Free Online Courses with Certificate | Udacity Free Courses | Eduonix | IP Cybersecurity | Coursera | Premium Certified Courses

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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If I were to start Computer Science in 2024 💫🚀

- Harvard - Stanford
- MIT - IBM - Telegram
- Microsoft - Google

❯ CS50 from Harvard
http://cs50.harvard.edu/x/2023/certificate/

❯ C/C++
http://ocw.mit.edu/courses/6-s096-effective-programming-in-c-and-c-january-iap-2014/

❯ Python
http://cs50.harvard.edu/python/2022/

https://t.me/dsabooks

❯ SQL
http://online.stanford.edu/courses/soe-ydatabases0005-databases-relational-databases-and-sql

https://t.me/sqlanalyst

❯ DSA
http://techdevguide.withgoogle.com/paths/data-structures-and-algorithms/

https://t.me/crackingthecodinginterview/290

❯ Java
http://learn.microsoft.com/shows/java-for-beginners/

https://t.me/Java_Programming_Notes

❯ JavaScript
http://learn.microsoft.com/training/paths/web-development-101/

https://t.me/javascript_courses

❯ TypeScript
http://learn.microsoft.com/training/paths/build-javascript-applications-typescript/

❯ C#
http://learn.microsoft.com/users/dotnet/collections/yz26f8y64n7k07

❯ Mathematics (incl. Statistics)
ocw.mit.edu/search/?d=Mathematics&s=department_course_numbers.sort_coursenum

❯ Data Science
cognitiveclass.ai/courses/data-science-101

https://t.me/datasciencefun/1141

❯ Machine Learning
http://developers.google.com/machine-learning/crash-course

❯ Deep Learning
introtodeeplearning.com

t.me/machinelearning_deeplearning/

❯ Full Stack Web (HTML/CSS)
pll.harvard.edu/course/cs50s-web-programming-python-and-javascript/2023-05

t.me/webdevcoursefree/594

❯ OS, Networking
ocw.mit.edu/courses/6-033-computer-system-engineering-spring-2018/

❯ Compiler Design
online.stanford.edu/courses/soe-ycscs1-compilers


Make sure to scroll through the above messages 💝 you will definitely find more interesting things 🤠

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UI UX Designer Preparation FREE Resources 👇👇
https://t.me/videoeditingskill/52

FREE RESOURCES TO LEARN MACHINE LEARNING
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Intro to ML by MIT Free Course

https://openlearninglibrary.mit.edu/courses/course-v1:MITx+6.036+1T2019/about

Machine Learning for Everyone FREE BOOK

https://buildmedia.readthedocs.org/media/pdf/pymbook/latest/pymbook.pdf

ML Crash Course by Google

https://developers.google.com/machine-learning/crash-course

Advanced Machine Learning with Python Github

https://github.com/PacktPublishing/Advanced-Machine-Learning-with-Python

Statistics Free Resources

https://t.me/datasciencefun/1835

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Complete Roadmap to learn DSA in 30 days

Day 1-5: Introduction to Data Structures and Algorithms
- Understand the importance of DSA in programming
- Learn about different types of data structures (arrays, linked lists, stacks, queues, trees, graphs)
- Study basic algorithms like searching and sorting

Day 6-10: Arrays and Strings
- Dive deeper into arrays and strings
- Learn about common operations and algorithms on arrays and strings
- Practice solving problems related to arrays and strings

Day 11-15: Linked Lists
- Study linked lists and their variations (singly linked list, doubly linked list, circular linked list)
- Implement basic operations on linked lists
- Solve problems involving linked lists

Day 16-20: Stacks and Queues
- Learn about stacks and queues and their applications
- Implement stack and queue data structures
- Solve problems using stacks and queues

Day 21-25: Trees and Graphs
- Study binary trees, binary search trees, AVL trees, heaps, and graphs
- Understand traversal algorithms (inorder, preorder, postorder) for trees
- Implement basic graph algorithms (DFS, BFS)
- Solve problems related to trees and graphs

Day 26-30: Advanced Topics
- Study advanced data structures like hash tables, tries, segment trees
- Learn about dynamic programming, backtracking, and divide and conquer algorithms
- Practice solving complex problems that require a combination of data structures and algorithms

Throughout the 30 days, make sure to practice regularly by solving coding problems on platforms like LeetCode, HackerRank, or Codeforces. Additionally, review your concepts regularly and seek out resources like online tutorials, textbooks, and study groups to deepen your understanding of DSA.

5⃣ Free DSA resources to crack coding interview

👉 GeekforGeeks

👉 Leetcode

👉 Hackerrank

👉 DSA Resources

👉 FreeCodeCamp

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Best way to prepare for Python interviews 👇👇

1. Fundamentals: Strengthen your understanding of Python basics, including data types, control structures, functions, and object-oriented programming concepts.

2. Data Structures and Algorithms: Familiarize yourself with common data structures (lists, dictionaries, sets, etc.) and algorithms. Practice solving coding problems on platforms like LeetCode or HackerRank.

3. Problem Solving: Develop problem-solving skills by working on real-world scenarios. Understand how to approach and solve problems efficiently using Python.

4. Libraries and Frameworks: Be well-versed in popular Python libraries and frameworks relevant to the job, such as NumPy, Pandas, Flask, or Django. Demonstrate your ability to apply these tools in practical situations.

5. Web Development (if applicable): If the position involves web development, understand web frameworks like Flask or Django. Be ready to discuss your experience in building web applications using Python.

6. Database Knowledge: Have a solid understanding of working with databases in Python. Know how to interact with databases using SQLAlchemy or Django ORM.

