À propos de ce cours
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Dates limites flexibles

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Niveau intermédiaire

Approx. 8 heures pour terminer

Recommandé : This course requires 4 to 5 hours of study....

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Sous-titres : Anglais

Compétences que vous acquerrez

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming

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. 8 heures pour terminer

Recommandé : This course requires 4 to 5 hours of study....

Anglais

Sous-titres : Anglais

Programme du cours : ce que vous apprendrez dans ce cours

Semaine
1
2 heures pour terminer

IBM AI Enterprise Workflow Introduction

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 course3 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 Quiz45 min
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

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

5 vidéos (Total 40 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 study16 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

Enseignants

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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

À propos de 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....

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

  • Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.

  • Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.

  • 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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