Data Science Related Topics 
Analytics Vidhya
OCTOBER 12, 2024
Introduction Data science is a rapidly growing tech field that’s transforming business decision-making. In this article, we’ve listed some of the best free […] The post 19 Free Data Science Courses by Harvard and IBM appeared first on Analytics Vidhya.
Analytics Vidhya
JUNE 12, 2025
Landing a data science role isn’t just about coding and modeling anymore. I’ll also provide you with 20 sample behavioral questions […] The post 20 Behavioral Questions to Ace Your Next Data Science Interview appeared first on Analytics Vidhya.
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Analytics Vidhya
DECEMBER 1, 2024
Data science has emerged as one of the most impactful fields in technology, transforming industries and driving innovation across the globe. Python’s dominance in the data science landscape is largely attributed to its rich […] The post Top 20 Python Libraries for Data Science Professionals appeared first on Analytics Vidhya.
KDnuggets
JUNE 12, 2025
By Bala Priya C , KDnuggets Contributing Editor & Technical Content Specialist on June 12, 2025 in Data Science Image by Author | Ideogram You dont need a rigorous math or computer science degree to get into data science. Well, most people approach data science math backwards.
Advertiser: Data Robot
Today, banks realize that data science can significantly speed up these decisions with accurate and targeted predictive analytics. By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. But times are changing.
KDnuggets
JULY 22, 2025
Your AI-Powered Partner in Colab Notebooks Data Science Agent in a Colab Notebook (sequences shortened, results for illustrative purposes) Colab notebooks are now an AI-first experience designed to speed up your workflow. Colab notebooks also have a built-in Data Science Agent. Get Started: Try the Data Science Agent 4.
KDnuggets
JULY 1, 2025
By Abid Ali Awan , KDnuggets Assistant Editor on July 1, 2025 in Data Science Image by Author | Canva Awesome lists are some of the most popular repositories on GitHub, often attracting thousands of stars from the community. In this article, we will review some of the most popular and impressive lists for data science.
Advertiser: Data Robot
Today, banks realize that data science can significantly speed up these decisions with accurate and targeted predictive analytics. By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. But times are changing.
Advertiser: Data Robot
Demand for data scientists is surging. With the number of available data science roles increasing by a staggering 650% since 2012, organizations are clearly looking for professionals who have the right combination of computer science, modeling, mathematics, and business skills.
Advertiser: Data Robot
As enterprises evolve their AI from pilot programs to an integral part of their tech strategy, the scope of AI expands from core data science teams to business, software development, enterprise architecture, and IT ops teams.
Advertiser: Data Robot
How can MLOps help data science teams, business leaders, and IT professionals build a resilient and scalable foundation for their AI initiatives? What are the core elements of an MLOps infrastructure? How can MLOps tools deliver trusted, scalable, and secure infrastructure for machine learning projects?
Advertiser: Data Robot
The new DataRobot whitepaper, Data Science Fails: Building AI You Can Trust, outlines eight important lessons that organizations must understand to follow best data science practices and ensure that AI is being implemented successfully. Download the report to gain insights including: How to watch for bias in AI.
Speaker: Judah Phillips, Co-CEO and Co-Founder, Product & Growth at Squark
Automating the sophisticated, complex aspects of data science is now simple with the no-code platform Squark. Judah Phillips, the co-CEO & co-Founder of Squark answers the 5 Things You Always Wanted to Know About Automating Data Science, but Never Asked!
Speaker: Timothy Chan, PhD., Head of Data Science
🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.
Speaker: Dr. Greg Loughnane and Chris Alexiuk
Greg Loughnane and Chris Alexiuk in this exciting webinar to learn all about: How to design and implement production-ready systems with guardrails, active monitoring of key evaluation metrics beyond latency and token count, managing prompts, and understanding the process for continuous improvement Best practices for setting up the proper mix of open- (..)
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