7. Testing and Debugging: Showcase your proficiency in writing unit tests and debugging code. Understand testing frameworks like pytest and debugging tools available in Python.

8. Version Control: Familiarize yourself with version control systems, particularly Git, and demonstrate your ability to collaborate on projects using Git.

9. Projects: Showcase relevant projects in your portfolio. Discuss the challenges you faced, solutions you implemented, and the impact of your work.

10. Soft Skills: Highlight your communication and collaboration skills. Be ready to explain your thought process and decision-making during technical discussions.

Best Resource to learn Python

Python Interview Questions with Answers

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Python for Data Analysis and Visualization

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💫🌈🧑‍💻👩‍💻⚛️Free Full Stack Certifications Courses to try in 2024

🔸HTML, CSS
https://freecodecamp.org/learn/2022/responsive-web-design

http://cs50.harvard.edu/web/

🔸Full Stack Development Roadmap
https://t.me/webdevcoursefree/752

🔸Java
https://data-flair.training/courses/free-java-course/

http://learn.microsoft.com/shows/java-for-beginners/

🔸 JavaScript Roadmap
https://t.me/javascript_courses/493

🔸Neo4j
https://graphacademy.neo4j.com/courses/neo4j-certification/

🔸React
https://hackerrank.com/skills-verification/react_basic

🔸Angular
https://hackerrank.com/skills-verification/angular_intermediate

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Free Resources to learn Ethical Hacking and Cyber Security
👇👇

Free Cyber Security course from Udacity

http://imp.i115008.net/7mJmZ3

Fundamentals of Computer Hacking

https://www.udemy.com/course/computer-hacking-fundamentals/

Ethical Hacking - SQL Injection Attack

https://www.udemy.com/course/sql-injection-ethical-hacking/

Cyber Security for Beginners Free Book

https://heimdalsecurity.com/pdf/cyber_security_for_beginners_ebook.pdf

Information Security Free Certified Course

https://www.freecodecamp.org/learn/information-security/

Complete Ethical Hacking Bootcamp 2021: Zero to Mastery

https://t.me/ethicalhackingtoday/3

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✅ Learn New Skills FREE 🔰

1. Web Development ➝
◀️ https://t.me/webdevcoursefree

2. CSS ➝
◀️ http://css-tricks.com

3. JavaScript ➝
◀️ http://t.me/javascript_courses

4. React ➝
◀️ http://react-tutorial.app

5. Data Engineering ➝
◀️ https://t.me/sql_engineer

6. Data Science  ➝
◀️ https://t.me/datasciencefun

7. Python ➝
◀️ http://pythontutorial.net

8. SQL ➝
◀️  https://t.me/sqlanalyst

9. Git and GitHub ➝
◀️ http://GitFluence.com

10. Blockchain ➝
◀️ https://t.me/Bitcoin_Crypto_Web

11. Mongo DB ➝
◀️ http://mongodb.com

12. Node JS ➝
◀️ http://nodejsera.com

13. English Speaking ➝
◀️ https://t.me/englishlearnerspro

14. C#➝
◀️ https://learn.microsoft.com/en-us/training/paths/get-started-c-sharp-part-1/

15. Excel➝
◀️ https://t.me/excel_analyst

16. Generative AI➝
◀️ https://t.me/generativeai_gpt

17. Java
◀️ https://t.me/Java_Programming_Notes

18. Artificial Intelligence
◀️ https://t.me/machinelearning_deeplearning

19. Data Structure & Algorithms
◀️ https://t.me/dsabooks

20. Backend Development
◀️ https://imp.i115008.net/rn2nyy

21. Python for AI
◀️ https://deeplearning.ai/short-courses/ai-python-for-beginners/

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10 best graduate degrees in demand by 2030

1. Artificial Intelligence and Machine Learning
2. Data Science and Analytics
3. Healthcare Administration
4. Cybersecurity
5. Sustainable and Renewable Energy Engineering
6. Biotechnology and Biomedical Engineering
7. Public Health
8. Robotics Engineering
9. Environmental Science and Sustainability
10. Business Analytics and Strategy

Hey guys,

Here are some best Telegram Channels for free education in 2024
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Python Free Courses

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Crack your coding Interviews

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Free Full Stack Certifications Courses to try in 2024:

🔸Python
http://developers.google.com/edu/python
https://freecodecamp.org/learn/scientific-computing-with-python/
🔸JavaScript
https://hackerrank.com/skills-verification/javascript_intermediate

http://learn.microsoft.com/training/paths/build-javascript-applications-typescript

🔸SQL
https://hackerrank.com/skills-verification/sql_advanced

http://online.stanford.edu/courses/soe-ydatabases0005-databases-relational-databases-and-sql

🔸Data Science
https://mylearn.oracle.com/ou/learning-path/become-an-oci-data-science-professional-2023/121944

http://cognitiveclass.ai/courses/data-science-101

🔸HTML, CSS
https://freecodecamp.org/learn/2022/responsive-web-design

http://cs50.harvard.edu/web/

🔸DevOps
https://mylearn.oracle.com/ou/learning-path/become-an-oci-devops-professional-2023/121756

🔸Machine Learning
https://freecodecamp.org/learn/machine-learning-with-python

http://developers.google.com/machine-learning/crash-course

🔸Java
https://data-flair.training/courses/free-java-course/

http://learn.microsoft.com/shows/java-for-beginners/

🔸Neo4j
https://graphacademy.neo4j.com/courses/neo4j-certification/

🔸React
https://hackerrank.com/skills-verification/react_basic

🔸Angular
https://hackerrank.com/skills-verification/angular_intermediate

🔸C#
http://learn.microsoft.com/users/dotnet/collections/yz26f8y64n7k07
https://hackerrank.com/skills-verification/c_sharp_basic

