Bitbucket is recommended for software development teams that need strong integration with Jira and Confluence, teams looking for private repository support, and organizations that prioritize customizable workflows and detailed permission settings.
Datacamp is recommended for beginners who are new to data science, as well as professionals looking to enhance their data skills. It is also suitable for anyone seeking to learn coding specific to data analysis tasks, or for those who wish to explore new data tools and techniques. It may not be ideal for those seeking in-depth theoretical knowledge or formal credentials.
Based on our record, BitBucket should be more popular than Datacamp. It has been mentiond 78 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I am using GitHub for both personal and work projects. In the past, I used BitBucket, and at some point I considered using GitLab, too. However, the popularity of GitHub and its ecosystem made it hard to ignore. I even use GitHub to follow trends in my profession. - Source: dev.to / about 1 month ago
Facilitated Collaboration and Funding: With easier identification comes better connectivity. Contributors, partners, and funders can more readily find projects that resonate with their interests and values. Moreover, platforms such as GitHub, GitLab, and Bitbucket are increasingly interested in integrating standardized licensing solutions like License-Token, paving the way for broader adoption and collaborative... - Source: dev.to / 3 months ago
Git ensures that your code is safe. Even if your laptop crashes, your work is backed up on a remote repository (e.g., GitHub, GitLab, Bitbucket). - Source: dev.to / 8 months ago
GitHub, GitLab, Bitbucket: These platforms provide easy-to-use interfaces for Git, adding features like pull requests, issue tracking, and more. Explore GitHub, GitLab, and Bitbucket. - Source: dev.to / 9 months ago
Tools: Use platforms like Bitbucket or GitHub’s pull request feature. - Source: dev.to / 12 months ago
Datascience: https://datacamp.com/ or self-study (python not r is best). Source: about 2 years ago
I took data from datacamp and tried to practice information that I learned from different resources. I would be very grateful for some advices to help me improve my skills in the next projects. Thanks for your time! Source: over 2 years ago
What steps do I need to take to build what they need? I have no experience in ML, AI, etc. I see there are services such as datacamp.com. Source: over 2 years ago
I am trying to create educational courses on my website. I am looking at datacamp.com for inspiration. Source: over 2 years ago
If you want to learn python for data science/machine learning, datacamp.com is an excellent resource (not sure what TDSB Learn4Life is). Source: almost 3 years ago
GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.
Udemy - Online Courses - Learn Anything, On Your Schedule
GitLab - Create, review and deploy code together with GitLab open source git repo management software | GitLab
Adobe Learning Manager - Adobe Learning Manager (formerly Adobe Captivate Prime LMS) is easy to setup and helps in delivering engaging learning experiences in a personalized manner across devices.
Gitea - A painless self-hosted Git service
LMS Collaborator - LMS Collaborator is a state-of-the-art learning management system designed to meet the need for corporate training, upskilling, and evaluation with flexible integration abilities.