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Ever wondered how to transition into the AI engineering space or what skills truly matter in this fast-evolving field? In this episode of Data Neighbor Podcast, we sit down with Aishwarya Reganti, a Generative AI Tech Lead at Amazon's AWS, to dive into the essentials of AI engineering and separate the signal from the noise surrounding AI today.

Aishwarya shares her journey from researcher to enterprise innovator and reveals:
🎙️ AI Engineering practical tips, roadmaps, and myths busted.
💡 How to get started with AI, whether you're a mid-career switcher or a recent graduate.
📚 A clear roadmap of skills to master, including concepts like RAG, agents, and prompt engineering.
🛠️ Practical advice for building AI projects that solve real problems and avoid unnecessary complexity.
🚀 How to stay focused amidst the overwhelming amount of AI content and buzzwords.

Whether you're looking to break into the field, better understand the hype around AI, or learn how to apply AI concepts simply and effectively, this episode is packed with insights for you.

🔗 Links Mentioned in the Episode

Aishwarya's Maven Course: https://lnkd.in/eiBx3Eaz
DeepLearning.AI Free Courses: https://www.deeplearning.ai/

Tools Highlighted: NotebookLM, Claude, PotSmart, and more

🎧 Follow Aishwarya
LinkedIn:   / areganti  

Chapters:

0:00 Introduction
2:00 Aishwarya's Journey: From Research to Enterprise AI
6:20 What Generative AI Can (and Can’t) Do
13:00 Breaking Down Key AI Concepts: RAG, Agents, and LLMs
19:00 The Daily Life of an AI Engineer
27:00 Advice for Aspiring AI Professionals
35:00 Building AI Projects That Matter
43:00 Tools of the Trade: NotebookLM, Claude, and More
50:00 The Future of Prompt Engineering
57:00 Evaluation: The Hardest Part of AI Development
1:08:00 Predictions for the Future of AI Roles
1:09:40 Closing Thoughts

Connect with Hai, Sravya, and Shane (let us know YouTube sent you!):
Hai Guan : https://linkedin.openinapp.co/4qi1r
Sravya Madipalli : https://linkedin.openinapp.co/9be8c
Shane Butler : https://linkedin.openinapp.co/b02fe

If you need personalized advice for your data science career roadmap, send us a message on LinkedIn or post a comment below!


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