Data Science is a fast-moving field with new tools and workflows constantly emerging. This article highlights the most-read and discussed articles from the past month, covering topics such as coding, productivity, LLMs, data engineering, remote work, time series forecasting, generative AI, interactive dashboards in Excel, and strategic data analysis. The article also introduces new authors on TDS.
Data Science: Practical Insights and Solutions
Stay up-to-date with the latest trends and insights in data science with our standout articles from the past month. From coding tips to career transitions, we cover a range of topics that provide actionable advice based on real-world experience.
Coding was Hard Until I Learned These 2 Things
Natassha Selvaraj shares practical tips for aspiring programmers, including developing a growth mindset and establishing a daily programming routine.
6 Bad Habits Killing Your Productivity in Data Science
Donato Riccio discusses the importance of breaking detrimental habits to improve productivity in data science workflows.
Forget RAG, the Future is RAG-Fusion
Adrian H. Raudaschl introduces RAG-Fusion, a modified technique for optimizing large language models, addressing challenges and improving performance.
Introducing KeyLLM — Keyword Extraction with LLMs
Maarten Grootendorst unveils KeyLLM, an extension to the KeyBERT package that facilitates efficient keyword extraction at scale.
How to Become a Data Engineer
Mike Shakhomirov provides a practical guide for beginner-level IT practitioners and intermediate software engineers looking to transition into a data engineering role.
Creating New Data Scientists in the Age of Remote Work
Stephanie Kirmer explores the challenges faced by early-career data scientists in remote and hybrid work models, offering insights for employers and employees to navigate this new territory.
TimesNet: The Latest Advance in Time Series Forecasting
Marco Peixeiro delves into TimesNet, a state-of-the-art model for time series analysis that utilizes a CNN-based architecture to achieve exceptional results.
5 Generative AI Use Cases Companies Can Implement Today
Barr Moses highlights five promising use cases where generative AI approaches can bring value to businesses.
Interactive Dashboards in Excel
Jake Teo provides a step-by-step tutorial on creating sleek interactive dashboards using Excel, a widely-used data engineering and analytics software.
Strategic Data Analysis (Part 1)
Viyaleta Apgar offers a structured overview of the questions data analysts are tasked with answering, providing various approaches to effectively address them. Start with Part 1 to understand the basic types of questions data analysts encounter.
Unlock the Potential of AI for Your Company
Embrace the power of AI to transform your organization and gain a competitive edge. Here are some key steps to get started:
Identify Automation Opportunities
Locate key customer interaction points that can benefit from AI and streamline your processes.
Define KPIs
Ensure your AI initiatives are aligned with measurable business outcomes to track their impact.
Select an AI Solution
Choose AI tools that meet your specific needs and offer customization options for optimal results.
Implement Gradually
Start with a pilot project, gather data, and expand AI usage gradually to maximize its benefits.
For expert advice on AI KPI management and to learn how AI can transform your business, contact us at hello@itinai.com. Stay updated on AI insights by following us on Telegram and Twitter @itinaicom.
Spotlight: AI Sales Bot
Enhance your customer engagement and automate interactions across all stages of the customer journey with our AI Sales Bot. Visit itinai.com/aisalesbot to explore how AI can redefine your sales processes.
List of Useful Links:
- AI Lab in Telegram @aiscrumbot – free consultation
- Productivity Tips, Data Career Insights, and Other Recent Must-Reads
- Towards Data Science – Medium
- Twitter – @itinaicom
