About this Course
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100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 9 hours to complete

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

English

Subtitles: English

Skills you will gain

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming
Learners taking this Course are
  • Data Scientists
  • Data Analysts
  • Software Engineers
  • Engineers

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 9 hours to complete

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

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
2 hours to complete

IBM AI Enterprise Workflow Introduction

3 videos (Total 12 min), 13 readings, 3 quizzes
3 videos
IBM Watson Studio - Create a project5m
Workflow Overview3m
13 readings
About this course3m
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 Quiz45m
Process Models & Design Thinking: Check for Understanding2m
Process Models, Design Thinking, and Introduction: End of Module Quiz10m
1 hour to complete

Data Collection

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

5 videos (Total 40 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 study16m
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

Instructors

Avatar

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

About 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....

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

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • 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.

  • 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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