AI practitioners course

Introduction

Artificial Intelligence (AI) is the science behind systems that can program themselves to classify, predict, and recommend.

This course explains how AI systems understand, reason, learn and interact. Learn from industry experience on AI use cases; develop a deeper understanding of machine learning techniques and the algorithms that power those systems, and propose solutions to real world scenarios leveraging AI methodologies.

IBM SkillsBuild for Academia
Self-paced course

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Explore the topics, technology and skills required to gain practice in the successful application of Artificial Intelligence techniques to address key industry problems.

Objectives

AI Practitioners

  • Further, the digital transformation of enterprises with an understanding of industry AI adoption patterns.
  • Are conversant with AI technologies such as natural language processing, machine learning, neural networks, virtual agents, and computer vision.

Scope

  • Watson Assistant — Build an AI assistant for a variety of channels, including mobile devices, messaging platforms, and event robots.
  • Discovery — Unlock hidden value in data to find answers, monitor trends, and surface patterns.
  • Visual Recognition — Tag and classify visual content using machine learning.

Learning objectives:

  • Understand the evolution and relevance of AI in the world today
  • Explore opportunities brought about by the intersection of human expertise and machine learning.
  • Analyze existing and future implementations of AI solutions across multiple industries including automotive, education, policy, social media, government, consumer, and others
  • Gain a competitive edge using low-code cloud-based AI tools and pre-built machine learning algorithms
  • Understand AI technology building blocks, including natural language processing, machine, and deep learning, neural networks, virtual agents, autonomics, and computer vision
  • Develop a deeper understanding of machine learning techniques and the algorithms that power those systems
  • Learn in-demand agile industry practices for design thinking and AI through an end-to-end industry use case experience
  • Participate in role-playing challenge-based scenarios to propose real-world solutions to different industries using AI and design thinking.
Young man studying space technology

CIMON brings Artificial Intelligence to the International Space Station

In the immortal words sung by Elton John, “It’s lonely out in space.” But for astronauts on the International Space Station, the journey might be a little less lonely — and maybe a little more productive — thanks to Watson AI on the IBM Cloud and CIMON, the first free-flying AI assistant in space.

CIMON (short for Crew Interactive MObile CompanioN) is the result of a partnership between the German space agency DLR, Airbus, and IBM. Matthias Biniok, the IBM project lead for CIMON, was first approached for the project in 2016. “Airbus proposed this idea they had to the German space agency: they wanted to build a robot and send it into space. When DLR commissioned them to build it, Airbus approached IBM about handling the AI components.”

The result was a roughly spherical, 11-pound robot that can converse with astronauts on the ISS. Facial-recognition software lets CIMON know who it’s talking to, and a deliberately simple visual design allows CIMON to show basic facial expressions. The astronaut bot can travel around the European Columbus Research Module of the ISS independently and has proven to be a handy assistant.

How Watson Assistant translates to space

“The idea was to create an actual astronaut assistant, so the astronauts could do their work more efficiently,” says Biniok. “A secondary goal was to have kind of a companion in space that they could talk to. That was the original idea, but in the course of things, the project focused in more on getting the experiments done with greater efficiency.”

One way CIMON helps with that is by functioning as a floating brain. The predominant AI technology used by CIMON is IBM Watson Assistant, already in use by IBM clients worldwide. Watson Assistant helps customer service representatives surface relevant and accurate information quickly so questions can be answered faster.

“Imagine you’re an astronaut in space, and you’re at your station working on an experiment,” explains Biniok. “Your hands are busy, and you have a question about the project you’re working on. Normally, you would have to float over to your laptop to get the answer, then back to the experiment station. With CIMON, you can just say, ‘CIMON, what’s the next step?’ and you don’t have to interrupt your workflow.

“Another way CIMON provides assistance is in helping to document the experiments as they’re being done. Astronauts need to record and film everything that they do. With CIMON, they can just tell him, ‘CIMON, come here. Turn your camera 30 degrees to the right and record…’”

Biniok proudly notes that all of the Watson services used in CIMON come from the IBM Cloud in Frankfurt. “That tells you how powerful our cloud is. If you can make it work in space, you can make it work anywhere.”

CIMON is a registered trademark in the European Union of Deutsches Zentrum für Luft- und Raumfahrt e. V., German Aerospace Center (DLR) and stands for Crew Interactive MObile CompanioN. It is a scientific project awarded by DLR, developed by AIRBUS and IBM, and funded by the German Federal Ministry for Economic Affairs and Energy (BMWi).

What Is AI?

AI is the science behind systems that can program themselves to classify, predict, and recommend from structured and unstructured data.

