🎯 𝐅𝐫𝐨𝐧𝐭𝐞𝐧𝐝 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐒𝐤𝐢𝐥𝐥𝐬 𝐟𝐨𝐫 𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐁𝐚𝐬𝐞𝐝 𝐂𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 🔥

✅ A roadmap is the best way to kick-start your attempt to become a front-end developer.

📌 𝗕𝗮𝘀𝗶𝗰 𝗝𝗮𝘃𝗮𝗦𝗰𝗿𝗶𝗽𝘁 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀:
1. Data types
2. Functions
3. Scope in JavaScript
4. Closure
5. Event loop
6. Prototype and prototype chain
7. Class and inheritance
8. DOM
9. bind/call/apply
10. Promise
11. WebAPI
12. Task queue
13. Call stack
14. Async/await
15. Generators
16. Typescript

📌 𝗕𝗮𝘀𝗶𝗰 𝗛𝗧𝗠𝗟 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀:
1. block element
2. import
3. etc - infinite questions

📌 𝗕𝗮𝘀𝗶𝗰 𝗖𝗦𝗦 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀:
1. Class and other selectors
2. Pseudo Classes
3. Box Model
4. Pseudo Elements
5. CSS type - flex, grid, normal
6. How to center
7. pseudo classes and elements
8. All element states - active, hover
9. Media queries
10. Pre-processors - SCSS or LESS
1. mixins
11. CSS constants
12. BEM
13. Import

📌 𝗕𝗮𝘀𝗶𝗰 𝗪𝗲𝗯 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀:
1. Page rendering cycle
2. HTTP / HTTPS / https2
3. CORS
4. Local storage/Session storage
5. Cookie
6. JWT
7. XHR
8. Micro Frontend
9. REST/GraphQL/Socket connection
10. Browser Concepts
11. Debugging Application
12. Chrome Dev Tool Features

Web Developer Lessons: https://t.me/webdevresourcestp/30

📌 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗝𝗮𝘃𝗮𝗦𝗰𝗿𝗶𝗽𝘁 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀:
1. OOPs concept
2. Design Patterns
a. Singleton
b. Provider
c. Prototype
d. Observer
e. Module
f. HOC

JavaScript Lessons: https://t.me/javascriptresourcestp/446

3. Understanding V8 in-depth
a. JIT
b. Interpreter
c. Execution
d. Compiler
4. Currying

📌 𝗕𝗮𝘀𝗶𝗰 𝗥𝗲𝗮𝗰𝘁𝗝𝗦 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 (bonus): -
1. Introduction JSX
2. React Component
3. Component State and Props
4. Adding Style (CSS)
5. Functional and Class components
6. React Lifecycle Methods
7. Virtual DOM
8. React Hooks
9. Custom Hooks
10. Context API
11. Synthetic Events
12. Routing
13. Data Flow (Redux/Flux)
14. Server-Side Rendering
15. Unit Testing
16. Jest & React Testing Library
17. Mocking Data
18. Understanding Webpack (Bundler)
19. Babel, env, prettier, linter

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Full Stack

How can I spot a bullish trend in the crypto market?

To spot a bullish trend in the crypto market, look for increasing prices, higher highs, and higher lows on the price chart. Analyzing moving averages, positive trading volume, and bullish indicators like the Relative Strength Index (RSI) can also provide confirmation. Keep in mind that no method guarantees success, so consider using a combination of technical analysis tools for a more comprehensive assessment.

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🎲 Some Useful Computer Shortcuts 🎲

