Course Summary
This course provides an introduction to the tools and concepts of data science, including version control, markdown, git, GitHub, R, and RStudio.Key Learning Points
- Learn essential tools and concepts of data science
- Gain hands-on experience with version control, markdown, git, GitHub, R, and RStudio
- Explore best practices and workflows of data science
Job Positions & Salaries of people who have taken this course might have
- Data Scientist
- USA: $113,309
- India: ₹1,066,613
- Spain: €32,000
- Data Analyst
- USA: $67,317
- India: ₹589,457
- Spain: €23,000
- Business Analyst
- USA: $69,163
- India: ₹611,125
- Spain: €24,000
Related Topics for further study
Learning Outcomes
- Understand the tools and concepts of data science
- Gain practical experience with version control, markdown, git, GitHub, R, and RStudio
- Develop best practices and workflows for data science
Prerequisites or good to have knowledge before taking this course
- Basic computer skills
- Familiarity with programming concepts
Course Difficulty Level
BeginnerCourse Format
- Online self-paced
- Video lectures
- Hands-on projects
Similar Courses
- Applied Data Science with Python
- Data Science Essentials
Related Education Paths
Notable People in This Field
- Hadley Wickham
- Hilary Mason
Related Books
Description
In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.
Knowledge
- Set up R, R-Studio, Github and other useful tools
- Understand the data, problems, and tools that data analysts use
- Explain essential study design concepts
- Create a Github repository
Outline
- Data Science Fundamentals
- Why Automated Videos?
- What is Data Science?
- What is Data?
- Getting Help
- The Data Science Process
- Welcome
- A Note of Explanation
- What is Data Science?
- What is Data?
- Getting Help Quiz
- Data Science Process
- Module One Summative Quiz
- R and RStudio
- Installing R
- Installing R Studio
- RStudio Tour
- R Packages
- Projects in R
- Installing R
- Installing R Studio
- RStudio Tour
- R Packages
- Projects in R
- Module Two Summative Quiz
- Version Control and GitHub
- Version Control
- Github and Git
- Linking Github and R Studio
- Projects under Version Control
- Version Control
- GitHub and Git
- Linking Git/GitHub and RStudio
- Projects under Version Control
- Module Three Summative Quiz
- R Markdown, Scientific Thinking, and Big Data
- R Markdown
- Types of Data Science Questions
- Experimental Design
- Big Data
- R Markdown
- Types of Data Science Questions
- Experimental Design
- Big Data
- Module Four Summative Quiz
Summary of User Reviews
Data Scientists' Tools is a highly recommended course for individuals looking to gain a better understanding of data science tools and techniques. The course has received an overall positive response from users.Key Aspect Users Liked About This Course
The course provides a solid foundation for understanding the tools and techniques used in data science.Pros from User Reviews
- Course is well-structured and easy to follow
- Instructors provide clear explanations and examples
- Hands-on assignments and quizzes help reinforce concepts
- Course covers a wide range of topics relevant to data science
- Great introductory course for those new to data science
Cons from User Reviews
- Some users felt the course was too basic and lacked advanced topics
- Course may not be suitable for those with prior experience in data science
- Some users experienced technical issues with the platform
- Course may require additional resources for deeper learning
- Some users felt the course did not cover enough programming languages
Jeff Leek, PhD
4.6 Raiting
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