🔸Go
https://hackerrank.com/skills-verification/golang_intermediate

🔸Security
https://mylearn.oracle.com/ou/learning-path/become-a-cloud-security-professional-2023/121923

🔸Backend (API Dev)
https://freecodecamp.org/learn/back-end-development-and-apis/

🔸Software Engineering
http://techdevguide.withgoogle.com/paths/principles/

🔸DSA
http://techdevguide.withgoogle.com/paths/data-structures-and-algorithms/

🔸OS, Networking
http://ocw.mit.edu/courses/6-033-computer-system-engineering-spring-2018/

SQL Quick Notes to refresh your concepts

Here is the list of latest trending tech stacks in 2024 👇👇

1. Frontend Development:
   - React.js: Known for its component-based architecture and strong community support.
   - Vue.js: Valued for its simplicity and flexibility in building user interfaces.
   - Angular: Still widely used, especially in enterprise applications.

2. Backend Development:
   - Node.js: Popular for building scalable and fast network applications using JavaScript.
   - Django: Preferred for its rapid development capabilities and robust security features.
   - Spring Boot: Widely used in Java-based applications for its ease of use and integration capabilities.

3. Mobile Development:
   - Flutter: Known for building natively compiled applications for mobile, web, and desktop from a single codebase.
   - React Native: Continues to be popular for building cross-platform applications with native capabilities.

4. Cloud Computing and DevOps:
   - AWS (Amazon Web Services), Azure, Google Cloud: Leading cloud service providers offering extensive services for computing, storage, and networking.
   - Docker and Kubernetes: Essential for containerization and orchestration of applications in a cloud-native environment.
   - Terraform: Infrastructure as code tool for managing and provisioning cloud infrastructure.

5. Data Science and Machine Learning:
   - Python: Dominant language for data science and machine learning, with libraries like NumPy, Pandas, and Scikit-learn.
   - TensorFlow and PyTorch: Leading frameworks for building and training machine learning models.
   - Apache Spark: Used for big data processing and analytics.

6. Cybersecurity:
   - SIEM Tools (Security Information and Event Management): Such as Splunk and ELK Stack, crucial for monitoring and managing security incidents.
   - Zero Trust Architecture: A security model that eliminates the idea of trust based on network location.

7. Blockchain and Cryptocurrency:
   - Ethereum: A blockchain platform supporting smart contracts and decentralized applications.
   - Hyperledger Fabric: Framework for developing permissioned, blockchain-based applications.

8. Artificial Intelligence (AI) and Natural Language Processing (NLP):
   - GPT (Generative Pre-trained Transformer) Models: Such as GPT-4, used for various natural language understanding tasks.
   - Computer Vision: Frameworks like OpenCV for image and video processing tasks.

9. Edge Computing and IoT (Internet of Things):
   - Edge Computing: Technologies that bring computation and data storage closer to the location where it is needed.
   - IoT Platforms: Such as AWS IoT, Azure IoT Hub, offering capabilities for managing and securing IoT devices and data.

Best Resources to help you with the journey 👇👇

Javascript Roadmap
https://t.me/javascript_courses/309

Best Programming Resources: https://topmate.io/coding/886839

Web Development Resources
https://t.me/webdevcoursefree

Latest Jobs & Internships
https://t.me/getjobss

Cryptocurrency Basics
https://t.me/Bitcoin_Crypto_Web/236

Python Resources
https://t.me/pythonanalyst

Data Science Resources
https://t.me/datasciencefree

Best DSA Resources
https://topmate.io/coding/886874

Udemy Free Courses with Certificate
https://t.me/udemy_free_courses_with_certi

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20 high-income skills to learn in
2024 👇

1. Artificial intelligence (AI)
2. Cloud computing
3. Data science
4. Machine learning
5. Blockchain/ Crypto
6. Data analytics and business intelligence
7. Data engineering
8. Finance
9. Web Development
10. Software development
11. UX design
12. Web design
13. Graphic design
14. Video editing
15. Content marketing
16. Blogging
17. Tech skills
18. Business analysis
19. Cybersecurity
20. Entrepreneurship
21. Freelancing
22. Sales and marketing

🖥 Roadmap of free courses for learning Python and Machine learning.

▪Data Science
▪ AI/ML
▪ Web Dev

1. Start with this
https://kaggle.com/learn/python

2. Take any one of these

❯ https://t.me/pythondevelopersindia/76

❯ https://youtu.be/rfscVS0vtbw?si=WdvcwfYR3PaLiyJQ

3. Then take this
https://netacad.com/courses/programming/pcap-programming-essentials-python

4. Attempt for this certification
https://freecodecamp.org/learn/scientific-computing-with-python/

5. Take it to next level

❯ Data Visualization
https://kaggle.com/learn/data-visualization

❯ Machine Learning
http://developers.google.com/machine-learning/crash-course

https://t.me/datasciencefun/290

❯ Deep Learning (TensorFlow)
http://kaggle.com/learn/intro-to-deep-learning

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Free Data Engineering Ebooks & Courses 👇👇
https://t.me/sql_engineer

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80% of weight loss comes from your nutrition.

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Health Fitness Tips

When you’re in an interview, it’s super important to know how to talk about your projects in a way that impresses the interviewer. Here are some key points to help you do just that:

➤ 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗢𝘃𝗲𝗿𝘃𝗶𝗲𝘄:
- Start with a quick summary of the project you worked on. What was it all about? What were the main goals? Keep it short and sweet something you can explain in about 30 seconds.