Ctrl+A - Select All
Ctrl+B - Bold
Ctrl+C - Copy
Ctrl+D - Fill Down
Ctrl+F - Find
Ctrl+G - Goto
Ctrl+H - Replace
Ctrl+I - Italic
Ctrl+K - Insert Hyperlink
Ctrl+N - New Workbook
Ctrl+O - Open
Ctrl+P - Print
Ctrl+R - Fill Right
Ctrl+S - Save
Ctrl+U - Underline
Ctrl+V - Paste
Ctrl W - Close
Ctrl+X - Cut
Ctrl+Y - Repeat
Ctrl+Z - Undo
F1 - Help
F2 - Edit
F3 - Paste Name
F4 - Repeat last action
F4 - While typing a formula, switch between absolute/relative refs
F5 - Goto
F6 - Next Pane
F7 - Spell check
F8 - Extend mode
F9 - Recalculate all workbooks
F10 - Activate Menu bar
F11 - New Chart
F12 - Save As
Ctrl+: - Insert Current Time
Ctrl+; - Insert Current Date
Ctrl+" - Copy Value from Cell Above
Ctrl+’ - Copy Formula from Cell Above
Shift - Hold down shift for additional functions in Excel’s menu
Shift+F1 - What’s This?
Shift+F2 - Edit cell comment
Shift+F3 - Paste function into formula
Shift+F4 - Find Next
Shift+F5 - Find
Shift+F6 - Previous Pane
Shift+F8 - Add to selection
Shift+F9 - Calculate active worksheet
Shift+F10 - Display shortcut menu
Shift+F11 - New worksheet
Ctrl+F3 - Define name
Ctrl+F4 - Close
Ctrl+F5 - XL, Restore window size
Ctrl+F6 - Next workbook window
Shift+Ctrl+F6 - Previous workbook window
Ctrl+F7 - Move window
Ctrl+F8 - Resize window
Ctrl+F9 - Minimize workbook
Ctrl+F10 - Maximize or restore window
Ctrl+F11 - Inset 4.0 Macro sheet
Ctrl+F1 - File Open
Alt+F1 - Insert Chart
Alt+F2 - Save As
Alt+F4 - Exit
Alt+Down arrow - Display AutoComplete list
Alt+’ - Format Style dialog box
Ctrl+Shift+~ - General format
Ctrl+Shift+! - Comma format
Ctrl+Shift+@ - Time format
Ctrl+Shift+# - Date format
Ctrl+Shift+$ - Currency format
Ctrl+Shift+% - Percent format
Ctrl+Shift+^ - Exponential format
Ctrl+Shift+& - Place outline border around selected cells
Ctrl+Shift+_ - Remove outline border
Ctrl+Shift+* - Select current region
Ctrl++ - Insert
Ctrl+- - Delete
Ctrl+1 - Format cells dialog box
Ctrl+2 - Bold
Ctrl+3 - Italic
Ctrl+4 - Underline
Ctrl+5 - Strikethrough
Ctrl+6 - Show/Hide objects
Ctrl+7 - Show/Hide Standard toolbar
Ctrl+8 - Toggle Outline symbols
Ctrl+9 - Hide rows
Ctrl+0 - Hide columns
Ctrl+Shift+( - Unhide rows
Ctrl+Shift+) - Unhide columns
Alt or F10 - Activate the menu
Ctrl+Tab - In toolbar: next toolbar
Shift+Ctrl+Tab - In toolbar: previous toolbar
Ctrl+Tab - In a workbook: activate next workbook
Shift+Ctrl+Tab - In a workbook: activate previous workbook
Tab - Next tool
Shift+Tab - Previous tool
Enter - Do the command
Shift+Ctrl+F - Font Drop down List
Shift+Ctrl+F+F - Font tab of Format Cell Dialog box
Shift+Ctrl+P - Point size Drop down List
Ctrl + E - Align center
Ctrl + J - justify
Ctrl + L - align 
Ctrl + R - align right
Alt + Tab - switch applications
Windows + P - Project screen
Windows + E - open file explorer
Windows + D - go to desktop
Windows + M - minimize all windows
Windows + S - search

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China lowers tariffs on US from 125% to 10% for 90 days.

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𝐀𝐈 & 𝐌𝐋 𝐅𝐑𝐄𝐄 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 𝐅𝐫𝐨𝐦 6 𝐓𝐨𝐩 𝐈𝐧𝐬𝐭𝐢𝐭𝐮𝐭𝐢𝐨𝐧𝐬!😍

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MVP — what is it and what does it do

Minimum Viable Product, MVP, - in our world, it is an application that has the minimum functionality, capable of covering the user's needs.

Development is expensive: a team of programmers has to build a digital solution to an idea, with a nice interface and without bugs. But businesses (often) don't have the money to pay long development fees first. There is only an idea.

To test the idea, they create an MVP. They choose key features, weed out the unnecessary ones, make a list of "would-be-do-it-if-we-have-time" features, make a plan, and decide: will this functionality be enough to test our idea? If the answer is yes, people will use the app even without the secondary functionality - then it's ok, we can keep sawing.

But in MVP applications we need to cut off not only the functionality.

There is also refactoring, for example. At some moment you will want to return to the old code and clean it up a bit. Make it more readable, standardize it. If this refactoring doesn't bring notable relief to the developers, you need to postpone it until after the release. Or tests. They are necessary and important, but not for MVP (debatable, I agree, it depends on the project). In my experience, MVP application code testing was increasing development time by 25-40%, not giving the desired output. We were wasting time covering tests that didn't help us much, delaying development.

All of this can and should be turned a blind eye if we're doing MVPs. The business doesn't care how this button is created, whether it's a method widget or just an object widget. For it the main thing is that there is a button, and it at least works. And it doesn't slow us down. Hence, we don't need to work on it at the moment.

