AI Roadmap 2025: Journey into the Future of AI

AI Roadmap 2025: How to Learn AI from Scratch (Bangla) | For Developers & Beginners

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Summary

Dive into the future of Artificial Intelligence with this comprehensive guide in Bangla, presented by Learn with Sumit - LWS. This video titled "AI Roadmap 2025: How to Learn AI from Scratch" offers a complete roadmap covering Machine Learning, Deep Learning, Generative AI, and Agentic AI, tailored for both developers and beginners. Understand the vital math prerequisites like Linear Algebra, Statistics, and Calculus, essential for reaching research-level AI. A perfect starting point for applications developers aiming to venture into AI, providing a step-by-step breakdown of the interrelations between different AI branches.

Highlights

Understand the complete AI learning roadmap and how different AI areas interconnect step-by-step. 📈
Discover the essential mathematical foundations needed for advanced AI research. 📚
Get tailored advice for application developers on entering and succeeding in the AI field. 🚀

Key Takeaways

AI Learning Roadmap: Get a structured roadmap to navigate through AI concepts from ML and DL to Generative AI. 🌟
Math Matters: Learn why Linear Algebra, Statistics, and Calculus are crucial for advancing in AI research. 📊
Developer Guide: Tailored pathways for application developers to delve into the world of AI. 🚀

Overview

Join us as we embark on an enlightening journey into the realm of Artificial Intelligence with this highly informative Bangla tutorial, brought to you by Learn with Sumit - LWS. This video is designed to be your go-to resource for understanding AI from the ground up, featuring a structured roadmap that guides you through the essentials of Machine Learning, Deep Learning, and beyond, equipping both newbies and seasoned developers with the insights they need.

Dive deeper into the mathematical core of AI, where you'll discover why subjects such as Linear Algebra, Statistics, and Calculus play a pivotal role in mastering and pushing the boundaries of AI research. This video ensures you grasp the importance of these subjects, making complex ideas accessible and engaging for all viewers.

Finally, whether you're a budding developer or an experienced coder, find a wealth of tailored advice to help you navigate the rapidly evolving landscape of AI. Learn how to effectively leverage your current skills and transition into this exciting field with confidence and clarity.

Chapters

00:00 - 00:30: Introduction to AI Roadmap 2025 The introductory chapter of the 'AI Roadmap 2025' video provides an overview of what viewers can expect from the series. It outlines the complete roadmap for learning AI, starting from Machine Learning and Deep Learning and extending to Generative AI and Agentic AI. This series is tailored for both beginners and developers. Key points include a detailed breakdown of the AI learning roadmap, highlighting the interconnections between AI, ML, DL, and Generative AI. Additionally, it emphasizes the importance of mathematical prerequisites such as Linear Algebra, Statistics, and Calculus, especially for those aspiring to delve into AI research. The chapter also touches on the developer's path, providing guidance for application developers.
00:30 - 01:00: Overview of AI Learning Components This chapter provides an overview of essential components in AI learning. It begins by contextualizing the tutorial 'AI Roadmap 2025' tailored for beginners and developers. The speaker from 'Learn with Sumit - LWS - Bangladesh' outlines AI concepts ranging from Machine Learning (ML) and Deep Learning (DL) to Generative AI and Agentic AI. Emphasis is placed on understanding the structured roadmap which explains the interconnections between AI, ML, DL, and Generative AI. Additionally, the chapter highlights the importance of mathematical prerequisites such as Linear Algebra, Statistics, and Calculus for advancing in AI research, along with insights into the developer's path in AI learning.
01:00 - 01:30: Understanding Machine Learning and Deep Learning This chapter serves as an introduction to the concepts of Machine Learning and Deep Learning, presented in the context of a comprehensive AI learning roadmap. Within a video titled 'AI Roadmap 2025,' the tutorial outlines the interconnectedness of AI, ML, DL, and Generative AI, breaking them down into stages appropriate for beginners and developers. It highlights the necessary mathematical prerequisites such as Linear Algebra, Statistics, and Calculus, aiming to bridge learners to advanced research levels. Additionally, the chapter sketches a path for developers focused on application development.
01:30 - 02:00: Exploring Generative AI Chapter Title: Exploring Generative AI In this chapter, titled "Exploring Generative AI," the tutorial provides a comprehensive breakdown of the roadmap for learning AI targeted towards beginners and developers. It covers the various stages starting from Machine Learning (ML) and Deep Learning (DL) to advanced topics like Generative AI and Agentic AI. The roadmap offers a detailed look at the relationships and progression paths between these areas, helping learners chart a path to mastery. Moreover, the chapter delves into the essential mathematical prerequisites needed for AI research, highlighting the importance of Linear Algebra, Statistics, and Calculus for advanced understanding. It also provides insights into the developer’s path, emphasizing the skills and knowledge required for application development in AI.
02:00 - 02:30: Connecting AI Concepts for Beginners and Developers The chapter titled "Connecting AI Concepts for Beginners and Developers" is part of a video series "AI Roadmap 2025: How to Learn AI from Scratch (Bangla)" by Learn with Sumit - LWS - Bangladesh. This chapter is designed to provide a comprehensive understanding of how beginners and developers can learn AI, focusing particularly on the roadmap from Machine Learning (ML) and Deep Learning (DL) to Generative AI and Agentic AI. It breaks down the AI learning roadmap into manageable steps, emphasizing the interconnectedness of AI, ML, DL, and Generative AI. Additionally, it discusses the mathematical prerequisites necessary for advancing to AI research, highlighting the importance of Linear Algebra, Statistics, and Calculus. For developers specifically, this section outlines the path one might follow as an application developer in the field of AI.

Legacy source notes (not a transcript)

Segment 1: 00:00 - 02:30 This is a video titled "AI Roadmap 2025: How to Learn AI from Scratch (Bangla) | For Developers & Beginners" by Learn with Sumit - LWS - Bangladesh. Video description: AI Roadmap 2025: Bangla tutorial-এ AI শিখুন। Machine Learning (ML), Deep Learning থেকে Generative AI এবং Agentic AI পর্যন্ত সম্পূর্ণ Roadmap। For beginners & developers. 📋 এই টিউটোরিয়ালে আমরা দেখব: ✅ Roadmap Breakdown: AI শেখার সম্পূর্ণ রোডম্যাপ, যেখানে AI, ML, DL, এবং Generative AI-এর মধ্যে সম্পর্ক ধাপে ধাপে দেখানো হয়েছে। ✅ Math Prerequisites: AI-এর রিসার্চ লেভেলে যাওয়ার জন্য Linear Algebra, Statistics, এবং Calculus কেন জরুরি, তা বুঝব। ✅ Developer’s Path: একজন অ্যাপ্লিকেশন ডেভেলপার হিসেবে