Most courses have bitesized projects including cancer detection, predicting economic trends, predicting customer churn, recommendation engines, building a dashboard to visualize US Economic Data, and more.
Профессиональная сертификация 'Наука о данных IBM'
Kickstart your career in data science & ML. Build data science skills, learn Python & SQL, analyze & visualize data, build machine learning models. No degree or prior experience required.
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Обзор
Duration: 12 мес
4 hours per week
Format: 100% онлайн
Learn at your own pace
Primary Language: Английский
Subtitles: Английский, Арабский, Французский
Empower yourself with a pathway to an in-demand career in Data Science
Empower yourself with a pathway to an in-demand career in Data Science
Data science is one of the hottest professions of the decade, and the demand for data scientists who can analyze data and communicate results to inform data driven decisions has never been greater.
It’s a myth that to become a data scientist you need a Ph.D. Anyone with a passion for learning can take this Professional Certificate – no prior knowledge of computer science or programming languages required – and develop the skills, tools, and portfolio to showcase your new talents in the job market as an entry level data scientist.
Учитесь у лидеров отрасли
Запишитесь на курсы, разработанные IBM
Получите востребованные у работодателей навыки и начните карьеру в data science.
Улучшайте свое резюме
Продемонстрируйте свои навыки и расширьте портфолио за счет проектов, основанных на реальных проблемах.
Получите от IBM документ, который подтверждает вашу квалификацию
Получите признанный в отрасли сертификат, чтобы улучшить свое резюме.

Ускорьте поиск работы с помощью кадровой службы Coursera
Узнайте больше от выпускников
Присоединяйтесь к сообществу Coursera для выпускников профессиональной сертификации Наука о данных IBM
Ознакомьтесь с практическими проектами, на которых вы будете учиться
Во время интервью о приеме на работу продемонстрируйте свои навыки, продемонстрировав портфолио
Building basic programs with data
Capstone project
You will learn about location data and different location data providers, such as Foursquare. You will learn how to make RESTful API calls to the Foursquare API to retrieve data about venues in different neighborhoods around the world. You will also learn how to be creative in situations where data are not readily available by scraping web data and parsing HTML code. You will utilize Python and its pandas library to manipulate data, which will help you refine your skills for exploring and analyzing data.

Описание программы
Приобретаемые навыки
- Data Science
- Python Programming
- Data Analysis
- Pandas
- Numpy
- Ipython
- Cloud Databases
- Relational Database Management System (RDBMS)
- SQL
- Predictive Modelling
- Data Visualization (DataViz)
- Model Selection
- Data Virtualization
- Matplotlib
Обзор
The program consists of 9 online courses that will provide you with the latest job-ready tools and skills, including open source tools and libraries, Python, databases, SQL, data visualization, data analysis, statistical analysis, predictive modeling, and machine learning algorithms. You’ll learn data science through hands-on practice in the IBM Cloud using real data science tools and real-world data sets.
Upon successfully completing these courses, you will have 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'll also receive a digital badge from IBM recognizing your proficiency in data science.
Профессиональная сертификация включает несколько курсов: 10
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.
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, JupyterLab, RStudio IDE, Git, GitHub, and Watson Studio. 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 Skills Network 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 Watson Studio 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, AI & Development
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 is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
Часто задаваемые вопросы
Получу ли я зачеты в университете за прохождение специализации?
Can I just enroll in a single course?
Можно ли зарегистрироваться только на один курс?
Действительно ли это полностью дистанционный курс? Нужно ли мне посещать какие-либо занятия лично?
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?
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