Профессиональная сертификация 'Наука о данных IBM'
Kickstart your Career in Data Science & ML. Master data science, learn Python & SQL, analyze & visualize data, build machine learning models.
Профессиональная сертификация: общие сведения
Приобретаемые навыки
Только онлайн-курсы
Гибкий график
Начальный уровень
Прибл. 3 месяца на выполнение
Английский
Что такое профессиональная сертификация?
Получайте нужные для работы навыки
Если вы ищите новую работу или хотите сменить род деятельности, освойте новую профессию и получите профессиональный сертификат Coursera. Учитесь в собственном темпе где и когда угодно. Зарегистрируйтесь сегодня и начните новый карьерный путь с 7-дневным бесплатным пробным периодом. Приостановить обучение или завершить подписку можно в любой момент.
Практические проекты
Примените свои навыки для выполнения практических проектов и создайте портфолио, которое продемонстрирует потенциальным работодателям вашу готовность к работе. Чтобы получить сертификат, вам нужно успешно завершить проекты.
Получите документ, который подтверждает вашу квалификацию
Завершив все курсы в программе, вы получите сертификат, которым можно делиться с коллегами по отрасли, а также доступ к профессиональным ресурсам, которые помогут начать новую карьеру. Многие профессиональные сертификации признаются работодателями-партнерами, а другие помогают подготовиться к сертификационному экзамену. Подробная информация доступна на страницах профессиональных сертификаций.

Профессиональная сертификация включает несколько курсов: 9
Что такое наука о данных?
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.
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.
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.
Python for Data Science and AI
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.
О IBM
Часто задаваемые вопросы
Какие правила возврата средств?
Можно ли зарегистрироваться только на один курс?
Да! Чтобы начать, нажмите карточку интересующего вас курса и зарегистрируйтесь. Зарегистрировавшись, вы можете пройти курс, чтобы получить сертификат, ссылкой на который можно делиться с другими людьми. Просто ознакомиться с содержанием курса можно бесплатно. При подписке на курс, входящий в сертификацию, вы автоматически подписываетесь на всю сертификацию. Ход учебы можно отслеживать в панели управления учащегося.
Действительно ли это полностью дистанционный курс? Нужно ли мне посещать какие-либо занятия лично?
Это полностью дистанционный курс, потому вам не нужно ничего посещать. Все лекции, материалы для самостоятельного изучения и задания доступны всегда и везде по Интернету и с мобильных устройств.
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 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 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.
What are my job opportunities on completion of this Data Science Professional Certificate
As a Coursera learner who completes the Data Science Professional certificate, you will have special access to join IBM’s Talent Network. Our Talent Network members receive all of the tools you need to land a dream job with IBM - sent directly to your inbox! You will get job opportunities as soon as they are posted, recommendations to apply matched directly to your skills and interests, and tips and tricks to help you stand apart from the crowd.
How can I access job opportunities with IBM after completing this Certificate?
As a Coursera learner who completes this Professional Certificate, you will have special access to join IBM’s Talent Network. Our Talent Network members receive all of the tools you need to land a dream job with IBM - sent directly to your inbox! You will get job opportunities as soon as they are posted, recommendations to apply matched directly to your skills and interests, and tips and tricks to help you stand apart from the crowd.
Остались вопросы? Посетите Центр поддержки учащихся.











