Choosing an AI Career in 2026? Understand Every AI Role Before You Start | CampusX

CampusX · Beginner ·📐 ML Fundamentals ·2mo ago
In this video, we break down a complete AI roadmap for 2026 — from the fundamentals to advanced topics like Machine Learning, Deep Learning, NLP, Transformers, and Generative AI. Instead of trying to learn every new tool, this roadmap focuses on building strong fundamentals and a clear learning path so you can progress toward becoming an AI Engineer or Data Scientist. Roadmap: https://roadmap.sh/r/ai-roadmap-for-2026---final-draft CampusX AI Courses: https://learnwith.campusx.in/s/store Notes: https://learnwith.campusx.in/s/store/courses/YouTube%20Notes Queries? - https://www.instagram.com/campusx.official What you’ll learn in this video: • Programming foundations for AI • Python and essential AI development tools • Mathematics required for ML and AI • Machine Learning fundamentals and algorithms • Deep Learning and neural networks • NLP and Transformers • Generative AI and Large Language Models • Important AI frameworks and tools • How to build AI projects for your portfolio • Career path to become an AI engineer 📱 Grow with us: CampusX' LinkedIn: https://www.linkedin.com/company/campusx-official My LinkedIn: https://www.linkedin.com/in/nitish-singh-03412789 Find Study Partner: https://discord.gg/PsWu8R87Z8 E-mail us at support@campusx.in ⌚Chapters⌚ 00:00:00 - Introduction and goal of the AI roadmap 00:03:40 - Why most people fail to learn AI 00:08:20 - How the roadmap is structured (end-to-end plan) 00:15:10 - Programming foundations required for AI 00:28:40 - Python and essential tools for AI development 00:45:30 - Mathematics required for AI (linear algebra, statistics, probability) 01:05:20 - Machine Learning fundamentals and algorithms 01:28:30 - Deep Learning concepts and neural networks 01:50:40 - Natural Language Processing and transformers 02:07:30 - Generative AI and Large Language Models 02:27:00 - AI tools, frameworks, and development stack 02:46:30 - Building real AI projects and portfolio 03:02:30 - Career roadmap and how to become an AI engin
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Chapters (13)

Introduction and goal of the AI roadmap
3:40 Why most people fail to learn AI
8:20 How the roadmap is structured (end-to-end plan)
15:10 Programming foundations required for AI
28:40 Python and essential tools for AI development
45:30 Mathematics required for AI (linear algebra, statistics, probability)
1:05:20 Machine Learning fundamentals and algorithms
1:28:30 Deep Learning concepts and neural networks
1:50:40 Natural Language Processing and transformers
2:07:30 Generative AI and Large Language Models
2:27:00 AI tools, frameworks, and development stack
2:46:30 Building real AI projects and portfolio
3:02:30 Career roadmap and how to become an AI engin
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