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🚀 How to Become a Self-Taught AI Developer?

AI is transforming the world, and the best part? You don’t need a formal degree to break into the field! With the right roadmap and hands-on practice, anyone can become an AI developer. Here’s how you can do it:

1️⃣ Master the Fundamentals of Programming

Start with Python, as it’s the most popular language for AI. Learn data structures, algorithms, and object-oriented programming (OOP). Practice coding on LeetCode and HackerRank.

👉How to get started Python: https://www.youtube.com/watch?v=EGdhnSEWKok
How to Create & Use Python Virtual Environments | ML Project Setup + GitHub Actions CI/CD https://youtu.be/qYYYgS-ou7Q

👉Beginner's Guide to Python Programming. Getting started now: https://youtu.be/ISv6XIl1hn0

👉Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok

👉OOP in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw

2️⃣ Build a Strong Math Foundation

AI relies on:
🔹 Linear Algebra – Matrices, vectors (used in deep learning) https://youtu.be/BNa2s6OtWls
🔹 Probability & Statistics – Bayesian reasoning, distributions https://youtube.com/playlist?list=PL0nX4ZoMtjYEl_1ONxAZHu65DPCQcsHmI&si=tAz0B3yoATAjE8Fx
🔹 Calculus – Derivatives, gradients (used in optimization)

📚 Learn from 3Blue1Brown, Khan Academy, or MIT OpenCourseWare.

3️⃣ Learn Machine Learning (ML)

Start with traditional ML before deep learning:
Supervised Learning – Linear regression, decision trees https://youtube.com/playlist?list=PL0nX4ZoMtjYGV8Ff_s2FtADIPfwlHst8B&si=buC-eP3AZkIjzI_N
Unsupervised Learning – Clustering, PCA
Reinforcement Learning – Q-learning, deep Q-networks

🔗 Best course? Andrew Ng’s ML Course on Coursera.

4️⃣ Dive into Deep Learning

Once comfortable with ML, explore:
Neural Networks (ANNs, CNNs, RNNs, Transformers)
TensorFlow & PyTorch (Industry-standard deep learning frameworks)
Computer Vision & NLP

Try Fast.ai or the Deep Learning Specialization by Andrew Ng.

5️⃣ Build Real-World Projects

The best way to learn AI? DO AI. 🚀
💡 Train models with Kaggle datasets
💡 Build a chatbot, image classifier, or recommendation system
💡 Contribute to open-source AI projects

6️⃣ Stay Updated & Join the AI Community

AI evolves fast! Stay ahead by:
🔹 Following Google AI, OpenAI, DeepMind
🔹 Engaging in Reddit r/MachineLearning, LinkedIn AI discussions
🔹 Attending AI conferences like NeurIPS & ICML

7️⃣ Create a Portfolio & Apply for AI Roles

📌 Publish projects on GitHub
📌 Share insights on Medium/Towards Data Science
📌 Network on LinkedIn & Kaggle

No CS degree? No problem! AI is about curiosity, consistency, and hands-on experience. Start now, keep learning, and let’s build the future with AI. 🚀

Tagging AI learners & enthusiasts: What’s your AI learning journey like? Let’s connect!. 🔥👇

#AI #MachineLearning #DeepLearning #Python #ArtificialIntelligence #SelfTaught



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🚀 How to Become a Self-Taught AI Developer?

AI is transforming the world, and the best part? You don’t need a formal degree to break into the field! With the right roadmap and hands-on practice, anyone can become an AI developer. Here’s how you can do it:

1️⃣ Master the Fundamentals of Programming

Start with Python, as it’s the most popular language for AI. Learn data structures, algorithms, and object-oriented programming (OOP). Practice coding on LeetCode and HackerRank.

