About the Course

There are four functional roles in Data Science, namely, Business Analyst, Data Analyst, Machine Learning Engineer and Data Engineer. The PA track targets the Machine Learning Engineer role.

Once you understand the fundamentals of Deep Learning and Predictive Modelling, its time to learn Natural Language Processing (NLP). NLP is all about teaching the computer how to talk. You will learn the fundamentals of NLP and also how to create custom language translation models and chatbots!

The course will also cover how to train NLP models on Big Data using Spark and Google Cloud Platform.

Prerequisites

• Curiosity
• Basic arithmetic skills - Brackets, division, multiplication, addition, subtraction
• Ability to operate a computer, keyboard and mouse
• Ability to use a web browser to access and use the internet
• Ability to install software on your computer
• Data Analytics : Introduction : PA101

Hardware and Software Requirements

• Physical operational computer (not in virtualization) – Fedora 34 or greater OR PopOS/Ubuntu 20.04 or greater, OR Windows 10 or greater, OR MacOS 10 or greater
• 16 GB RAM
• Broadband internet connection > 5 MBPS
• 100 GB free hard disk space. SSD Drive recommended
• Dedicated graphic card is not required but recommended. Cloud will be used.
• Access to a credit card for Google Cloud Compute account with billing enabled and free $300 credits

Learning Objective

NLP

• Introduction
• Python Text Basics
• NLP Basics
• Part of Speech and Named Entity
• Introduction to Text Classification
• Building Sentiment Analysis Systems
• Topic Modeling
• Text Generation
• QnA Chatbots

Building Conversational Chatbots with Dialogflow

• Introduction
• Introducing Dialogflow
• Flow Of Conversation
• Setting Up A Dialogflow Account
• Authorize Dialogflow On GCP
• Configuring Agents
• Default Intents
• Smalltalk
• Custom Intents
• Entities
• Configuring Custom Intents
• Introducing Fulfillment
• Single Intent Linear Dialogs
• Multiple Intent Linear Dialogs Using Context
• Follow-up Intents
• Non-linear Dialogs

Pyspark NLP

• Batch
• Streaming

Interpreting NLP Models

Learning Outcome

• Understand the fundamentals of Natural Language Processing (NLP)
• Learn to classify text into categories using various techniques
• Learn to build Sentiment Analysis Systems
• Generate new text based on learnings form a corpus
• Create Chatbots that can understand english and perform requested actions

Fineprint

• The topics presented are tentative and we reserve the right to add or remove a topic to update or improve the bootcamp, or for a technical or time reasons.
• † taxes extra.