Hi guys,
I got this query from many people asking if there is any demand for web development, data science, machine learning, cybersecurity or similar fields in the future. Many people who are new to these fields are wondering if AI would replace their jobs or if these fields will still be relevant.
The short answer is yes, there is still a significant demand for these skills, and they are expected to remain relevant for the foreseeable future. Here's a breakdown of each field:
1. Web Development: With the continuous growth of the internet and the increasing number of online businesses, web development remains a vital skill. The demand for dynamic and responsive websites, as well as web applications, ensures that web developers will always have opportunities.
2. Data Science: As companies accumulate more data, the need for skilled data scientists to analyze and interpret this data is growing. Data-driven decision-making is becoming essential for businesses, making data science a highly sought-after field.
3. Machine Learning: Machine learning is a subset of AI that involves teaching computers to learn from data. Its applications range from recommendation systems to predictive analytics and autonomous systems. The field is rapidly expanding and is expected to create numerous job opportunities.
4. Cybersecurity: With the increasing number of cyber threats and attacks, cybersecurity has become a top priority for organizations. Professionals in this field are crucial for protecting sensitive information and ensuring the security of digital infrastructure.
While AI is indeed advancing and automating many tasks, it is also creating new opportunities and fields of study. AI will likely augment rather than replace professionals in these areas, enabling them to work more efficiently and effectively. Adapting to new technologies and continuously upskilling will be key to staying relevant in the evolving job market.
In conclusion, take an overview of each field and see if that interests you. Pick up a field which you can do for years which will make you an expert in long run. Experts are highly valued & irreplaceable in any field. AI might automate simple tasks, but it can't replace the depth of experience and expertise you bring.
Give your best, leave the rest ✅
I got this query from many people asking if there is any demand for web development, data science, machine learning, cybersecurity or similar fields in the future. Many people who are new to these fields are wondering if AI would replace their jobs or if these fields will still be relevant.
The short answer is yes, there is still a significant demand for these skills, and they are expected to remain relevant for the foreseeable future. Here's a breakdown of each field:
1. Web Development: With the continuous growth of the internet and the increasing number of online businesses, web development remains a vital skill. The demand for dynamic and responsive websites, as well as web applications, ensures that web developers will always have opportunities.
2. Data Science: As companies accumulate more data, the need for skilled data scientists to analyze and interpret this data is growing. Data-driven decision-making is becoming essential for businesses, making data science a highly sought-after field.
3. Machine Learning: Machine learning is a subset of AI that involves teaching computers to learn from data. Its applications range from recommendation systems to predictive analytics and autonomous systems. The field is rapidly expanding and is expected to create numerous job opportunities.
4. Cybersecurity: With the increasing number of cyber threats and attacks, cybersecurity has become a top priority for organizations. Professionals in this field are crucial for protecting sensitive information and ensuring the security of digital infrastructure.
While AI is indeed advancing and automating many tasks, it is also creating new opportunities and fields of study. AI will likely augment rather than replace professionals in these areas, enabling them to work more efficiently and effectively. Adapting to new technologies and continuously upskilling will be key to staying relevant in the evolving job market.
In conclusion, take an overview of each field and see if that interests you. Pick up a field which you can do for years which will make you an expert in long run. Experts are highly valued & irreplaceable in any field. AI might automate simple tasks, but it can't replace the depth of experience and expertise you bring.
Give your best, leave the rest ✅
👍2
🔎 How to generate a photo of a non-existent person! 🔎
😎 If you want to create a fake account on a social network, you can use another person's photo, but this is not the best option. It is better to use the following service to generate photos of non-existent people:
🤯. Open this website: https://thispersondoesnotexist.com/
🤯. Visiting the website, we immediately get a photo of a non-existent person.
🤯. Updating the page, you will see a new generated image.