👉How to get started Python: https://www.youtube.com/watch?v=EGdhnSEWKok
How to Create & Use Python Virtual Environments | ML Project Setup + GitHub Actions CI/CD https://youtu.be/qYYYgS-ou7Q

👉Beginner's Guide to Python Programming. Getting started now: https://youtu.be/ISv6XIl1hn0

👉Data Structures with Projects full tutorial for beginners
https://www.youtube.com/watch?v=lbdKQI8Jsok

👉OOP in Python - beginners Crash Course https://www.youtube.com/watch?v=I7z6i1QTdsw

2️⃣ Build a Strong Math Foundation

AI relies on:
🔹 Linear Algebra – Matrices, vectors (used in deep learning) https://youtu.be/BNa2s6OtWls
🔹 Probability & Statistics – Bayesian reasoning, distributions https://youtube.com/playlist?list=PL0nX4ZoMtjYEl_1ONxAZHu65DPCQcsHmI&si=tAz0B3yoATAjE8Fx
🔹 Calculus – Derivatives, gradients (used in optimization)

📚 Learn from 3Blue1Brown, Khan Academy, or MIT OpenCourseWare.

3️⃣ Learn Machine Learning (ML)

Start with traditional ML before deep learning:
Supervised Learning – Linear regression, decision trees https://youtube.com/playlist?list=PL0nX4ZoMtjYGV8Ff_s2FtADIPfwlHst8B&si=buC-eP3AZkIjzI_N
Unsupervised Learning – Clustering, PCA
Reinforcement Learning – Q-learning, deep Q-networks

🔗 Best course? Andrew Ng’s ML Course on Coursera.

4️⃣ Dive into Deep Learning

Once comfortable with ML, explore:
Neural Networks (ANNs, CNNs, RNNs, Transformers)
TensorFlow & PyTorch (Industry-standard deep learning frameworks)
Computer Vision & NLP

Try Fast.ai or the Deep Learning Specialization by Andrew Ng.

5️⃣ Build Real-World Projects

The best way to learn AI? DO AI. 🚀
💡 Train models with Kaggle datasets
💡 Build a chatbot, image classifier, or recommendation system
💡 Contribute to open-source AI projects

6️⃣ Stay Updated & Join the AI Community

AI evolves fast! Stay ahead by:
🔹 Following Google AI, OpenAI, DeepMind
🔹 Engaging in Reddit r/MachineLearning, LinkedIn AI discussions
🔹 Attending AI conferences like NeurIPS & ICML

7️⃣ Create a Portfolio & Apply for AI Roles

📌 Publish projects on GitHub
📌 Share insights on Medium/Towards Data Science
📌 Network on LinkedIn & Kaggle

No CS degree? No problem! AI is about curiosity, consistency, and hands-on experience. Start now, keep learning, and let’s build the future with AI. 🚀

Tagging AI learners & enthusiasts: What’s your AI learning journey like? Let’s connect!. 🔥👇

#AI #MachineLearning #DeepLearning #Python #ArtificialIntelligence #SelfTaught

BY Epython Lab




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Following this, Sebi, in an order passed in January 2022, established that the administrators of a Telegram channel having a large subscriber base enticed the subscribers to act upon recommendations that were circulated by those administrators on the channel, leading to significant price and volume impact in various scrips. Recently, Durav wrote on his Telegram channel that users' right to privacy, in light of the war in Ukraine, is "sacred, now more than ever." Oh no. There’s a certain degree of myth-making around what exactly went on, so take everything that follows lightly. Telegram was originally launched as a side project by the Durov brothers, with Nikolai handling the coding and Pavel as CEO, while both were at VK. Andrey, a Russian entrepreneur living in Brazil who, fearing retaliation, asked that NPR not use his last name, said Telegram has become one of the few places Russians can access independent news about the war. That hurt tech stocks. For the past few weeks, the 10-year yield has traded between 1.72% and 2%, as traders moved into the bond for safety when Russia headlines were ugly—and out of it when headlines improved. Now, the yield is touching its pandemic-era high. If the yield breaks above that level, that could signal that it’s on a sustainable path higher. Higher long-dated bond yields make future profits less valuable—and many tech companies are valued on the basis of profits forecast for many years in the future.
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