Upskilling in AI as a Data Scientist

Hosted by Manisha Arora

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What you'll learn

Strengthening Programming Fundamentals

Develop expertise in data pull and manipulation through clean, organized code.

Mastering end-to-end AI Project Lifecycle

Understand the lifecycle of ML/AI Projects, from business scoping to deployment and monitoring.

Building Hands-on Projects

Identify real-world problems, apply the learnings, and build projects that drive value.

Resources for Skill Development

Gain insights into the best tools, platforms, and communities for professional development.

Why this topic matters

The industry is at the cusp of a revolution driven by the latest advancements in AI. Discover how you can master AI/ML principles and stay relevant in the domain. Build strategies to enhance your programming skills, understand project lifecycle, and build hands-on projects. We will discuss resources to stay ahead of the curve. You'll also receive actionable tips to start implementing right away!

You'll learn from

Manisha Arora

Data Science Lead at Google

I am a seasoned Data Science professional with 10+ years of experience leading data science teams and driving business growth through data-driven decision making. Having navigated the job market both as a candidate and as an interviewer, I understand the intricacies of the hiring process from both perspectives.


I am passionate about democratizing data science and enabling others level up in their careers. I found PrepVector to enable aspiring professionals to excel in their data science careers. I have taught 350+ data professionals through my courses at Maven & PrepVector. I am committed to providing individuals with the skills and knowledge required to thrive in the industry.

Previously at

Google
Axtria
MIT research group
UT Austin
Cincinnati Bearcats
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