Best programming language suited for different fields:

1. Web development - Javanoscript, Python, PHP
2. AI & ML- Python, R
3. Competitive Programming - C++, Java
4. Mobile App development - Swift, Kotlin
5. Game Development - C#, C++
6. DSA- Java, Python
7. Data Analysis - Python, R
8. Data Science and ML - Python, R
9. Blockchain Dev- C++, Solidity
10. HFTs- C++, Java
11. Systems Programming - Rust, C
12. Embedded Systems - C, Assembly
13. Cybersecurity - Python, C
14. Financial Technology (Fintech) - Java, Scala
15. Internet of Things (IOT) - C, Python
16. Cloud Computing - Go, Java
17. DevOps & Automation - Python, Ruby
18. Scientific Computing - Fortran, Julia

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⭕️ G-Mail keyboard shortcuts ⭕️
#pc_feature #OldPost

Here is the complete list of Gmail keyboard shortcuts:

Compose and Chat

<Shift> + <Esc> : Focus main window
<Esc> : Focus latest chat or compose
<Ctrl> + . : Advance to next chat or compose
<Ctrl> + , : Advance to previous chat or compose
<Ctrl> + <Enter> : Send
<Ctrl> + <Shift> + c : Add cc recipients
<Ctrl> + <Shift> + b : Add bcc recipients
<Ctrl> + <Shift> + f : Access custom from
<Ctrl> + k : Insert a link
<Ctrl> + ; : Go to previous misspelled word
<Ctrl> + ' : Go to next misspelled word
<Ctrl> + m : Open spelling suggestions

Formatting

<Ctrl> + <Shift> + 5 : Previous font
<Ctrl> + <Shift> + 6 : Next font
<Ctrl> + <Shift> + - : Decrease text size
<Ctrl> + <Shift> + + : Increase text size
<Ctrl> + b : Bold
<Ctrl> + i : Italics
<Ctrl> + u : Underline
<Ctrl> + <Shift> + 7 : Numbered list
<Ctrl> + <Shift> + 8 : Bulleted list
<Ctrl> + <Shift> + 9 : Quote
<Ctrl> + [ : Indent less
<Ctrl> + ] : Indent more
<Ctrl> + <Shift> + l : Align left
<Ctrl> + <Shift> + e : Align center
<Ctrl> + <Shift> + r : Align right
<Ctrl> + <Shift> + , : Set right-to-left
<Ctrl> + <Shift> + . : Set left-to-right
<Ctrl> + \ : Remove formatting


Jumping

g then i : Go to Inbox
g then s : Go to Starred conversations
g then t : Go to Sent messages
g then d : Go to Drafts
g then a : Go to All mail
g then c : Go to Contacts
g then k : Go to Tasks
g then l : Go to Label

Threadlist selection

* then a : Select all conversations
* then n : Deselect all conversations
* then r : Select read conversations
* then u : Select unread conversations
* then s : Select starred conversations
* then t : Select unstarred conversations

Navigation

u : Back to threadlist
k / j : Newer/older conversation
o or <Enter> : Open conversation; collapse/expand conversation
p / n : Read previous/next message
` : Go to next inbox section
~ : Go to previous inbox section

Application

c : Compose
d : Compose in a tab (new compose only)
/ : Search mail
q : Search chat contacts
. : Open "more actions" menu
v : Open "move to" menu
l : Open "label as" menu
? : Open keyboard shortcut help

Actions

, : Move focus to toolbar
x : Select conversation
s : Rotate superstar
y : Remove label
e : Archive
m : Mute conversation
! : Report as spam
# : Delete
r : Reply
<Shift> + r : Reply in a new window
a : Reply all
<Shift> + a : Reply all in a new window
f : Forward
<Shift> + f : Forward in a new window
<Shift> + n : Update conversation
] / [ :  Remove conversation from current view and go previous/next
} / { : Archive conversation and go previous/next
z : Undo last action
<Shift> + i : Mark as read
<Shift> + u : Mark as unread
_ : Mark unread from the selected message
+ or = : Mark as important
- : Mark as not important
<Shift> + t : Add conversation to Tasks

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Review Fundamental Concepts: Ensure you have a strong grasp of statistics, probability, linear algebra, data structures, algorithms, and programming languages like Python, R, and SQL.

Refresh Machine Learning Knowledge: Familiarize yourself with various machine learning algorithms, including supervised, unsupervised, and reinforcement learning.

Practice Coding: Sharpen your coding skills by solving data science-related problems on platforms like HackerRank, LeetCode, and Kaggle.

Build a Project Portfolio: Showcase your proficiency by creating a portfolio highlighting projects covering data cleaning, wrangling, exploratory data analysis, and machine learning.

Hone Communication Skills: Practice articulating complex technical ideas in simple terms, as effective communication is vital for data scientists when interacting with non-technical stakeholders.

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