Data Science

Five Ways to Cultivate a Healthy Culture on a Data Science Team

View more in

Career Development & Advice

By Editors’ Picks

towardsdatascience.com

2 hours ago

Cover picture for the articleHello all! We’re back with a new post today setting aside learning a new hard skill to focus on some important soft skills in the data science realm. It goes without saying that a healthy working culture is important for any job, and the same holds true for data scientists and…

towardsdatascience.com

Related

towardsdatascience.com

Creating Your First Data Science Project — Data Scientist Perspective

Applying for a Data Science position is not an easy feat because of how complex the preparation is; From learning programming, understanding how to analyze data, reading statistic books, and creating the data science project as a portfolio — there are so much to do. The problem is that you…

towardsdatascience.com

7 Data Pet Projects To Learn Data Science Faster

I am a firm believer in following your heart. That said, learning data science online was a struggle because I had no idea where my heart was. I would follow a beginner course and only go so far because I felt completely disconnected from the data problem they were working on.

towardsdatascience.com

UCL Data Science Society: Python sequences

This year, as Head of Science for the UCL Data Science Society, the society is presenting a series of 20 workshops covering topics such as introduction to Python, a Data Scientists toolkit and Machine learning methods, throughout the academic year. For each of these that I present and deliver I aim to create a series of small blogposts that will outline the main points with links to the full workshop for anyone who wishes to follow along. All of these can be found at out GitHub, and will be updated throughout the year with new workshops and challenges.

Thrive Global

5 Ways Managers Can Establish Healthy Relations With Their Teams

“An employee’s motivation is a direct result of the sum of interactions with his or her manager.” – Bob Nelson. Bosses, team leaders, managers, supervisors, and so on! They always have a terrible reputation. No matter what they do, they just can’t get it right in their subordinates or team members’ eyes.

IN THIS ARTICLE

World Economic Forum

Top-down or bottom-up? How to cultivate a digital culture in your organization

The COVID-19 pandemic accelerated the shift to a digital-first world which made businesses rethink the way they operate. One key to business success in a post-Covid world is to embrace a digital culture. For digital culture to be successful, it must be driven from the ground up. The COVID-19 pandemic…

stanford.edu

How to teach data science in K-12 schools? Stanford-led team launches “Big Ideas”

Amid a growing push for schools to better prepare young people to navigate a world awash in data, a team of scholars led by Stanford Graduate School of Education Professor Jo Boaler has introduced a groundbreaking tool for educators: “Big Ideas in Data Science,” a proposed set of standards for teaching data science to students in kindergarten through tenth grade.

towardsdatascience.com

Automate the Structure of Your Data Science Projects with Cookiecutter

Stop the manual work, reuse project templates instead. Here’s a situation a lot of data scientists are familiar with. Every time you start a new project, you reuse the structure of older projects. You go through their folders and copy-paste them, you remove the unnecessary files, you rename the remaining ones with your new project’s specifics, and you go inside each configuration file and replace the old environment variables (URLs, API keys, Hosts, Ports, etc.) with the new ones.

Forbes

Five Best Practices For Scaling Data Science Across Organizations

Chief Data Scientist at Reorg, a global provider of credit intelligence, data and analytics, and Adjunct at UVA’s School of Data Science. Many new companies are hiring data scientists with the goal of leveraging their existing data to create business growth. I was hired five years ago to establish data science at Reorg. Throughout this time, I worked with many teams — business, commercial, technology, product and C-level. Through collaboration on various projects, I discovered the importance of educating non-technical stakeholders on the strengths and weaknesses of data science approaches. While data scientists are often seen as excellent problem solvers, they cannot solve business problems alone.

YOU MAY ALSO LIKE

ocmomblog.com

Important Skills You Should Polish in Your Career

Do you want to be successful in your career? You can’t do it without the right skills. This article will discuss essential skills that you should polish during your career and how they could help advance your success. People Skills. This refers to your ability to work with others and…

towardsdatascience.com

5 Data Science Podcasts To Follow in 2022

Hear the voices from within the world of data science. Data science is not something you can learn from listening to podcasts. However, what podcasts provide is something you cannot learn from other resources: real life experience. We live in a time where it is extremely easy and cheap to…

towardsdatascience.com

4 Categorical Encoding Concepts to Know for Data Scientists

The categorical data type is data divided by category or group — for example, Gender, Education, and Birth Place. Each element in the categorical data is used to group information on specific labels, different from numerical data where the numerical data information is in numbers. The problem with the unprocessed categorical data is the machine learning issue where many models cannot accept categorical data. This issue is why we need Categorical Encoding.

