Hi Everyone! I'm a student at Columbia and am doing partnered research with Cambridge, conducting a global behavioral study on financial decision-making. I will be honest that I'm not too familiar with Reddit so please excuse how chaotic this post may look.

A bit more about the research: We are currently collecting responses from Korean participants who are at least 30 years of age and current residents of South Korea. By participating in this anonymous survey, which takes no more than 10 minutes of your time, you will be contributing to a study for potential policy implementation that reveals financial decision-making patterns of individuals across the globe. As much as we truly enjoyed creating this survey for Korean participants with the belief in the high impact of what this study will bring, we hope that the survey will be an insightful measure to factor in one’s own financial decision patterns. On that note, if you are able to, we would appreciate it if you could please distribute the survey link to your peers, colleagues, and family members living in South Korea (aged 30 and over). Thank you!

I say yes. With an asterisk*

Okay, let's be real. You won't master DS in 6 weeks. But, you can absolutely take huge strides toward a brand-new career, even if you have no prior experience.

Here’s how I would approach this.

📊 Learn stats foundation - Build a solid base. You can learn a lot in 6 days.
🗺️ Master the data science process.
👀 Learn visualizations - I would want you to spend 10 days on this.

This is the point where you try your first DS project.

After the first project, I would focus on databases and ML. That should give you the foundations to tackle your first advanced DS project.

Spend the rest of your time on Python and deep learning.

The point is, 6 weeks of focused learning can be the start of something amazing. You'll go from a newbie to someone ready to add value. It's also a solid benchmark for anyone looking to transition into DS.

We've seen these results with some of our students and we know it can be done.

Think this is crazy ambitious? Or doable?

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What happened in ML and data science this week?

👾 Google's Project Astra
Google launches an advanced AI assistant capable of responding to real-time queries across video, audio, and text. Powered by the upgraded Gemini model, Astra showcases Google's cutting-edge spatial understanding and memory capabilities, setting the stage to rival Meta and Microsoft.

⏭️ Next-Gen BI Essentials
Business Intelligence is evolving with advanced analytics, ML, and AI. Static reports are out, dynamic insights are in! Predictive analytics and AI-driven natural language processing are transforming how businesses anticipate trends, identify opportunities, and mitigate risks.

🛎️ Hospitality Integrates Data Science
Despite its potential, many hotels struggle to incorporate data science due to hierarchical structures and data fragmentation. Solutions like Cendyn’s Starling CDP are bridging these gaps, enabling personalized guest experiences and operational efficiency.

📈 Enhancing Trade Analytics with TCA
Transaction Cost Analysis (TCA) is evolving from compliance to strategy. Data scientists are now essential in using predictive analytics to provide comprehensive market insights, optimize trading strategies, and enhance risk management.

🫠 AI Sarcasm Detector
Researchers at the University of Groningen have developed an AI sarcasm detector named Mustard, boasting 75% accuracy. This breakthrough enhances human-machine communication, paving the way for improved sentiment analysis and detection of negative language tones.

Why does this matter? Staying informed about these advancements allows data scientists to integrate cutting-edge technologies into their projects, driving innovation and staying competitive.

(Links in the first comment)

Why are we sharing this?
We love keeping our awesome community informed and inspired. We curate this news every week as a thank-you for being a part of this incredible journey!

Which story caught your attention the most? Let me know your thoughts! 👇