Ideally, of course, the team should meet together at the beginning of the project and agree on what they do and don't do. You can write manuals and recommendations. Or we could say: guys, we've got some crap in our code here, let's not do this anymore. The point is, our job is to get it up and running as quickly as possible. After all, the application could be so useless that we won't continue development at all. So why do we need code that is 100% covered by tests and doesn't contain a single anti-pattern if we're not going to work on it?

Yes, we'll have to roll out an application with shitty code. But if this code solves a business problem and is able to attract the first money, it's not such a shitty code. After all, it solved the main problem. To get it up and running. From there we look at user feedback, fix what we need, and try to get some time for refactoring.

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𝐀𝐈 & 𝐌𝐋 𝐅𝐑𝐄𝐄 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 𝐅𝐫𝐨𝐦 6 𝐓𝐨𝐩 𝐈𝐧𝐬𝐭𝐢𝐭𝐮𝐭𝐢𝐨𝐧𝐬!😍

Explore these 6 amazing courses offered by the:
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Spend $0 to master new skills in 2025:

1. HTML - w3schools.com
2. CSS - css-tricks.com
3. JavaScript - learnjavascript.online
4. React - react-tutorial.app
5. Tailwind - scrimba.com
6. Vue - vueschool.io
7. Python - pythontutorial.net
8. SQL - t.me/sqlresourcestp
9. Git - atlassian.com/git/tutorials
10. Data Analysis - t.me/dataanalysisresourcestp

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✅Introducing the Crypto Exchange

🔴Buying cryptocurrency is just like buying foreign currency for a holiday. It is just an exchange of one currency for another at an agreed rate - e.g Euros for BTC (the currency symbol for bitcoin) - which is why the most common place to buy cryptocurrency is called an Exchange. 

🔴It might feel confusing when cryptocurrency like bitcoin is talked about as having a price, whereas for dollar, euro etc we are used to talking about an exchange rate. 

➡️These two terms - price/exchange rate - are interchangeable and simply reflect the fact that currency values - especially crypto - are constantly changing. 

🔴The price simply reflects the interaction between buyers and sellers on each Exchange, which organically maintain parity with each other. (again explained in detail elsewhere). An overall representation of price can then be reached by aggregating the price from the main exchanges.

Choosing the Right Crypto Exchange: https://t.me/techpsyche/774

What Is Crypto Arbitrage: https://t.me/techpsyche/881

How can I spot a bullish trend?: https://t.me/techpsyche/925

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Who is Data Scientist?

He/she is responsible for collecting, analyzing and interpreting the results, through a large amount of data. This process is used to take an important decision for the business, which can affect the growth and help to face compititon in the market.

A data scientist analyzes data to extract actionable insight from it. More specifically, a data scientist:

Determines correct datasets and variables.

Identifies the most challenging data-analytics problems.

Collects large sets of data- structured and unstructured, from different sources.

Cleans and validates data ensuring accuracy, completeness, and uniformity.

Builds and applies models and algorithms to mine stores of big data.

Analyzes data to recognize patterns and trends.

Interprets data to find solutions.

Communicates findings to stakeholders using tools like visualization.

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Tableau vs Power BI: Must-Know Differences

Tableau:
- Usage: Best suited for advanced data visualization and analytics with complex datasets.
- Best For: Users who need highly customized, detailed visualizations and are working with large datasets across different industries.
- Data Handling: Performs well with large datasets and offers strong data handling capabilities.
- Visuals: Known for its superior, highly customizable visuals, making it perfect for complex and artistic data representations.
- Integration: Easily connects with a wide range of data sources but may require more technical skills for setup.
- Sharing: Sharing options are available, but often require paid licenses for viewers.
- Cost: Tableau tends to be more expensive, especially at the enterprise level.
- Automation: Supports automated data refreshes, but the setup might be more complex than Power BI.

Power BI:
- Usage: Designed for data analysis and creating interactive, dynamic reports that integrate seamlessly with other Microsoft tools.
- Best For: Users who need to combine data from multiple sources and create reports with interactive dashboards.
- Data Handling: Efficiently handles large datasets without performance issues and integrates smoothly with Microsoft platforms.
- Visuals: Offers interactive dashboards and visualizations, with built-in themes that are user-friendly.
- Integration: Easily integrates with Microsoft products like Excel, Azure, and SQL Server, making it a natural choice for Microsoft users.
- Sharing: Built-in cloud sharing features allow for real-time collaboration and automatic updates.
- Cost: Power BI is more affordable, with a free version available and competitive pricing for the Pro version.
- Automation: Offers strong automation features with real-time data refreshes and scheduling, making it ideal for dynamic reporting.

Tableau is a great choice for users who prioritize advanced visualizations, while Power BI is better for those who need easy integration with Microsoft tools, affordability, and real-time collaboration.

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3. Website

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5. AI Model

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4. Meeting

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Innovations Shaping the Future of 2030

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