➤ 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 𝗦𝘁𝗮𝘁𝗲𝗺𝗲𝗻𝘁:
- What problem were you trying to solve with this project? Explain why this problem was important and needed addressing.

➤ 𝗣𝗿𝗼𝗽𝗼𝘀𝗲𝗱 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻:
- Describe the solution you came up with. How does it work, and why is it a good fix for the problem?

➤ 𝗬𝗼𝘂𝗿 𝗥𝗼𝗹𝗲:
- Talk about what you specifically did. What were your main tasks? Did you face any challenges, and how did you overcome them? Make sure it’s clear whether you were leading the project, a key player, or supporting the team.

➤ 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀 𝗮𝗻𝗱 𝗧𝗼𝗼𝗹𝘀:
- Mention the tech and tools you used. This shows your technical know-how and your ability to choose the right tools for the job.

➤ 𝗜𝗺𝗽𝗮𝗰𝘁 𝗮𝗻𝗱 𝗔𝗰𝗵𝗶𝗲𝘃𝗲𝗺𝗲𝗻𝘁𝘀:
- Share the results of your project. Did it make things better? How? Mention any improvements, efficiencies, or positive feedback you got.

➤ 𝗧𝗲𝗮𝗺 𝗖𝗼𝗹𝗹𝗮𝗯𝗼𝗿𝗮𝘁𝗶𝗼𝗻:
- Talk about how you collaborated. What was your role in the team? How did you communicate and contribute to the team’s success?

➤ 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁:
- Reflect on what you learned from the project. What new skills did you gain, and what would you do differently next time?

➤ 𝗧𝗶𝗽𝘀 𝗳𝗼𝗿 𝗬𝗼𝘂𝗿 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗣𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻:
- Be ready with a 30 second elevator pitch about your projects, and also have a five-minute detailed overview ready.
- If there’s a pause after you describe the project, don’t hesitate to ask if they’d like more details or if there’s a specific part they’re interested in.

By preparing your project details thoroughly and understanding what the interviewer is looking for, you can talk about your experience in a way that really showcases your skills and increases your chances of getting the job.

Best DSA RESOURCES: https://topmate.io/coding/886874

All the best 👍👍

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1️⃣ AI for beginners
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Free Coding Courses

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Few more courses ✅

𝟭.𝗗𝗮𝘁𝗮 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀
https://learn.microsoft.com/en-us/training/paths/azure-data-fundamentals-explore-non-relational-data/

𝟮.𝗦𝗾𝗹 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀
https://learn.microsoft.com/en-us/training/paths/azure-sql-fundamentals/

𝟯.𝗣𝗼𝘄𝗲𝗿 𝗕𝗜
https://learn.microsoft.com/en-us/training/paths/create-use-analvtics-reports-power-bi/

𝟰.𝗔𝘇𝘂𝗿𝗲 𝗰𝗼𝘀𝗺𝗼𝘀 𝗗𝗕
https://learn.microsoft.com/en-us/training/paths/create-use-analytics-reports-power-bi/

𝟱.𝗔𝗜 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀
https://learn.microsoft.com/en-us/training/paths/create-no-code-predictive-models-azure-machine-learning/

Here are the list of free courses if you are planning to learn Data science and Data Analytics in 2024

📌complete data analytics courses by Cisco

https://skillsforall.com/course/data-analytics-essentials?courseLang=en-US

📌data science premium course by Cisco

https://skillsforall.com/course/introduction-data-science?courseLang=en-US


📌 python for data science by IBM

https://cognitiveclass.ai/courses/python-for-data-science

📌Analyze data with excel by Microsoft

https://learn.microsoft.com/en-us/search/

📌Google analytics for both beginners and Advance by Google.

https://analytics.google.com/analytics/academy/course/7

All these courses are completely free and you will also get a certificate certificate. Once you complete this courses.

Many people reached out to me saying telegram may get banned in their countries. So I've decided to create WhatsApp channels based on your interests 👇👇

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Python Free Books & Projects: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L

Java Resources: https://whatsapp.com/channel/0029VamdH5mHAdNMHMSBwg1s

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SQL: https://whatsapp.com/channel/0029VanC5rODzgT6TiTGoa1v

Power BI: https://whatsapp.com/channel/0029Vai1xKf1dAvuk6s1v22c

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ENJOY LEARNING 👍👍

Frontend web development:

https://www.w3schools.com/html

https://www.w3schools.com/css

https://www.jschallenger.com

https://javascript30.com

https://t.me/webdevcoursefree/110

https://t.me/Programming_experts/107

Backend development:

https://learnpython.org/

https://t.me/pythondevelopersindia/314

https://www.geeksforgeeks.org/java/

https://introcs.cs.princeton.edu/java/11cheatsheet/

https://docs.microsoft.com/en-us/shows/beginners-series-to-nodejs/?languages=nodejs

Database:

https://mode.com/sql-tutorial/introduction-to-sql

https://www.sqltutorial.org/wp-content/uploads/2016/04/SQL-cheat-sheet.pdf

https://books.goalkicker.com/MySQLBook/MySQLNotesForProfessionals.pdf

https://docs.oracle.com/cd/B19306_01/server.102/b14200.pdf

https://leetcode.com/problemset/database/

Cloud Computing:

https://bit.ly/3aoxt1N

https://t.me/free4unow_backup/366

UI/UX:

https://www.freecodecamp.org/learn/responsive-web-design/

https://bit.ly/3r6F9xE

ENJOY LEARNING 👍👍

https://stanford.edu/~shervine/teaching/cs-229/cheatsheet-machine-learning-tips-and-tricks

