Applied Data Science 專項課程
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.
You will complete hands-on labs and projects to apply and demonstrate your newly acquired skills and knowledge. For example the Python course includes a project to create a random album generator. The specialization Capstone involves a Battle of Neighborhoods using geospatial data and building a machine learning model.
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？
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 Introduction to Applied Data Science specialization by IBM.
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 Captsone course.
Will I earn university credit for completing the Specialization?
You will be able to learn practical Python skills, and apply them to interesting Data Visualization and Data Analysis problems.