在数据科学领域工作. Gain foundational data science skills to prepare for a career or further advanced learning in data science.
You will utilize tools like Jupyter, GitHub, R Studio, and Watson Studio to complete hands-on labs and projects throughout the Specialization. Using new skills and knowledge gained through the program, you’ll also work with real world data sets and query them using SQL from Jupyter notebooks.
Svetlana LevitanSenior Developer Advocate with IBM Center for Open Data and AI Technologies
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
Can I just enroll in a single course?
Can I take the course for free?
此课程是 100% 在线学习吗？是否需要现场参加课程？
What is data science?
Data science is the process of collecting, storing, and analyzing data. Data scientists use data to tell compelling stories to inform business decisions. Learn more about what data science is and what data scientists do in the IBM Course, "What is Data Science?"
What are some examples of careers in data science?
An understanding of data science and the ability to make data driven decisions is useful in any career, but some careers specifically require a data science background. Some examples of careers in data science include:
- Business Intelligence Analyst
- Data Analyst
- Data Architect
- Data Engineer
- Data Scientist
- Machine Learning Engineer
- Marketing Analyst
- Operations Analyst
- Quantitative Analyst
How long does it take to complete this Specialization?
The Specialization consists of 4 courses. Suggested time to complete each course is 3-4 weeks. If you follow recommended timelines, it would take 3 to 4 months to complete the entire Specialization.
What background knowledge is necessary?
This Specialization is intended for learners wanting to build foundational skills in data science. No prior background in data science or programming is required.
Do I need to take the courses in a specific order?
In order to get the most out of this Specialization, it is recommended to take the courses in the order they are listed.
Will I earn university credit for completing the Specialization?
No, there is no university credit associated with completing this Specialization.
In this Specialization, learners will develop foundational data science skills to prepare them for a career or further learning that involves more advanced topics in data science.