FREE RESOURCES TO LEARN DATA ENGINEERING
👇👇

Big Data and Hadoop Essentials free course

https://bit.ly/3rLxbul

Data Engineer: Prepare Financial Data for ML and Backtesting FREE UDEMY COURSE
[4.6 stars out of 5]

https://bit.ly/3fGRjLu

Understanding Data Engineering from Datacamp

https://clnk.in/soLY

Data Engineering Free Books

https://ia600201.us.archive.org/4/items/springer_10.1007-978-1-4419-0176-7/10.1007-978-1-4419-0176-7.pdf

https://www.darwinpricing.com/training/Data_Engineering_Cookbook.pdf

Big Data of Data Engineering Free book

https://databricks.com/wp-content/uploads/2021/10/Big-Book-of-Data-Engineering-Final.pdf

https://aimlcommunity.com/wp-content/uploads/2019/09/Data-Engineering.pdf

The Data Engineer’s Guide to Apache Spark

https://t.me/datasciencefun/783?single

Data Engineering with Python

https://t.me/pythondevelopersindia/343

Data Engineering Projects -

1.End-To-End From Web Scraping to Tableau  https://lnkd.in/ePMw63ge

2. Building Data Model and Writing ETL Job https://lnkd.in/eq-e3_3J

3. Data Modeling and Analysis using Semantic Web Technologies https://lnkd.in/e4A86Ypq

4. ETL Project in Azure Data Factory - https://lnkd.in/eP8huQW3

5. ETL Pipeline on AWS Cloud - https://lnkd.in/ebgNtNRR

6. Covid Data Analysis Project - https://lnkd.in/eWZ3JfKD

7. YouTube Data Analysis 
   (End-To-End Data Engineering Project) - https://lnkd.in/eYJTEKwF

8. Twitter Data Pipeline using Airflow - https://lnkd.in/eNxHHZbY

9. Sentiment analysis Twitter:
    Kafka and Spark Structured Streaming -  https://lnkd.in/esVAaqtU

ENJOY LEARNING 👍👍

Free Courses/ Certifications for a full-stack career in 2024:

1. Web design https://freecodecamp.org/learn/2022/responsive-web-design/

2. JavaScript https://freecodecamp.org/learn/javascript-algorithms-and-data-structures/

https://bit.ly/3PI8JWB

3. Front-end libraries https://freecodecamp.org/learn/front-end-development-libraries/

5. Back-end and APIs
https://freecodecamp.org/learn/back-end-development-and-apis/

6. Databases
https://freecodecamp.org/learn/relational-database/

7. Full Stack Web Development Bootcamp
https://t.me/webdevcoursefree/461

Join @free4unow_backup for more free resources

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You don't need to spend several $𝟭𝟬𝟬𝟬𝘀 to learn Data Science.❌

Stanford University, Harvard University & Massachusetts Institute of Technology is providing free courses.💥

Here's 8 free Courses that'll teach you better than the paid ones:


1. CS50’s Introduction to Artificial Intelligence with Python (Harvard)

https://pll.harvard.edu/course/cs50s-introduction-artificial-intelligence-python

2. Data Science: Machine Learning (Harvard)

https://pll.harvard.edu/course/data-science-machine-learning

3. Artificial Intelligence (MIT)

https://lnkd.in/dG5BCPen

4. Introduction to Computational Thinking and Data Science (MIT)

https://lnkd.in/ddm5Ckk9

5. Machine Learning (MIT)

https://lnkd.in/dJEjStCw

6. Matrix Methods in Data Analysis, Signal Processing, and Machine Learning (MIT)

https://lnkd.in/dkpyt6qr

7. Statistical Learning (Stanford)

https://online.stanford.edu/courses/sohs-ystatslearning-statistical-learning

8. Mining Massive Data Sets (Stanford)

📍https://online.stanford.edu/courses/soe-ycs0007-mining-massive-data-sets

ENJOY LEARNING

Finance Paid Course for FREE with Certificate

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Coupon code: FREEDOM100

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Free courses by Google
👇👇

1. Fundamentals of Digital Marketing https://learndigital.withgoogle.com/digitalgarage/course/digital-marketing

2. Communicate your Ideas through storytelling and design https://lnkd.in/gp4zqUPA

3. Understand customers needs and online behaviours https://lnkd.in/gfpV6FW8

4. Customer Segmentation & Prospecting https://lnkd.in/gfpV6FW8

5. Google Analytics for Beginners https://lnkd.in/g-qJV-s2

6. Google Analytics Certification https://lnkd.in/gS7VwNj6

7. Getting a job using google https://lnkd.in/gMQDxu-n

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9. Business Writing https://lnkd.in/g8HJqXft

10. How to increase Productivity at work?
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12. Public Speaking & giving great Presentation s https://lnkd.in/gzzUCzKT

13. Improve communication skills https://lnkd.in/gV9H2niJ

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Confused about which field to dive into—Front-End Development (FE), Back-End Development (BE), Machine Learning (ML), or Blockchain?

Here's a concise breakdown of each, designed to clarify your options:

### Front-End Development (FE)
Key Skills:
- HTML/CSS: Fundamental for creating the structure and style of web pages.
- JavaScript: Essential for adding interactivity and functionality to websites.
- Frameworks/Libraries: React, Angular, or Vue.js for efficient and scalable front-end development.
- Responsive Design: Ensuring websites look good on all devices.
- Version Control: Git for managing code changes and collaboration.

Career Prospects:
- Web Developer
- UI/UX Designer
- Front-End Engineer

### Back-End Development (BE)
Key Skills:
- Programming Languages: Python, Java, Ruby, Node.js, or PHP for server-side logic.
- Databases: SQL (MySQL, PostgreSQL) and NoSQL (MongoDB) for data management.
- APIs: RESTful and GraphQL for communication between front-end and back-end.
- Server Management: Understanding of server, network, and hosting environments.
- Security: Knowledge of authentication, authorization, and data protection.