⚠️ That's it, you can update the resource until you are satisfied with the photo. The site works very fast which is an undoubted plus. Many sites based on the work of artificial intelligence are often very slow. ⚠️
➡️ Need 200 Reactions on this Post
😎 If you want to create a fake account on a social network, you can use another person's photo, but this is not the best option. It is better to use the following service to generate photos of non-existent people:
🤯. Open this website: https://thispersondoesnotexist.com/
🤯. Visiting the website, we immediately get a photo of a non-existent person.
🤯. Updating the page, you will see a new generated image.
⚠️ That's it, you can update the resource until you are satisfied with the photo. The site works very fast which is an undoubted plus. Many sites based on the work of artificial intelligence are often very slow. ⚠️
➡️ Need 200 Reactions on this Post
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Let's explore different data fields today 😄
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Top 21 skills to learn this year 👇
1. Artificial Intelligence and Machine Learning: Understanding AI algorithms and applications.
2. Data Science: Proficiency in tools like Python/ R, Jupyter Notebook, and GitHub, with the ability to apply data science algorithms to solve real-world problems.
3. Cybersecurity: Protecting data and systems from cyber threats.
4. Cloud Computing: Proficiency in platforms like AWS, Azure, and Google Cloud.
5. Blockchain Technology: Understanding blockchain architecture and applications beyond cryptocurrencies.
6. Digital Marketing: Expertise in SEO, social media, and online advertising.
7. Programming: Skills in languages such as Python, JavaScript, and Go.
8. UX/UI Design: Creating intuitive and effective user interfaces and experiences.
9. Consulting: Expertise in providing strategic advice, improving business processes, and implementing solutions to drive business growth.
10. Data Analysis and Visualization: Proficiency in tools like Excel, SQL, Tableau, and Power BI to analyze and present data effectively.
11. Business Analysis & Project Management: Using tools and methodologies like Agile and Scrum.
12. Remote Work Tools: Proficiency in tools for remote collaboration and productivity.
13. Financial Literacy: Understanding personal finance, investment, and cryptocurrencies.
14. Emotional Intelligence: Skills in empathy, communication, and relationship management.
15. Business Acumen: A deep understanding of how businesses operate, including strategic thinking, market analysis, and financial literacy.
16. Investment Banking: Knowledge of financial markets, valuation methods, mergers and acquisitions, and financial modeling.
17. Mobile App Development: Skills in developing apps for iOS and Android using Swift, Kotlin, or React Native.
18. Financial Management: Proficiency in financial planning, analysis, and tools like QuickBooks and SAP.
19. Web Development: Proficiency in front-end and back-end development using HTML, CSS, JavaScript, and frameworks like React, Angular, and Node.js.
20. Data Engineering: Skills in designing, building, and maintaining data pipelines and architectures using tools like Hadoop, Spark, and Kafka.
21. Soft Skills: Improving leadership, teamwork, and adaptability skills.
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1. Artificial Intelligence and Machine Learning: Understanding AI algorithms and applications.
2. Data Science: Proficiency in tools like Python/ R, Jupyter Notebook, and GitHub, with the ability to apply data science algorithms to solve real-world problems.
3. Cybersecurity: Protecting data and systems from cyber threats.
4. Cloud Computing: Proficiency in platforms like AWS, Azure, and Google Cloud.
5. Blockchain Technology: Understanding blockchain architecture and applications beyond cryptocurrencies.
6. Digital Marketing: Expertise in SEO, social media, and online advertising.
7. Programming: Skills in languages such as Python, JavaScript, and Go.
8. UX/UI Design: Creating intuitive and effective user interfaces and experiences.
9. Consulting: Expertise in providing strategic advice, improving business processes, and implementing solutions to drive business growth.
10. Data Analysis and Visualization: Proficiency in tools like Excel, SQL, Tableau, and Power BI to analyze and present data effectively.
11. Business Analysis & Project Management: Using tools and methodologies like Agile and Scrum.
12. Remote Work Tools: Proficiency in tools for remote collaboration and productivity.
13. Financial Literacy: Understanding personal finance, investment, and cryptocurrencies.
14. Emotional Intelligence: Skills in empathy, communication, and relationship management.
15. Business Acumen: A deep understanding of how businesses operate, including strategic thinking, market analysis, and financial literacy.
