pointers
If recursion is banned then
- Stack
If must solve in-place then
- Swap corresponding values
- Store one or more different values in the same pointer
If asked for maximum/minimum subarray/subset/options then
- Dynamic programming
If asked for top/least K items then
- Heap
If asked for common strings then
- Map
- Trie
Else
- Map/Set for O(1) time & O(n) space
- Sort input for O(nlogn) time and O(1) space
Link : https://t.me/teamJavaHyd๐๐๐
Check out a GitHub repo by Sean Prasad if you're interested to read more about this, it's absolutely amazing!
#leetcode #placements #dsa #interview #coding #preparation #consistency #quality #programming #softwareengineering #india #competitiveprogramming #datastructures #algorithms #connections #interviewpreparation
๐ด๐๐๐ ๐บ๐๐๐ ๐๐๐ ๐บ๐๐๐๐ !!!!
For ex.
If input array is sorted then
- Binary search
- Two pointers
If asked for all permutations/subsets then
- Backtracking
If given a tree then
- DFS
- BFS
If given a graph then
- DFS
- BFS
If given a linked list then
- Two pointers
If recursion is banned then
- Stack
If must solve in-place then
- Swap corresponding values
- Store one or more different values in the same pointer
If asked for maximum/minimum subarray/subset/options then
- Dynamic programming
If asked for top/least K items then
- Heap
If asked for common strings then
- Map
- Trie
Else
- Map/Set for O(1) time & O(n) space
- Sort input for O(nlogn) time and O(1) space
Link : https://t.me/teamJavaHyd๐๐๐
Check out a GitHub repo by Sean Prasad if you're interested to read more about this, it's absolutely amazing!
#leetcode #placements #dsa #interview #coding #preparation #consistency #quality #programming #softwareengineering #india #competitiveprogramming #datastructures #algorithms #connections #interviewpreparation