Applied Data Science 专项课程
Get hands-on skills for a career in data science. Learn Python, analyze and visualize data. Apply your skills to data science and machine learning.
Complete hands-on labs and projects in the IBM Cloud by applying your newly acquired skills and knowledge throughout the Specialization. Projects include creating a random album generator, building a machine learning model, and analyzing geospatial data.
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. The recommended 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?
No prior experience in data science or programming is required. However it is recommended that you have some foundational knowledge about data science, which can be developed by taking the the IBM Introduction to Data Science Specialization.
Do I need to take the courses in a specific order?
It is strongly recommended that you take the Python for Data Science course first. Then you can take either the Visualization or the Data Science course - whichever you prefer – and end with the Capstone course.
Will I earn university credit for completing the Specialization?
No, there is no university credit associated with completing this Specialization.
You will be able to exercise practical Python skills, and apply them to interesting data visualization and data analysis problems.