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        1. IBM 数据科学专业认证

          IBM Data Science Professional Certificate

          开启数据科学和ML.Master数据科学的职业生?#27169;?#23398;习Python和SQL,分析和可视化数据,构建机器学习模型。

          IBM

          Coursera

          计算机

          简单(初级)

          3 个月

          • 英语, 德语
          • 1335

          课程概况

          Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming. This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Data Science or Machine Learning.

          This program consists of 9 courses providing you with latest job-ready skills and techniques covering a wide array of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud using real data science tools and real-world data sets.

          It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. We start small, re-enforce applied learning, and build up to more complex topics.

          Upon successfully completing these courses you will have done several hands-on assignments and built a portfolio of data science projects to provide you with the confidence to plunge into an exciting profession in Data Science. In addition to earning a Professional Certificate from Coursera, you will also receive a digital Badge from IBM recognizing your proficiency in Data Science.

          LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

          包含课程

          课程1
          What is Data Science?

          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. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

          课程2
          Open Source 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. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

          课程3
          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. This course has one purpose, and that is to share a methodology that can be used within data science, to ensure that the data used in problem solving is relevant and properly manipulated to address the question at hand. Accordingly, in this course, you will learn: - The major steps involved in tackling a data science problem. - The major steps involved in practicing data science, from forming a concrete business or research problem, to collecting and analyzing data, to building a model, and understanding the feedback after model deployment. - How data scientists think! LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

          课程4
          Python for Data Science

          This introduction to Python will kickstart your learning of Python for data science, as well as programming in general. This beginner-friendly Python course will take you from zero to programming in Python in a matter of hours. Module 1 - Python Basics o Your first program o Types o Expressions and Variables o String Operations Module 2 - Python Data Structures o Lists and Tuples o Sets o Dictionaries Module 3 - Python Programming Fundamentals o Conditions and Branching o Loops o Functions o Objects and Classes Module 4 - Working with Data in Python o Reading files with open o Writing files with open o Loading data with Pandas o Numpy Finally, you will create a project to test your skills. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate.

          常见问题

          退款政策是如何规定?#27169;?/p>

          如果订?#27169;?#24744;可以获得 7 天免费试听,在此期间,您可以取消课程,无需支?#24230;?#20309;罚金。在此之后,我们不会退款,但您可以随时取消订阅。请阅读我们完整的退款政策。

          我可以只注册一门课程吗?

          可以!点击您感兴趣的课程卡开始注册即可开始学习。注册并完成课程后,您可以获得可共享的证书,或者您也可以旁听该课程免费查看课程资料。如果您订阅的课程是某证书的一部分,系统会自动为您订阅完整的证书。访问您的学生面板,跟踪您?#24917;?#24230;。

          此课程是 100% 在线学习吗?是否需要现场参加课程?

          此课程完全在线学习,无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。

          How long does it take to complete the Professional Certificate?

          The certificate requires completion of 9 courses. Each course typically contains 3-6 modules with an average effort of 2 to 4 hours per module. If learning part-time (e.g. 1 module per week), it would take 6 to 12 months to complete the entire certificate. If learning full-time (e.g. 1 module per day) the certificate can be completed in 2 to 3 months.

          What background knowledge is necessary?

          This certificate is open for anyone with any job and academic background. No prior computer programming experience is necessary, but is an asset. Familiarity working with computers, high school math, communication and presentation skills. For the last few courses knowledge of Calculus and Linear Algebra is an asset but not an absolute requirement.

          Do I need to take the courses in a specific order?

          Yes, it is highly recommended to take the courses in the order they are listed, as they progressively build on concepts taught in previous courses. For example the Data Visualization, Python and Machine Learning courses require knowledge of Python.

          Will I earn university credit for completing the Professional Certificate?

          No, there is no University credits involved with taking these courses.

          What will I be able to do upon completing the Professional Certificate?

          Become job ready for a career in Data Science. Develop practical skills using hands-on labs in Cloud environments, projects and captsones.

          I already completed some of the other courses in this Professional Certificate. Will I get "credit" for them?

          If you have already completed some of the courses in this Professional Certificate, either individually or as part of another specialization, they will be marked as "Complete". So you do not have to take those courses again and will be able to finish the Professional Certificate faster. You will only need to complete the courses that you have not yet completed.

          I have already completed the "Introduction to Data Science" Specialization. Can I still enrol for this Professional Certificate?

          Yes, absolutely. Any courses that you have already completed as part of that Specialization will be marked as "Complete". So you do not have to take those courses again and will be able to finish the Professional Certificate faster.

          Which should I enroll for - "Introduction to Data Science" Specialization, or this "Data Science Professional Certificate"?

          This Professional Certificate consists of 9 courses. The "Introduction to Data Science" Specialization has 4 courses, all of which are also included in this Professional Certificate.

          If you are unsure about your ability to commit to the level of effort and time required to complete this Professional Certificate, we recommend starting with the Introduction to Data Science Specialization, which has fewer courses. And if after earning the specialization certificate you are still determined to continue building your Data Science skills, you can then enroll for this Professional Certificate and then just complete the courses that are not in the specialization.

          I have already completed the "Applied Data Science" Specialization. Can I still enroll for this Professional Certificate?

          Yes, absolutely. Any courses that you have already completed as part of that Specialization will be marked as "Complete". So you do not have to take those courses again and will be able to finish this Professional Certificate faster.

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