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Курс 1 из 6 в программе

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Промежуточный уровень

Прибл. 9 часа на выполнение

Предполагаемая нагрузка: This course requires 4 to 5 hours of study....

Английский

Субтитры: Английский

Приобретаемые навыки

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming

Курс 1 из 6 в программе

100% онлайн

Начните сейчас и учитесь по собственному графику.

Гибкие сроки

Назначьте сроки сдачи в соответствии со своим графиком.

Промежуточный уровень

Прибл. 9 часа на выполнение

Предполагаемая нагрузка: This course requires 4 to 5 hours of study....

Английский

Субтитры: Английский

Программа курса: что вы изучите

Неделя
1
2 ч. на завершение

IBM AI Enterprise Workflow Introduction

3 видео ((всего 12 мин.)), 13 материалов для самостоятельного изучения, 3 тестов
3 видео
IBM Watson Studio - Create a project5мин
Workflow Overview3мин
13 материала для самостоятельного изучения
About this course3мин
Target Audience2мин
Required skills2мин
An introduction to IBM Watson Studio and IBM Design Thinking12мин
Overview of IBM Watson Studio2мин
Am I ready?1мин
Am I ready to take this Specialization?3мин
Readiness Quiz Review12мин
Advantages and disadvantages of process models2мин
Data Science Process Models2мин
The design thinking process2мин
Data science workflow combined with design thinking13мин
Process Models, Design Thinking, and Introduction: Summary/Review3мин
3 практического упражнения
Readiness Quiz45мин
Process Models & Design Thinking: Check for Understanding2мин
Process Models, Design Thinking, and Introduction: End of Module Quiz10мин
1 ч. на завершение

Data Collection

5 видео ((всего 17 мин.)), 5 материалов для самостоятельного изучения, 4 тестов
5 видео
Introduction to Business Opportunities2мин
Introduction to Scientific Thinking for Business2мин
Introduction to Gathering Data2мин
AI Workflow: Gathering data6мин
5 материала для самостоятельного изучения
Data Collection Objectives2мин
Identifying the business opportunity: Through the eyes of our Working Example5мин
Scientific Thinking for Business10мин
Gathering Data12мин
Data Collection: Summary/Review3мин
4 практического упражнения
Business Opportunities: Check for Understanding4мин
Scientific Thinking for Business: Check for Understanding2мин
Gathering Data: Check for Understanding2мин
Data Collection: End of Module Quiz5мин
Неделя
2
3 ч. на завершение

Data Ingestion

5 видео ((всего 40 мин.)), 15 материалов для самостоятельного изучения, 2 тестов
5 видео
AI Workflow: Data ingestion6мин
AI Workflow: Sparse matrices for data pipeline development10мин
Using Watson Studio to complete the case study16мин
Case Study2мин
15 материала для самостоятельного изучения
Data Engineering3мин
Limitations of Extract, Transform, Load (ETL)3мин
Data ingestion in the modern enterprise1мин
Enterprise data stores for data ingestion3мин
Why we need a data ingestion process2мин
Data ingestion and automation3мин
Sparse matrices are used early in data ingestion development5мин
Getting started Watson Studio3мин
Case Study Introduction2мин
Getting Started3мин
Data Sources2мин
PART 1: Gathering the data10мин
PART 2: Checks for quality assurance (Includes Assessment)10мин
PART 3: Automating the process (Includes Assessment)10мин
Data Ingestion: Summary/Review3мин
2 практического упражнения
Ingesting Data: Check for Understanding3мин
Data Ingestion: End of Module Quiz

Преподаватели

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Mark J Grover

Digital Content Delivery Lead
IBM Data & AI Learning
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Ray Lopez, Ph.D.

Data Science Curriculum Leader
IBM Data & Artificial Intelligence

О 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....

Специализация IBM AI Enterprise Workflow: общие сведения

This six course specialization is designed to prepare you to take the certification examination for IBM AI Enterprise Workflow V1 Data Science Specialist. IBM AI Enterprise Workflow is a comprehensive, end-to-end process that enables data scientists to build AI solutions, starting with business priorities and working through to taking AI into production. The learning aims to elevate the skills of practicing data scientists by explicitly connecting business priorities to technical implementations, connecting machine learning to specialized AI use cases such as visual recognition and NLP, and connecting Python to IBM Cloud technologies. The videos, readings, and case studies in these courses are designed to guide you through your work as a data scientist at a hypothetical streaming media company. Throughout this specialization, the focus will be on the practice of data science in large, modern enterprises. You will be guided through the use of enterprise-class tools on the IBM Cloud, tools that you will use to create, deploy and test machine learning models. Your favorite open source tools, such a Jupyter notebooks and Python libraries will be used extensively for data preparation and building models. Models will be deployed on the IBM Cloud using IBM Watson tooling that works seamlessly with open source tools. After successfully completing this specialization, you will be ready to take the official IBM certification examination for the IBM AI Enterprise Workflow....
IBM AI Enterprise Workflow

Часто задаваемые вопросы

  • Зарегистрировавшись на сертификацию, вы получите доступ ко всем видео, тестам и заданиям по программированию (если они предусмотрены). Задания по взаимной оценке сокурсниками можно сдавать и проверять только после начала сессии. Если вы проходите курс без оплаты, некоторые задания могут быть недоступны.

  • Записавшись на курс, вы получите доступ ко всем курсам в специализации, а также возможность получить сертификат о его прохождении. После успешного прохождения курса на странице ваших достижений появится электронный сертификат. Оттуда его можно распечатать или прикрепить к профилю LinkedIn. Просто ознакомиться с содержанием курса можно бесплатно.

  • This course assumes that you are already familiar with basic data science concepts including probability and statistics, linear algebra, machine learning, and the use of Python and Jupyter. If you are unsure we do offer a Readiness Exam you can take to see if you are prepared.

  • No. Most of the exercises may be completed with open source tools running on your personal computer. However, the exercises are designed with an enterprise focus and are intended to be run in an enterprise environment that allows for easier sharing and collaboration. The exercises in the last two modules of the course are heavily focused on deployment and testing of machine learning models and use the IBM Watson tooling found on the IBM Cloud.

  • Yes. All IBM Cloud Data and AI services are based upon open source technologies.

  • The exercises in the course may be completed by anyone using the IBM Cloud "Lite" plan, which is free for use.

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