For millennia, humans have pondered the idea of building intelligent machines. Ever since, AI has had highs and lows, demonstrated successes, and unfulfilled potential.

Today, AI is empowering people and changing our world. Netflix recommends movies from the long tail, Amazon recommends the popular brand from a list, cars learn when to pass the vehicle in front, and robots distinguish trash from dishes to be washed.

In this course, we will explain how AI systems understand, reason, learn and interact; learn from industry experience on AI use cases; develop a deeper understanding of machine learning techniques and the algorithms that power those systems, and propose solutions to real-world scenarios leveraging AI methodologies and techniques.

Journey

  • Expand knowledge and understanding of the topic through lectures, examples, videos, and quizzes.

    Every lecture approx. 90 min.

    Lecture 1 – AI landscape

    • Impact of AI in the world today
    • History and evolution of AI
    • AI explained
    • AI technologies
    • Summary and resources

    Lecture 2 – AI industry adoption approaches

    • AI – impact on the industry
    • Autonomous vehicles
    • Smart robotics
    • Future workforce and AI
    • Summary and resources

    Lecture 3 – Natural language understanding

    • NLP overview
    • NLP explained
    • Virtual agents overview
    • Virtual agents for the enterprise

    Lecture 4 – Computer vision

    • Computer vision overview
    • AI vision through Deep Learning
    • Computer vision for the enterprise
    • Experiments
    • Summary and resources

    Lecture 5 – Machine learning and Deep learning

    • Machine learning explained
    • Decision tree classifier
    • Deep learning explained
    • Deep learning ecosystem
    • Experiments
    • Summary and resources

    Lecture 6 – Future Trends for AI

    • Artificial Intelligence trends
    • Limits of the machine and the human
    • AI predictions for the next 5 years
    • Summary and resources
  • Implement concepts learned through simulations, hands-on labs, and games.
    Every lab approx. 120 min.

    Lab 1 – Setting up your cloud account

    • Obtain an IBM Cloud account
    • Apply promotion code

    Lab 2 – Gain insights from Airbnb reviews

    • Crawl, convert, enrich, and normalize data
    • Explore proprietary and public content
    • Apply concepts, relations, and sentiment

    Lab 3 – Creating an AI virtual assistant

    • Create a dialog skill
    • Create a virtual assistant
    • Load virtual assistant with various dialog skills
    • Integrate your assistant

    Lab 4 – Training AI to host customers

    • Plan a dialog
    • Define custom intents
    • Add dialog nodes to handle intents
    • Add entities for responses
    • Set and reference context variables

    Lab 5 – Building your own translator with AI

    • Construct a Node-RED flow
    • Create a Telegram bot
    • Create a translator dialog using Watson
    • Integrate Node-RED with Telegram

    Lab 6 – Analyze, classify, and detect objects

    • Use the general pre-trained classifier to identify objects in an image
    • Build a custom classifier to better suit your specific images
    • Detect objects within an image

    Lab 7 – Classifying images using NODE-RED

    • Provision a Node-RED boilerplate
    • Import the Node-RED flow
    • Install zip node from Manage Palette menu
    • Connect your node-RED app with Visual Recognition service

    Lab 8 – Fraud prediction using AutoAI

    • Ingest data and initiate Auto AI process
    • Build different models and evaluate
    • Generate predictions using deployed model
  • Understand the real-world impact of topics covered with a deep-dive into industry case studies.
    Every use case approx. 16 hrs. group work

    Design Thinking for AI

    • Clearbridge hotels use case
    • Align on your intent
    • Determine your data
    • Understanding a loyalty profile
    • Reasoning for a tailored check-in

    Challenges

    Consumer products

    Analyze Amazon product reviews

    How can an e-commerce site help shoppers decide between numerous options? Use AI technology to sift through reviews and quickly reveal product insights.

    Aerospace

    Track the International Space Station

    With about 3,000 satellites in space, how can you find the position of just one? Build a satellite tracker that returns position information from satellites orbiting the earth.

    Finance

    Visualize article sentiment

    How can a financial advisor stay abreast of trends in Bitcoin? Use AI to automatically add Bitcoin articles to a collection, query the articles and visualize the sentiment.

    Media and entertainment

    Analyze Twitter sentiment

    How can a company determine the current attitude towards their brand and products? Use sentiment analysis on social media postings to derive insights.

    Insurance

    Classify vehicle damage images

    How can an insurance company quickly assess vehicle damage and generate a cost estimate for repair? Use AI technologies within a mobile app to identify and classify the damage.

    Customer service

    Create a next-generation call center

    How can a call center efficiently improve the customer experience? Use AI to handle some of your calls instead of using call center agents.

