IBM Skills Academy/Artificial Intelligence
About the IBM Skills Academy Program
Acquire skills in the exciting field of Artificial Intelligence, where computers and humans interact. Build a chatbot virtual assistant using natural language processing, teach a machine to classify images, rank written reactions, and more!
The IBM Skills Academy Program is IBM’s premier training and digital badging worldwide program with curriculum aligned to high-demand jobs in the new digital-age technology job market. The program explores the topics, technology and skills required to gain practice in the successful application of Artificial Intelligence techniques to address key industry problems. The program uses several open source technologies including the premier IBM Watson platform.
There are no prerequisites for this course. For further information, please contact Kristine Bunyea at Kristine.Bunyea@sunywcc.edu or 914-606-7904.
Dates, Times & Course Information
Days: Tuesdays and Thursdays Fall 2021
Dates: September 14-November 18
Times: 9:30 am – 12:30 pm
Location: Remote with live instructor
Course Information: CE-COMP 2233WP
Course Contact Hours: 60 hours instructor-led + 20 hours self-paced
To register, please call 914-606-6830, and press 1. Thank you.
Upon completion of this course, the participant will:
- Understand the evolution and relevance of AI in the world today.
- Explore opportunities brought by the intersection between 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 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 end-to-end industry use case experience
- Engage in role-playing challenge-based scenarios to propose real-world solutions to different industries using AI and Design Thinking
Lab 1: Introduction to Artificial Intelligence and Node-RED
We will create IBM Cloud accounts and Node-RED services for students in this class. Our labs will operate on the IBM Cloud, and we will use the services embedded in this platform to explore some of the capabilities of Artificial Intelligence. Students will also work with Node-RED, an open-source development tool for visual programming which provides a web browser-based flow editor.
Lab 2: Gaining Insights from AirBnB Reviews
We will use IBM Watson Discovery to analyze unstructured data according to queries such as keyword and sentiment. We will use Natural Language Understanding (NLU) to filter AirBnB reviews according to negative sentiment.
Lab 3: Creating an AI Virtual Assistant
Lab 4: Training AI to Host Restaurant Customers
A chatbox can handle simple inquiries such as “Can I see your gluten-free menu options?” and “What are your store hours?”
We will use IBM Watson Assistant service to create a chat box on IBM Cloud (deployable to a social media or messaging channel). The virtual assistant we create will have dialog skills that interact using natural language to provide customers these answers. Our bot will combine machine learning, natural language understanding, and integrated dialog tools to correctly dialog whether the user asks “What are your store hours?” or “What time do you close today?” We will discuss intents, entities, and dialog.
A second lab will be specific to creating a chat box for a fictitious restaurant. The assistant we create will respond to “I want to know more about your restaurant” as well as “Can I see the menu?” and “Do you have a dessert menu?” Our virtual assistant will be able to cancel an order and can dialog referring to the user by name.
Lab 5: Building your own Translator with AI
We will use Node-RED, Telegram and the IBM Language Translator service to create a multi-language chatbot translator. The created chatbot will work for voice or text and will allow us to quickly translate phrases from English to Spanish, for example, right on our own phones. Other tools employed include IBM Speech and Language Services and Speech to Text, Text to Speech IBM Services.
Lab 6: Analyze, Classify and Detect Objects
Lab 7: Classifying Images using Node-RED
With Watson Visual Recognition Service, we can determine whether the equipment in an image meets normal conditions and we can train the service to identify particular defects and damage.
In our lab, we will provide the Watson Visual Recognition Service a set of images for two categories (cats and dogs) by defining a classifier to analyze the images. A pre-trained General Classifier will identify images and provide a confidence indicator as to certainty of match. We will then build a custom classifier trained to suit our specific images. Last, we will use IBM Watson Visual Recognition Custom Object Detection to identify items and their locations in an image based on a set of images with labeled training data that we provide, for example, we could train the object detection model to detect vehicle damage.
In a second lab, we will use Visual Recognition to classify images using Node-RED.
Lab 8: Fraud Prediction using AutoAI
We will look at building predictive models in the area of fraud prediction using IBM Auto AI and compare this to creating a new Juptyer notebook to do the same. We will discuss the reduction of time in building and deploying models that IBM Auto AI offers.
Participants will earn the IBM Skills Academy/Artificial Intelligence digital badge upon successful completion of the course readings, labs and final exam.
Who Will Benefit
You will benefit most from the IBM Data Artificial Intelligence digital badge if you are a:
- Research Team Member
- Chat Support Specialist
- Machine Learning Engineer
- Business Analyst
- Data Analyst
- Data Scientist
- Project Manager
- Cyber Security Specialist
- Software Developer