16. Investment Banking: Knowledge of financial markets, valuation methods, mergers and acquisitions, and financial modeling.
17. Mobile App Development: Skills in developing apps for iOS and Android using Swift, Kotlin, or React Native.
18. Financial Management: Proficiency in financial planning, analysis, and tools like QuickBooks and SAP.
19. Web Development: Proficiency in front-end and back-end development using HTML, CSS, JavaScript, and frameworks like React, Angular, and Node.js.
20. Data Engineering: Skills in designing, building, and maintaining data pipelines and architectures using tools like Hadoop, Spark, and Kafka.
21. Soft Skills: Improving leadership, teamwork, and adaptability skills.
Join for more: 👇
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ENJOY LEARNING 👍👍
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Useful Telegram Channels to boost your career in 2025 😄👇
Free Courses with Certificate
Web Development
Data Science & Machine Learning
Programming books
Python Free Courses
Data Analytics
Ethical Hacking & Cyber Security
English Speaking & Communication
Stock Marketing & Investment Banking
Excel
ChatGPT Hacks
SQL
Tableau & Power BI
Coding Projects
Data Science Projects
Jobs & Internship Opportunities
Coding Interviews
Udemy Free Courses with Certificate
Data Analyst Interview
Data Analyst Jobs
Python Interview
ChatGPT Hacks
ENJOY LEARNING 👍👍
Free Courses with Certificate
Web Development
Data Science & Machine Learning
Programming books
Python Free Courses
Data Analytics
Ethical Hacking & Cyber Security
English Speaking & Communication
Stock Marketing & Investment Banking
Excel
ChatGPT Hacks
SQL
Tableau & Power BI
Coding Projects
Data Science Projects
Jobs & Internship Opportunities
Coding Interviews
Udemy Free Courses with Certificate
Data Analyst Interview
Data Analyst Jobs
Python Interview
ChatGPT Hacks
ENJOY LEARNING 👍👍
👍3
Complete Ethical Hacking Roadmap
👇👇
1. Introduction to Ethical Hacking
- Definition
- Purpose
- Types of Hackers
- Legal and Ethical Considerations
2. Networking Basics
- TCP/IP
- OSI Model
- Subnetting
- DNS
- DHCP
3. Operating Systems
- Linux
- Windows
- macOS
- Command Line Basics
4. Cybersecurity Fundamentals
- Encryption
- Firewalls
- Antivirus
- IDS/IPS
5. Programming Languages
- Python
- Javascript
- Bash Scripting
- SQL
- C/ C++/ Java/ Ruby
6. Scanning and Enumeration
- Port Scanning
- Service Enumeration
- Vulnerability Scanning
7. Exploitation
- Common Vulnerabilities and Exploits
- Metasploit Framework
- Buffer Overflows
8. Web Application Security
- OWASP Top Ten
- SQL Injection
- Cross-Site Scripting (XSS)
9. Wireless Network Hacking
- Wi-Fi Security
- WEP, WPA, WPA2
- Wireless Attacks
10. Social Engineering
- Phishing
- Spear Phishing
- Social Engineering Toolkit (SET)
11. Sniffing and Spoofing
- Man-in-the-Middle Attacks
- ARP Spoofing
- DNS Spoofing
12. Malware Analysis
- Types of Malware
- Sandbox Analysis
- Signature-Based and Behavior-Based Detection
13. Incident Response and Handling
- Incident Response Process
- Digital Forensics
- Chain of Custody
14. Penetration Testing
- Types of Penetration Testing
- Methodology
- Reporting
15. Cryptography
- Symmetric and Asymmetric Encryption
- Hashing Algorithms
- Digital Signatures
16. Mobile Hacking
- Android and iOS Security