Career Prospects:
- Back-End Developer
- Full-Stack Developer
- Database Administrator

### Machine Learning (ML)
Key Skills:
- Programming Languages: Python and R are widely used in ML.
- Mathematics: Statistics, linear algebra, and calculus for understanding ML algorithms.
- Libraries/Frameworks: TensorFlow, PyTorch, Scikit-Learn for building ML models.
- Data Handling: Pandas, NumPy for data manipulation and preprocessing.
- Model Evaluation: Techniques for assessing model performance.

Career Prospects:
- Data Scientist
- Machine Learning Engineer
- AI Researcher

### Blockchain
Key Skills:
- Cryptography: Understanding of encryption and security principles.
- Blockchain Platforms: Ethereum, Hyperledger, Binance Smart Chain for building decentralized applications.
- Smart Contracts: Solidity for developing smart contracts.
- Distributed Systems: Knowledge of peer-to-peer networks and consensus algorithms.
- Blockchain Tools: Truffle, Ganache, Metamask for development and testing.

Career Prospects:
- Blockchain Developer
- Smart Contract Developer
- Crypto Analyst

### Decision Criteria
1. Interest: Choose an area you are genuinely interested in.
2. Market Demand: Research the current job market to see which skills are in demand.
3. Career Goals: Consider your long-term career aspirations.
4. Learning Curve: Assess how much time and effort you can dedicate to learning new skills.

Each field offers unique opportunities and challenges, so weigh your options carefully based on your personal preferences and career objectives.

Here are some telegram channels to help you build your career 👇

Web Development
https://t.me/webdevcoursefree

Jobs & Internships
https://t.me/getjobss

Blockchain
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Machine Learning
https://t.me/datasciencefun

Artificial Intelligence
https://t.me/machinelearning_deeplearning

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https://t.me/CAstudyzone

Finance Paid Course for FREE with Certificate

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Complete roadmap to learn data science in 2024 👇👇

1. Learn the Basics:
- Brush up on your mathematics, especially statistics.
- Familiarize yourself with programming languages like Python or R.
- Understand basic concepts in databases and data manipulation.

2. Programming Proficiency:
- Develop strong programming skills, particularly in Python or R.
- Learn data manipulation libraries (e.g., Pandas) and visualization tools (e.g., Matplotlib, Seaborn).

3. Statistics and Mathematics:
- Deepen your understanding of statistical concepts.
- Explore linear algebra and calculus, especially for machine learning.

4. Data Exploration and Preprocessing:
- Practice exploratory data analysis (EDA) techniques.
- Learn how to handle missing data and outliers.

5. Machine Learning Fundamentals:
- Understand basic machine learning algorithms (e.g., linear regression, decision trees).
- Learn how to evaluate model performance.

6. Advanced Machine Learning:
- Dive into more complex algorithms (e.g., SVM, neural networks).
- Explore ensemble methods and deep learning.

7. Big Data Technologies:
- Familiarize yourself with big data tools like Apache Hadoop and Spark.
- Learn distributed computing concepts.

8. Feature Engineering and Selection:
- Master techniques for creating and selecting relevant features in your data.

9. Model Deployment:
- Understand how to deploy machine learning models to production.
- Explore containerization and cloud services.

10. Version Control and Collaboration:
- Use version control systems like Git.
- Collaborate with others using platforms like GitHub.

11. Stay Updated:
- Keep up with the latest developments in data science and machine learning.
- Participate in online communities, read research papers, and attend conferences.

12. Build a Portfolio:
- Showcase your projects on platforms like GitHub.
- Develop a portfolio demonstrating your skills and expertise.

Best Resources to learn Data Science

Intro to Data Analytics by Udacity

Machine Learning course by Google

Machine Learning with Python

Data Science Interview Questions

Data Science Project ideas

Data Science: Linear Regression Course by Harvard

Machine Learning Interview Questions

Free Datasets for Projects

Please give us credits while sharing: -> https://t.me/free4unow_backup

ENJOY LEARNING 👍👍

7⃣ Free Resources To Learn Web Development

👉 HTML

https://www.w3schools.com/html/

https://web.stanford.edu/group/csp/cs21/htmlcheatsheet.pdf

👉 CSS

https://bit.ly/3uv2fRS

https://www.w3schools.com/css/

👉 Javascript

https://www.jschallenger.com/

https://javascript30.com/

👉 PHP

https://bit.ly/3QkY3wW

https://t.me/programming_guide/301

👉 React

https://t.me/webdevcoursefree/110

👉 Flask

https://bit.ly/3ilskze

https://www.codecademy.com/learn/learn-flask

👉 Projects in HTML, CSS & Lava script

https://t.me/Programming_experts/107

ENJOY LEARNING 👍👍

Here is the list of latest trending tech stacks in 2024 👇👇

1. Frontend Development:
- React.js: Known for its component-based architecture and strong community support.
- Vue.js: Valued for its simplicity and flexibility in building user interfaces.
- Angular: Still widely used, especially in enterprise applications.

2. Backend Development:
- Node.js: Popular for building scalable and fast network applications using JavaScript.
- Django: Preferred for its rapid development capabilities and robust security features.
- Spring Boot: Widely used in Java-based applications for its ease of use and integration capabilities.

3. Mobile Development:
- Flutter: Known for building natively compiled applications for mobile, web, and desktop from a single codebase.
- React Native: Continues to be popular for building cross-platform applications with native capabilities.

