IBM 数据科学 專業證書
Kickstart your career in data science & ML. Master data science, learn Python & SQL, analyze & visualize data, build machine learning models.
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Learn what data science is, the various activities of a data scientist’s job, and methodology to think and work like a data scientist
Develop hands-on skills using the tools, languages, and libraries used by professional data scientists
Import and clean data sets, analyze and visualize data, and build and evaluate machine learning models and pipelines using Python
Apply various data science skills, techniques, and tools to complete a project and publish a report
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應用的學習項目
This Professional Certificate has a strong emphasis on applied learning. Except for the first course, all other courses include a series of hands-on labs in the IBM Cloud that will give you practical skills with applicability to real jobs, including:
Tools: Jupyter / JupyterLab, GitHub, R Studio, and Watson Studio
Libraries: Pandas, NumPy, Matplotlib, Seaborn, Folium, ipython-sql, Scikit-learn, ScipPy, etc.
Projects: random album generator, predict housing prices, best classifier model, battle of neighborhoods
無需相關領域的預備知識無需相關經驗。
無需相關領域的預備知識無需相關經驗。
此專業證書包含 9 門課程
什么是数据科学?
The art of uncovering the insights and trends in data has been around since ancient times. The ancient Egyptians used census data to increase efficiency in tax collection and they accurately predicted the flooding of the Nile river every year. Since then, people working in data science have carved out a unique and distinct field for the work they do. This field is data science. In this course, we will meet some data science practitioners and we will get an overview of what data science is today.
Tools for Data Science
What are some of the most popular data science tools, how do you use them, and what are their features? In this course, you'll learn about Jupyter Notebooks, RStudio IDE, Apache Zeppelin and Data Science Experience. You will learn about what each tool is used for, what programming languages they can execute, their features and limitations. With the tools hosted in the cloud on Cognitive Class Labs, you will be able to test each tool and follow instructions to run simple code in Python, R or Scala. To end the course, you will create a final project with a Jupyter Notebook on IBM Data Science Experience and demonstrate your proficiency preparing a notebook, writing Markdown, and sharing your work with your peers.
Data Science Methodology
Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand.
Python for Data Science and AI
Kickstart your learning of Python for data science, as well as programming in general, with this beginner-friendly introduction to Python. Python is one of the world’s most popular programming languages, and there has never been greater demand for professionals with the ability to apply Python fundamentals to drive business solutions across industries.
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IBM
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.
常見問題
完成专项课程后我会获得大学学分吗?
Can I just enroll in a single course?
我可以只注册一门课程吗?
此课程是 100% 在线学习吗?是否需要现场参加课程?
What is data science?
What are some examples of careers in data science?
How long does it take to complete the Professional Certificate?
What background knowledge do I need for this program?
Do I need to take the courses in a specific order?
Will I earn university credit for completing the Professional Certificate?
What will I be able to do upon completing the Professional Certificate?
I already completed some of the other courses in this Professional Certificate. Will I get "credit" for them?
I have already completed the Introduction to Data Science Specialization. Can I still enroll in this Professional Certificate?
Which program should I enroll in - the Introduction to Data Science Specialization, or this Professional Certificate?
I have already completed the Applied Data Science Specialization. Can I still enroll in this Professional Certificate?
How can I access job opportunities with IBM and other organizations after completing this Professional Certificate?
還有其他問題嗎?請訪問 學生幫助中心。