Implementing AI using IBM Watson Chatbots

Learn how to develop Conversational AI Chatbots using IBM Watson and how to integrate it with FB Messenger.

Duration

2 Days

Level

Beginner Level

Design and Tailor this course

As per your team needs

Edit Content

This two day course focuses on practical aspects of Conversational Artificial Intelligence. The objective is to understand the need of Chatbots, suitable business problems/use cases to apply Chatbot related solutions, when to avoid Chatbot related solutions, key Chatbot solutions available for buying/building, understanding AI and Conversational AI, Build Chatbots using IBM Watson assistant. The participants will gain a basic understanding about Chatbots, key options available to build chatbots, set up a Chatbot on IBM Cloud and integrate Chatbot with FB Messenger.

Edit Content

Anyone who is keen in

Understanding if Chatbot is the right solution for a Business problem
Understanding the broader perspective of implementing Chatbots
Understanding unbiased comparisons of key Chatbot solutions
Building a Chatbot on IBM Cloud platform
Integrating it with a Social network

Edit Content

Chatbots Overview

What are Chatbots?
Why are Chatbots necessary?
Where Chatbots fit in the AI Ecosystem?
How are Natural Language Processing and Chatbots related?
How are Chatbots different from Robotics Process Automation?
Chatbot Use Cases
Limitations of Chatbots

Various Chatbot Options

Google Cloud Dialog Flow
Amazon Lex
Azure Bot Service
Watson Assistant Chatbot IBM
Rasa etc.

Conversation API

IBM Watson Assistant offerings
Why IBM Watson Assistant?
Signup to IBM Cloud
Guide through IBM Cloud
Guide through IBM Cloud-part2

IBM Watson Assistant

Intents and Entities

What are Intents?
Create and test Intents
Import Intents
Intents Quiz
What are entities?
Annotations, Import Entities and System Entities
Entities Quiz

Working with Dialog

What is Dialog?
Building Dialog
Understanding Dialog and Chatbot Ethics
Context Variables
Slots
Digressions

Deploy Chatbot

Adding Integration channels

Pytorch Transformers

Introduction to Transformers
Input Embeddings
Positional Encoding
MultiHead Attention
Concat and Linear
Residual Learning
Layer Normalization
Feed Forward
Masked MultiHead Attention
MultiHead Attention in Decoder
Cross Entropy Loss
KL Divergence Loss

Building Chatbots with Transformers

Dataset Preprocessing
Data Masking
Embeddings
MultiHead Attention Implementation
Feed Forward Implementation
Encoder Layer
Decoder Layer
Transformer
Loss with Label Smoothing
Defining the Model
Training Function
Evaluation Function

Edit Content

No Prerequisites

FIND YOUR COURSE

Topics

Brands

Implementing AI using IBM Watson Chatbots

Duration

Level

Design and Tailor this course

Quick Links

our Offerings

Get in touch

Sign up for DataCouch Communications

Connect

we'd love to have your feedback on your experience so far