4. Cloud Computing and DevOps:
- AWS (Amazon Web Services), Azure, Google Cloud: Leading cloud service providers offering extensive services for computing, storage, and networking.
- Docker and Kubernetes: Essential for containerization and orchestration of applications in a cloud-native environment.
- Terraform: Infrastructure as code tool for managing and provisioning cloud infrastructure.

5. Data Science and Machine Learning:
- Python: Dominant language for data science and machine learning, with libraries like NumPy, Pandas, and Scikit-learn.
- TensorFlow and PyTorch: Leading frameworks for building and training machine learning models.
- Apache Spark: Used for big data processing and analytics.

6. Cybersecurity:
- SIEM Tools (Security Information and Event Management): Such as Splunk and ELK Stack, crucial for monitoring and managing security incidents.
- Zero Trust Architecture: A security model that eliminates the idea of trust based on network location.

7. Blockchain and Cryptocurrency:
- Ethereum: A blockchain platform supporting smart contracts and decentralized applications.
- Hyperledger Fabric: Framework for developing permissioned, blockchain-based applications.

8. Artificial Intelligence (AI) and Natural Language Processing (NLP):
- GPT (Generative Pre-trained Transformer) Models: Such as GPT-4, used for various natural language understanding tasks.
- Computer Vision: Frameworks like OpenCV for image and video processing tasks.

9. Edge Computing and IoT (Internet of Things):
- Edge Computing: Technologies that bring computation and data storage closer to the location where it is needed.
- IoT Platforms: Such as AWS IoT, Azure IoT Hub, offering capabilities for managing and securing IoT devices and data.

Best Resources to help you with the journey 👇👇

Javascript Roadmap
https://t.me/javascript_courses/309

Best Programming Resources: https://topmate.io/coding/886839

Web Development Resources
https://t.me/webdevcoursefree

Latest Jobs & Internships
https://t.me/getjobss

Cryptocurrency Basics
https://t.me/Bitcoin_Crypto_Web/236

Python Resources
https://t.me/pythonanalyst

Data Science Resources
https://t.me/datasciencefree

Best DSA Resources
https://topmate.io/coding/886874

Udemy Free Courses with Certificate
https://t.me/udemy_free_courses_with_certi

Join @free4unow_backup for more free resources.

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Finance Paid Course for FREE with Certificate

Link: https://bit.ly/4fGwbzD

Coupon code: FREEDOM100

Note: This is a special coupon code which I got for my subscribers so please apply it manually while enrolling.

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ENJOY LEARNING 👍👍

🔺 Free Machine learning Courses

1️⃣ Intro to ML course : an introductory and self-paced course to start machine learning.

2️⃣ ML for Everybody course : A simple approach to learning machine learning concepts.

3️⃣ ML in Python course : focus on machine learning with Python and Scikit-Learn.

4️⃣ ML Crash Course : A quick but comprehensive introduction to machine learning.

5️⃣ CS229 : ML : An advanced course for those who want to deepen their knowledge

Companies List that are HIRING for REMOTE Jobs

https://www.linkedin.com/posts/sqlspecialist_companies-list-that-are-hiring-for-remote-activity-7228299409623531520-NtlF?utm_source=share&utm_medium=member_android

Free courses from Microsoft ✅

𝟭.𝗗𝗮𝘁𝗮 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀
https://learn.microsoft.com/en-us/training/paths/azure-data-fundamentals-explore-non-relational-data/

𝟮.𝗦𝗾𝗹 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀
https://learn.microsoft.com/en-us/training/paths/azure-sql-fundamentals/

𝟯.𝗣𝗼𝘄𝗲𝗿 𝗕𝗜
https://learn.microsoft.com/en-us/training/paths/create-use-analvtics-reports-power-bi/

𝟰.𝗔𝘇𝘂𝗿𝗲 𝗰𝗼𝘀𝗺𝗼𝘀 𝗗𝗕
https://learn.microsoft.com/en-us/training/paths/create-use-analytics-reports-power-bi/

𝟱.𝗔𝗜 𝗳𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀
https://learn.microsoft.com/en-us/training/paths/create-no-code-predictive-models-azure-machine-learning/

Master SQL step-by-step! From basics to advanced, here are the key topics you need for a solid SQL foundation. 🚀

1. Foundations:
- Learn basic SQL syntax, including SELECT, FROM, WHERE clauses.
- Understand data types, constraints, and the basic structure of a database.

2. Database Design:
- Study database normalization to ensure efficient data organization.
- Learn about primary keys, foreign keys, and relationships between tables.

3. Queries and Joins:
- Practice writing simple to complex SELECT queries.
- Master different types of joins (INNER, LEFT, RIGHT, FULL) to combine data from multiple tables.

4. Aggregation and Grouping:
- Explore aggregate functions like COUNT, SUM, AVG, MAX, and MIN.
- Understand GROUP BY clause for summarizing data based on specific criteria.

5. Subqueries and Nested Queries:
- Learn how to use subqueries to perform operations within another query.
- Understand the concept of nested queries and their practical applications.

6. Indexing and Optimization:
- Study indexing for enhancing query performance.
- Learn optimization techniques, such as avoiding SELECT * and using appropriate indexes.

7. Transactions and ACID Properties:
- Understand the basics of transactions and their role in maintaining data integrity.
- Explore ACID properties (Atomicity, Consistency, Isolation, Durability) in database management.

8. Views and Stored Procedures:
- Create and use views to simplify complex queries.
- Learn about stored procedures for reusable and efficient query execution.

9. Security and Permissions:
- Understand SQL injection risks and how to prevent them.
- Learn how to manage user permissions and access control.

