About this Course

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Flexible deadlines
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Intermediate Level
Approx. 6 hours to complete
Subtitles: English

Skills you will gain

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 6 hours to complete
Subtitles: English

Offered by

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Syllabus - What you will learn from this course


Week 1

2 hours to complete

IBM AI Enterprise Workflow Introduction

2 hours to complete
3 videos (Total 12 min), 13 readings, 3 quizzes
3 videos
IBM Watson Studio - Create a project5m
Workflow Overview3m
13 readings
About this Course5m
Target Audience2m
Required skills2m
An introduction to IBM Watson Studio and IBM Design Thinking12m
Overview of IBM Watson Studio2m
Am I Ready?1m
Am I ready to take this Specialization?3m
Readiness Quiz Review12m
Advantages and Disadvantages of Process Models2m
Data Science Process Models2m
The Design Thinking Process2m
Data Science Workflow Combined with Design Thinking13m
Process Models, Design Thinking, and Introduction: Summary/Review3m
3 practice exercises
Readiness Quiz1h
Process Models & Design Thinking: Check for Understanding2m
Process Models, Design Thinking, and Introduction: End of Module Quiz10m
1 hour to complete

Data Collection

1 hour to complete
5 videos (Total 17 min), 5 readings, 4 quizzes
5 videos
Introduction to Business Opportunities2m
Introduction to Scientific Thinking for Business2m
Introduction to Gathering Data2m
AI Workflow: Gathering data6m
5 readings
Data Collection Objectives2m
Identifying the Business Opportunity: Through the Eyes of our Working Example5m
Scientific Thinking for Business10m
Gathering Data12m
Data Collection: Summary/Review3m
4 practice exercises
Business Opportunities: Check for Understanding4m
Scientific Thinking for Business: Check for Understanding2m
Gathering Data: Check for Understanding2m
Data Collection: End of Module Quiz5m

Week 2

3 hours to complete

Data Ingestion

3 hours to complete
5 videos (Total 41 min), 15 readings, 2 quizzes
5 videos
AI Workflow: Data ingestion6m
AI Workflow: Sparse Matrices for Data Pipeline Development10m
Using Watson Studio to Complete the Case Study17m
Case Study2m
15 readings
Data Engineering3m
Limitations of Extract, Transform, Load (ETL)3m
Data Ingestion in the Modern Enterprise1m
Enterprise Data Stores for Data Ingestion3m
Why We Need a Data Ingestion Process2m
Data Ingestion and Automation3m
Sparse Matrices are Used Early in Data Ingestion Development5m
Getting started Watson Studio3m
Case Study Introduction2m
Getting Started3m
Data Sources2m
PART 1: Gathering the data10m
PART 2: Checks for quality assurance (Includes Assessment)10m
PART 3: Automating the process (Includes Assessment)10m
Data Ingestion: Summary/Review3m
2 practice exercises
Ingesting Data: Check for Understanding3m
Data Ingestion: End of Module Quiz



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About the IBM AI Enterprise Workflow Specialization

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

Frequently Asked 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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