À propos de ce cours

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Niveau intermédiaire
Approx. 6 heures pour terminer
Sous-titres : Anglais

Compétences que vous acquerrez

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
Approx. 6 heures pour terminer
Sous-titres : Anglais

Offert par

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Programme du cours : ce que vous apprendrez dans ce cours


Semaine 1

2 heures pour terminer

IBM AI Enterprise Workflow Introduction

2 heures pour terminer
3 vidéos (Total 12 min), 13 lectures, 3 quiz
3 vidéos
IBM Watson Studio - Create a project5 min
Workflow Overview3 min
13 lectures
About this course5 min
Target Audience2 min
Required skills2 min
An introduction to IBM Watson Studio and IBM Design Thinking12 min
Overview of IBM Watson Studio2 min
Am I ready?1 min
Am I ready to take this Specialization?3 min
Readiness Quiz Review12 min
Advantages and Disadvantages of Process Models2 min
Data Science Process Models2 min
The Design Thinking Process2 min
Data Science Workflow Combined with Design Thinking13 min
Process Models, Design Thinking, and Introduction: Summary/Review3 min
3 exercices pour s'entraîner
Readiness Quiz1 h
Process Models & Design Thinking: Check for Understanding2 min
Process Models, Design Thinking, and Introduction: End of Module Quiz10 min
1 heure pour terminer

Data Collection

1 heure pour terminer
5 vidéos (Total 17 min), 5 lectures, 4 quiz
5 vidéos
Introduction to Business Opportunities2 min
Introduction to Scientific Thinking for Business2 min
Introduction to Gathering Data2 min
AI Workflow: Gathering data6 min
5 lectures
Data Collection Objectives2 min
Identifying the Business Opportunity: Through the Eyes of our Working Example5 min
Scientific Thinking for Business10 min
Gathering Data12 min
Data Collection: Summary/Review3 min
4 exercices pour s'entraîner
Business Opportunities: Check for Understanding4 min
Scientific Thinking for Business: Check for Understanding2 min
Gathering Data: Check for Understanding2 min
Data Collection: End of Module Quiz5 min

Semaine 2

3 heures pour terminer

Data Ingestion

3 heures pour terminer
5 vidéos (Total 41 min), 15 lectures, 2 quiz
5 vidéos
AI Workflow: Data ingestion6 min
AI Workflow: Sparse matrices for data pipeline development10 min
Using Watson Studio to complete the case study17 min
Case Study2 min
15 lectures
Data Engineering3 min
Limitations of Extract, Transform, Load (ETL)3 min
Data ingestion in the modern enterprise1 min
Enterprise data stores for data ingestion3 min
Why we need a data ingestion process2 min
Data ingestion and automation3 min
Sparse matrices are used early in data ingestion development5 min
Getting started Watson Studio3 min
Case Study Introduction2 min
Getting Started3 min
Data Sources2 min
PART 1: Gathering the data10 min
PART 2: Checks for quality assurance (Includes Assessment)10 min
PART 3: Automating the process (Includes Assessment)10 min
Data Ingestion: Summary/Review3 min
2 exercices pour s'entraîner
Ingesting Data: Check for Understanding3 min
Data Ingestion: End of Module Quiz



Voir tous les avis

À propos du Spécialisation IBM AI Enterprise Workflow

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

Foire Aux Questions

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

  • 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. The certification exam is administered by Pearson VUE and must be taken at one of their testing facilities. You may visit their site at https://home.pearsonvue.com/ for more information.

  • Please visit the Pearson VUE web site at https://home.pearsonvue.com/ for the latest information on taking the AI Enterprise Workflow certification test.

  • It is highly recommended that you have at least a basic working knowledge of design thinking and Watson Studio prior to taking this course. Please visit the IBM Skills Gateway at http://ibm.com/training/badges and "Find a Badge" related to "design thinking" or "Watson Studio". From there you will be directed to courses covering these topics.

  • 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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