- Mobile Application Security
17. Cloud Security
- AWS, Azure, Google Cloud
- Security Best Practices
18. IoT Security
- Internet of Things Risks
- Securing IoT Devices
19. Legal and Compliance
- Computer Fraud and Abuse Act (CFAA)
- GDPR, HIPAA, PCI DSS
20. Cybersecurity Tools
- Nmap, Wireshark, Burp Suite
- Snort, Nessus, Aircrack-ng
21. Career Path and Certifications
- Certified Ethical Hacker (CEH)
- Offensive Security Certified Professional (OSCP)
- CISSP, CompTIA Security+
---------------------------------------------------------
Some good resources to learn Ethical Hacking
1. Tutorials & Courses
- Informarion Security Free Course
- Ethical Hacking Bootcamp
- Network Hacking Course
2. Telegram Channels
- Cyber Security and Ethical Hacking
- Ethical Hacking Books
3. Books
- Ultimate Linux Free Book
- Python for Ethical Hacking
4. Ethical Hacking Forums
Join @free4unow_backup for more free resources
ENJOY LEARNING 👨💻🔒
👇👇
1. Introduction to Ethical Hacking
- Definition
- Purpose
- Types of Hackers
- Legal and Ethical Considerations
2. Networking Basics
- TCP/IP
- OSI Model
- Subnetting
- DNS
- DHCP
3. Operating Systems
- Linux
- Windows
- macOS
- Command Line Basics
4. Cybersecurity Fundamentals
- Encryption
- Firewalls
- Antivirus
- IDS/IPS
5. Programming Languages
- Python
- Javascript
- Bash Scripting
- SQL
- C/ C++/ Java/ Ruby
6. Scanning and Enumeration
- Port Scanning
- Service Enumeration
- Vulnerability Scanning
7. Exploitation
- Common Vulnerabilities and Exploits
- Metasploit Framework
- Buffer Overflows
8. Web Application Security
- OWASP Top Ten
- SQL Injection
- Cross-Site Scripting (XSS)
9. Wireless Network Hacking
- Wi-Fi Security
- WEP, WPA, WPA2
- Wireless Attacks
10. Social Engineering
- Phishing
- Spear Phishing
- Social Engineering Toolkit (SET)
11. Sniffing and Spoofing
- Man-in-the-Middle Attacks
- ARP Spoofing
- DNS Spoofing
12. Malware Analysis
- Types of Malware
- Sandbox Analysis
- Signature-Based and Behavior-Based Detection
13. Incident Response and Handling
- Incident Response Process
- Digital Forensics
- Chain of Custody
14. Penetration Testing
- Types of Penetration Testing
- Methodology
- Reporting
15. Cryptography
- Symmetric and Asymmetric Encryption
- Hashing Algorithms
- Digital Signatures
16. Mobile Hacking
- Android and iOS Security
- Mobile Application Security
17. Cloud Security
- AWS, Azure, Google Cloud
- Security Best Practices
18. IoT Security
- Internet of Things Risks
- Securing IoT Devices
19. Legal and Compliance
- Computer Fraud and Abuse Act (CFAA)
- GDPR, HIPAA, PCI DSS
20. Cybersecurity Tools
- Nmap, Wireshark, Burp Suite
- Snort, Nessus, Aircrack-ng
21. Career Path and Certifications
- Certified Ethical Hacker (CEH)
- Offensive Security Certified Professional (OSCP)
- CISSP, CompTIA Security+
---------------------------------------------------------
Some good resources to learn Ethical Hacking
1. Tutorials & Courses
- Informarion Security Free Course
- Ethical Hacking Bootcamp
- Network Hacking Course
2. Telegram Channels
- Cyber Security and Ethical Hacking
- Ethical Hacking Books
3. Books
- Ultimate Linux Free Book
- Python for Ethical Hacking
4. Ethical Hacking Forums
Join @free4unow_backup for more free resources
ENJOY LEARNING 👨💻🔒
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