10. Advanced Topics:
- Explore advanced SQL concepts like window functions, CTEs (Common Table Expressions), and recursive queries.
- Familiarize yourself with database-specific features (e.g., PostgreSQL's JSON functions, MySQL's spatial data types).

11. Real-world Projects:
- Apply your knowledge to real-world scenarios by working on projects.
- Practice with sample databases or create your own to reinforce your skills.

12. Continuous Learning:
- Stay updated on SQL advancements and industry best practices.
- Engage with online communities, forums, and resources for ongoing learning and problem-solving.

Here are some free resources to learn & practice SQL 👇👇

Udacity free course- https://imp.i115008.net/AoAg7K

SQL For Data Analysis: https://t.me/sqlanalyst

For Practice- https://stratascratch.com/?via=free

SQL Learning Series: https://t.me/sqlspecialist/567

Top 10 SQL Projects with Datasets: https://t.me/DataPortfolio/16

Join for more free resources: https://t.me/free4unow_backup

ENJOY LEARNING 👍👍

ChatGPT Prompt to learn any skill
👇👇
I am seeking to become an expert professional in [Making ChatGPT prompts perfectly]. I would like ChatGPT to provide me with a complete course on this subject, following the principles of Pareto principle and simulating the complexity, structure, duration, and quality of the information found in a college degree program at a prestigious university. The course should cover the following aspects: Course Duration: The course should be structured as a comprehensive program, spanning a duration equivalent to a full-time college degree program, typically four years. Curriculum Structure: The curriculum should be well-organized and divided into semesters or modules, progressing from beginner to advanced levels of proficiency. Each semester/module should have a logical flow and build upon the previous knowledge. Relevant and Accurate Information: The course should provide all the necessary and up-to-date information required to master the skill or knowledge area. It should cover both theoretical concepts and practical applications. Projects and Assignments: The course should include a series of hands-on projects and assignments that allow me to apply the knowledge gained. These projects should range in complexity, starting from basic exercises and gradually advancing to more challenging real-world applications. Learning Resources: ChatGPT should share a variety of learning resources, including textbooks, research papers, online tutorials, video lectures, practice exams, and any other relevant materials that can enhance the learning experience. Expert Guidance: ChatGPT should provide expert guidance throughout the course, answering questions, providing clarifications, and offering additional insights to deepen understanding. I understand that ChatGPT's responses will be generated based on the information it has been trained on and the knowledge it has up until September 2021. However, I expect the course to be as complete and accurate as possible within these limitations. Please provide the course syllabus, including a breakdown of topics to be covered in each semester/module, recommended learning resources, and any other relevant information

(Tap on above text to copy)

Free Programming and Data Analytics Resources 👇👇

✅ Data science and Data Analytics Free Courses by Google

https://developers.google.com/edu/python/introduction

https://grow.google/intl/en_in/data-analytics-course/?tab=get-started-in-the-field

https://cloud.google.com/data-science?hl=en

https://developers.google.com/machine-learning/crash-course

https://t.me/datasciencefun/1371

🔍 Free Data Analytics Courses by Microsoft

1. Get started with microsoft dataanalytics
https://learn.microsoft.com/en-us/training/paths/data-analytics-microsoft/

2. Introduction to version control with git
https://learn.microsoft.com/en-us/training/paths/intro-to-vc-git/

3. Microsoft azure ai fundamentals
https://learn.microsoft.com/en-us/training/paths/get-started-with-artificial-intelligence-on-azure/

🤖 Free AI Courses by Microsoft

1. Fundamentals of AI by Microsoft

https://learn.microsoft.com/en-us/training/paths/get-started-with-artificial-intelligence-on-azure/

2. Introduction to AI with python by Harvard.

https://pll.harvard.edu/course/cs50s-introduction-artificial-intelligence-python

📚 Useful Resources for the Programmers

Data Analyst Roadmap
https://t.me/sqlspecialist/94

Free C course from Microsoft
https://docs.microsoft.com/en-us/cpp/c-language/?view=msvc-170&viewFallbackFrom=vs-2019

Interactive React Native Resources
https://fullstackopen.com/en/part10

Python for Data Science and ML
https://t.me/datasciencefree/68

Ethical Hacking Bootcamp
https://t.me/ethicalhackingtoday/3

Unity Documentation
https://docs.unity3d.com/Manual/index.html

Advanced Javascript concepts
https://t.me/Programming_experts/72

Oops in Java
https://nptel.ac.in/courses/106105224

Intro to Version control with Git
https://docs.microsoft.com/en-us/learn/modules/intro-to-git/0-introduction

Python Data Structure and Algorithms
https://t.me/programming_guide/76

Free PowerBI course by Microsoft
https://docs.microsoft.com/en-us/users/microsoftpowerplatform-5978/collections/k8xidwwnzk1em

Data Structures Interview Preparation
https://t.me/crackingthecodinginterview/309?single

🍻 Free Programming Courses by Microsoft

❯ JavaScript
http://learn.microsoft.com/training/paths/web-development-101/

❯ TypeScript
http://learn.microsoft.com/training/paths/build-javascript-applications-typescript/

❯ C#
http://learn.microsoft.com/users/dotnet/collections/yz26f8y64n7k07

Join @free4unow_backup for more free resources.

ENJOY LEARNING 👍👍

7. Web Programming:

Learn how to build your website.

https://pll.harvard.edu/course/cs50s-web-programming-python-and-javascript

Share this telegram channel with your friends: https://t.me/udacityfreecourse

6. Entrepreneurship in Emerging Economies:

Learn how to start a successful business in countries where the economy is growing fast.

https://pll.harvard.edu/course/entrepreneurship-in-emerging-economies