Why I Chose AI Upskilling
49sRelatable career upgrade story with a clear 'why' that resonates with professionals fearing obsolescence.
▶ Play ClipAI Summary
The video is a testimonial from Isha, a finance professional who took the Applied Data Science course from the University of Chicago, likely sponsored by Simplilearn. She discusses her background, her motivation for upskilling in AI, the course's value and structure, and how it helped her build a stronger professional profile.
Chapters
[00:06]
Background and Motivation
Isha has about eight years of experience combining data science, analytics, and finance. She took this course to upgrade her skills due to the recent AI advancements.
[00:40]
Prior Work Experience
She previously worked in India for Tommy Hilfiger, handling cost-benefit analysis for stores, focusing on profitability ratios and footfall.
[01:09]
Course Value and Selection
She chose this course because it was less expensive than alternatives from Stanford or UCLA, and the content structure was really good.
[01:42]
Course Content and Python Basics
The initial optional Python basics were detailed and helpful for beginners, covering functions, if loops, pandas, and numpy. The course itself is advanced in applied data science.
[02:23]
Course Experience and Resources
She enjoyed the LLM introduction, the course flow, the module structure, and the shared recordings and documents, which allowed her to review and rewrite code.
[03:05]
Impact on Career
Building agents and chatbots helped her create a strong data profile, making her look more professional and versed in industry concepts.
[03:49]
Career Journey and Final Advice
She has worked with UBS, Credit Suisse, and in investment banking in London, and currently lives in California. She believes continuous learning opens many career gates.
Mentioned in this Video
💡 Key Takeaways
💡
AI Advancements as a Upskilling Trigger
Highlights how the need to adapt to new-age AI motivates professionals to seek further education.
00:21
📊
Career Trajectory with Continuous Learning
Shows a clear path from finance roles in London to a data science career in California.
03:49
🔧
Using Recorded Sessions and Codes
Underscores the value of flexible learning resources for reinforcing and practicing new skills.
02:37
💡
Necessity of Continuous Learning
Directly states that in the current era, upskilling is a requirement for career growth.
04:02Full Transcript
[00:06] from University of Chicago and I around eight years of experience in finance and which is an amalgamation of data science, analytics, field like that. My intention to do this course was because this the a recent new age AI
[00:21] advancement that's happening and the technologies that we have been using for financial analysis or other kinds of analysis in different industries have actually changed a lot and I wanted an upgrade, so I picked the course.
[00:40] Fashion back in India, but the domain that I was working on was finance. I was dealing with their cost benefit analysis at various stores around the country in India for Tommy Hilfiger and my main job was to
[00:55] understand the profitability ratios, what kind of profits are being made in each of those stores, what is the footfall and then yes, I moved to Kodak footfall and then yes, I moved to Kodak which is again a finance.
[01:09] googled few courses and there were a lot of options. Also the price it was not as expensive as other courses that Stanford UCLA or even other colleges here around in US were
[01:25] offering. So the content that you had on the course structure it was really good actually. [music] >> [music] >> but your first basics on Python were
[01:42] really good actually even some for someone who is not >> familiar with the coding languages like Python, it was given in detail. You mentioned about everything pandas, numpy before
[01:54] >> [music] >> the basics of Python functions, and if loops, etc., etc. That I found at the initial optional course on Python is the must for any data science, [music] stats, or AI-based course if you want to
[02:09] do that. The course definitely is advanced. It in [music] applied data science from University of Chicago. So, for me it was the perfect blend [music] of what all I wanted. I enjoyed the LLM introduction,
[02:23] how you have explained everything, the flow of the course, the addition of after every module, the way modules were structured, and also the recordings. Sometimes you miss
[02:37] the class, or you know, you have your stuff going on, but then the recordings documents that were also shared were really good because you could just look into those, use those codes again, rewrite them, and learn so much
[02:52] >> about how to create an agent, and on how to create a chatbot. actually helped me to build a very strong data [music] profile, which I was
[03:05] lacking earlier. So, that way it it makes me look more professional. It makes me look more versed [music] with the concepts that will be used in the industry. So, I think that's a great start for me.
[03:24] gym and swimming. [music] I'm into sports, so I do I play badminton regularly. Other than that, I like spending time >> [music] >> and friends. I like having good quality
[03:37] >> and friends. I like having good quality time with people around me. >> Within eight years I'm in California. [laughter]
[03:49] I've done my lot of study [music] in finance. I worked with UBS, Credit Suisse. I worked in London in hardcore investment banking, worked in fraud and [music] of Chicago for my master's program.
[04:02] And now I'm in California. So, I think continuous learning just opens up lot of gates for your career and future. And currently the era that we are in, uh, you don't have any other choice also. You have to keep upgrading yourself.