    Energy and Utilities

    Use intelligent search on smart documents

    How can utility workers in the field quickly access information needed to make repairs? Use Smart Document Understanding (SDU) to only search for the most relevant information found in a typical manual.

Tools

This course uses the following tools:

  • Angular
  • Cloud Foundry
  • Cloud Functions
  • Cloud Object Storage
  • Cloudant
  • Core Machine Learning
  • IBM Cloud
  • IBM Cloud Private
  • IBM Voice Gateway
  • Jupyter Notebook
  • LocationIQ
  • Matplotlib
  • Node.js
  • Node-RED
  • Postman
  • Python
  • Telegram
  • Tensorflow
  • Twilio
  • Visual Recognition
  • Watson Assistant
  • Watson Discovery
  • Watson Language Translator
  • Watson Natural Language Understanding
  • Watson Speech to Text
  • Watson Studio
  • Watson Text to Speech
  • Watson Tone Analyzer

Prerequisites

Instructor Workshop

Facilitator has taken the course and successfully passed the exam.

  • Avid speaker with good presentation skills
  • Pedagogical group management skills
  • Encourage critical thinking and domain exploration
  • Experience handling data sets and IP copyrights

Classroom Format

Individuals with an active interest in applying for entry-level jobs to work in AI related fields.

  • Basic IT Literacy skills*

*Basic IT Literacy – Refers to skills required to operate at the user level a graphical operating system environment
such as Microsoft Windows® or Linux Ubuntu®, performing basic operating commands such as launching an application, copying and pasting information, using menus, windows and peripheral devices such as mouse and keyboard. Additionally, users should be familiar with internet browsers, search engines, page navigation, and forms.

Digital credential

Practitioner Badge

Badge - IBM Artificial Intelligence Practitioner Certificate

IBM Artificial Intelligence Practitioner Badge

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About this certificate

Through validated Artificial Intelligence (AI) instructor-led training, this badge earner has demonstrated the ability to have acquired the skills and understanding of AI concepts and technologies.

The badge earner has demonstrated proficiency and understanding of Artificial Intelligence technical topics and design thinking.

The earner has gained the ability to apply the concepts and technology of Artificial Intelligence with the applicable open source tools that are relevant to real world Artificial Intelligence scenarios, suitable for educational purposes.

Skills

AI, AI operations, Collaboration, Communication, Computer vision, AI industry expertise, Neural networks, Virtual agents, Computer vision, AI operations, Data sources, Machine learning, Natural language processing, Deep learning, Watson discovery, IBM Cloud, Node-RED, IBM Watson, Natural language understanding, Visual recognition, Design Thinking, Use cases, Communication, Collaboration, Teamwork, Problem solving, Empathy, Personas, Experience design, Ideation, User experience, User research, User-centered design, User-centric approach, and Storyboarding.

Criteria

  • Must attend a training session at a higher education institution implementing the IBM Skills Academy program
  • Must have completed the instructor led AI Practitioners training.
  • Must have earned the Enterprise Design Thinking Practitioner Badge.
  • Must pass the AI practitioners exam and satisfactorily complete the group exercise.

Instructor Badge

Badge - IBM Artificial Intelligence Practitioner - Instructor Certificate

IBM Artificial Intelligence practitioner course Instructor

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About this certificate

Through an IBM instructor-led workshop, this badge earner has acquired skills on Artificial Intelligence (AI) concepts, technology, and use cases.

The badge earner has demonstrated proficiency on the following topics: Artificial Intelligence foundations, Machine learning, AI language and vision, Understand Design Thinking for AI, and AI industry use cases.

The earner has demonstrated the capacity to deliver the Artificial Intelligence course as an instructor applying pedagogical skills to drive the group work using challenged based scenarios.

Skills

AI, Industry expertise, Neural networks, Virtual agents, Computer vision, AI operations, Data sources, Machine learning, Natural language processing, Deep learning, Watson discovery, IBM Cloud, Node-RED, IBM Watson, Natural Language Understanding, Visual Recognition, Design Thinking, Use cases, Trainer, Lecturer, Advisor, Communication, Collaboration, Teamwork, Problem solving, Empathy, Personas, Experience design, Ideation, UX, User experience, User research,
User-centered design, User-centric approach, and Storyboarding.

Criteria

  • Must be an instructor of a Higher Education Institution which has or is implementing the IBM Skills Academy Program.
  • Must have completed the IBM Artificial Intelligence Workshop Practitioners – Instructors Workshop.
  • Must have earned the Enterprise Design Thinking Practitioner Badge.
  • Must fulfill the requirements of IBM Skills Academy teaching validation process.