towardsdatascience.com

Top 3 Visualization Python Packages to Help Your Data Science Activities

Data visualization is a process to summary your data into a graphic representation to help people understand the data. Imagine your data exploration or validation without data visualization? It is hard, right?. Additionally, data visualization might reveal additional information we cannot find in the statistical summary. Data visualization also helps…

towardsdatascience.com

Data Science in Semiconductor Process Yield

Using Machine Learning to improve fab throughput and profitability. In this stage of the pandemic, demand for all kinds of semiconductor chips has exploded and semiconductor fabs are struggling to keep up. Traditional IC customers are now competing with the demands of new compute applications (such as AI and autonomous driving) to get their custom-design wafers fabricated. Unfortunately, increasing the wafer capacity of semiconductor fabs to react with new waves of demand is very expensive and challenging. Once a decision is made to increase a fab’s capacity, it can take months to purchase new tools, install them in the fab, and qualify them for production.

gitconnected.com

Basic SQL for Data Science

SQL stands for Structured Query Language. It is a query language used to work with Relational Databases, meaning that we interact with data stored in the relational databases using this very language. There are different platforms for SQL like. Sqlite. Postgresql. Mysql. etc.,. Today I am going to share some…

towardsdatascience.com

18 Data Science Project Ideas for Beginners

Pick one or all of them — whatever looks like the most fun to you. Data science projects are a great way for beginners to get to grips with some of the very basic data science skills and languages that you’ll need to pursue data science as a hobby or a career. Tutorials, lessons, and videos are all great, but projects really act as a stepping stone to getting involved with data science and getting your hands dirty.

Six ways to improve data science in the cloud

The data science market is flourishing, with an increasing number of companies across sectors placing data at the forefront of their digital transformation strategies. The rise of data analytics has seen the demand for data scientists and data engineers tripling over the past five years, rising by as much as 231%. Yet as many businesses rush to hire the talent they need to make their plans a reality, many are still on a journey in realizing the full value that their data can offer.

atlanticcitynews.net

Data Science in Finance – Beginners Guide

Data science has found inroads into every industry. Virtually every organized industry has realized the benefits of data science techniques to derive useful and game-changing information from historical and live data streams. Finance is no exception and has many applications of data science already in use. The sections below look at how data science is being used to plug gaps and overcome challenges in the fiancé sector.

hackernoon.com

6 Essential Tips to Solve Data Science Projects

Data science projects are focusing on solving social or business problems by using data. Solving data science projects can be a very challenging task for beginners in this field. You will need to have a different skills set depending on the type of data problem you want to solve. Data preparation is the process of cleaning and transforming your raw data into useful features that you can use to analyze and create predictive models. Take advantage of Cloud Platforms to train your data with a large dataset and run a lot of experiments.

The future of work is hybrid – here’s an expert’s recommendations for success

COVID-19 has changed the way we work. Even before the pandemic, the U.S. workforce increasingly relied on remote collaboration technologies like videoconferencing and Slack. The global crisis accelerated the adoption of these work tools and practices in an unprecedented way. By April 2020, about half of companies reported that more than 80% of their employees worked from home because of COVID-19. That shift was made possible by decades of research into, and then development of, technologies that support remote work, but not everyone uses these technologies with the same ease. As early as 1987, groundbreaking research identified some of the…

towardsdatascience.com

The Art of Learning Data Science

So back in January of 2020, I released a video called Strategies for learning data science in 2020 where I shared some of my tips on how you could get started in learning data science. A year has passed and I thought that it would be a great opportunity to revisit the topic by creating this article The Art of Learning Data Science where I share my best tips (along with tips of several eminent data scientists) on how to learn data science in 2021.

Related
towardsdatascience.com

Creating Your First Data Science Project — Data Scientist Perspective

Applying for a Data Science position is not an easy feat because of how complex the preparation is; From learning programming, understanding how to analyze data, reading statistic books, and creating the data science project as a portfolio — there are so much to do. The problem is that you…

towardsdatascience.com

7 Data Pet Projects To Learn Data Science Faster

I am a firm believer in following your heart. That said, learning data science online was a struggle because I had no idea where my heart was. I would follow a beginner course and only go so far because I felt completely disconnected from the data problem they were working on.

towardsdatascience.com

UCL Data Science Society: Python sequences

This year, as Head of Science for the UCL Data Science Society, the society is presenting a series of 20 workshops covering topics such as introduction to Python, a Data Scientists toolkit and Machine learning methods, throughout the academic year. For each of these that I present and deliver I aim to create a series of small blogposts that will outline the main points with links to the full workshop for anyone who wishes to follow along. All of these can be found at out GitHub, and will be updated throughout the year with new workshops and challenges.

Thrive Global

5 Ways Managers Can Establish Healthy Relations With Their Teams

“An employee’s motivation is a direct result of the sum of interactions with his or her manager.” – Bob Nelson. Bosses, team leaders, managers, supervisors, and so on! They always have a terrible reputation. No matter what they do, they just can’t get it right in their subordinates or team members’ eyes.

IN THIS ARTICLE

Source: https://www.newsbreak.com/news/2412749910677/five-ways-to-cultivate-a-healthy-culture-on-a-data-science-team

Donovan Larsen

Donovan is a columnist and associate editor at the Dark News. He has written on everything from the politics to diversity issues in the workplace.

Related Articles

Leave a Reply

Your email address will not be published. Required fields are marked *

Back to top button