Brief Introduction
You will have an opportunity to work through a data science project end to end, from analyzing a dataset to visualizing and communicating your data analysis. Through working on the class project, you will be exposed to and understand the skills that are needed to become a data scientist yourself.Course Summary
Learn the basics of data science, including data analysis, visualization, and manipulation using Python and its libraries. Gain hands-on experience with real-world datasets and complete a project to showcase your skills.Key Learning Points
- Gain proficiency in Python for data science
- Learn data analysis and manipulation techniques
- Develop visualization skills and communicate findings effectively
Related Topics for further study
Learning Outcomes
- Proficiency in Python programming for data analysis
- Ability to manipulate and analyze real-world datasets
- Effective communication of data findings through visualization
Prerequisites or good to have knowledge before taking this course
- Basic understanding of programming concepts
- Familiarity with Python is helpful but not required
Course Difficulty Level
IntermediateCourse Format
- Self-paced
- Online
- Project-based
Similar Courses
- Data Analysis with Python
- Applied Data Science with Python
- Python for Data Science
Related Education Paths
Notable People in This Field
- Chief Scientist, RStudio
- Founder, Fast Forward Labs
Related Books
Description
What does a data scientist do? In this course, we will survey the main topics in data science so you can understand the skills that are needed to become a data scientist!Requirements
- The ideal students for this class are prepared individuals who have: Strong interest in data science Background in intro level statistics Python programming experience Or understanding of programming concepts such as variables, functions, loops, and basic python data structures like lists and dictionaries If you need to brush up on your programming, we highly recommend Introduction to Computer Science: Building a Search Engine . If you need a refresher on statistics, enroll in Intro to Descriptive Statistics and Intro to Inferential Statisitics . All three are on Udacity! See the Technology Requirements for using Udacity.
Knowledge
- Instructor videosLearn by doing exercisesTaught by industry professionals
Outline
- lesson 1 Introduction to Data Science Pi-Chaun (Data Scientist @ Google): What is Data Science? Gabor (Data Scientist @ Twitter): What is Data Science? Problems solved by data science. lesson 2 Data Wrangling What is Data Wrangling? Acquiring data. Common data formats. lesson 3 Data Analysis Statistical rigor. Kurt (Data Scientist @ Twitter) - Why is Stats Useful? Introduction to normal distribution. lesson 4 Data Visualization Effective information visualization. An analysis of Napoleon's invasion of Russia! Don (Principal Data Scientist @ AT&T): Communicating Findings. lesson 5 MapReduce Introduction to Big Data and MapReduce. Learn the basics of MapReduce. Mapper.
Summary of User Reviews
Discover the world of data science with Udacity's Intro to Data Science course. Students have given this course high praise for its comprehensive curriculum and hands-on projects. Many users appreciated the focus on real-world applications of data science.Key Aspect Users Liked About This Course
Real-world applications of data sciencePros from User Reviews
- Comprehensive curriculum
- Hands-on projects
- Clear and engaging instruction
- Great preparation for a data science career
- Excellent support from instructors and peers
Cons from User Reviews
- Some sections may be too basic for experienced data scientists
- Limited interaction with instructors
- Course materials could be more interactive
- Some technical issues with the online platform
- Not enough emphasis on statistical concepts
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