How to get job in AI, Data Science and Data Analytics
UNIQ Technologies
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How to get job in AI, Data Science and Data Analytics
2 299 просмотров · 4 месяца назад
UNIQ Technologies
143 тыс. подписчиков
2 299 просмотров · 4 месяца назад
AI is a tool that boosts productivity but won't replace engineers who master it. Success requires strong math, coding fundamentals, and clear communication skills.
120 Days Developer Challange ( Fill This Form )
https://forms.gle/2NBC78NqENvp5A3Z8
contact:
Free Career Guidance Contact
HR - Nithya
Mobile Number - 9150014169
Whatsapp - https://wa.link/2mrgmw
Hussain sir and Rajesh discuss how AI, like electricity, is a general-purpose technology that will impact every field. While it won't replace engineers, it will significantly boost the productivity of those who master it. The professionals most at risk are those who fail to adapt to these new tools.
Key takeaways for career growth include:
Master Fundamentals: Success relies on strong roots in math, coding, and software engineering to use AI effectively.
Role-Specific Skills: Data Analysts need SQL and Python; Data Scientists require statistics; and AI Engineers must understand the full software development lifecycle.
Soft Skills: Clear communication and problem-solving remain vital, as AI cannot yet handle complex tasks independently.
Avoid Shortcuts: Short-term "mastery" courses cannot replace the deep technical expertise needed to debug and refine AI-generated work.
00:00 - 00:45: Introduction of Rajesh (Data Scientist and AI Engineer) and the initial discussion on whether AI will replace programmers.
00:46 - 02:15: AI defined as a "general-purpose technology" (like electricity) and its impact on productivity and job security.
02:16 - 03:50: Discussion on which IT roles are at risk and why human intelligence remains vital for problem-solving.
03:51 - 04:55: The importance of fundamentals in software engineering and the limitations of AI-generated code.
04:56 - 06:15: Campus interview insights: What recruiters look for (marks, projects, and honesty).
06:16 - 08:30: Deep dive into specific skill sets for Data Analysts, Data Scientists, and AI Engineers.
08:31 - 10:45: Comparison between "AI Engineering" and "Generative AI" (GenAI), and the myth of 30-day mastery courses.
10:46 - End: Final career advice for youngsters: Focus on continuous learning and core skills over social media hype.
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