course | Machine Learning with AWS
Advance your career with Machine Learning with AWS. Hands‑on learning in Dubai covering machine learning aws and more. Enroll today.
DIGTR-496 | Machine Learning with AWS
Course Sector : Digital Transformation and Innovation
| Duration | Date from | Date to | Course Venue | Course fees | Book a course |
|---|---|---|---|---|---|
| 5 Days | 19/10/2026 | 23/10/2026 | Dubai | $4,250 | Book now |
| 5 Days | 25/01/2027 | 29/01/2027 | Singapore | $4,950 | Book now |
| 5 Days | 26/04/2027 | 30/04/2027 | Abu Dhabi | $4,250 | Book now |
| 5 Days | 26/07/2027 | 30/07/2027 | Dubai | $4,250 | Book now |
Course Introduction
Machine learning (ML) is one of the fastest-growing areas in technology and a highly sought-after skillset in today’s job market. It is the biggest shift of the decade in Machine Learning. This training course is designed to provide participants with the concepts of the emerging world of patterns, techniques, and practices, in understanding proven solutions to common problems.
This course will discuss various artificial intelligence and machine learning services available on AWS, learn how to use these services to generate impressive results, and how to use a wide range of AWS services in your own projects.
Course objective
- Gain a comprehensive understanding of AWS and its role in Machine Learning
- Build intelligent applications using Amazon AI services like Amazon Comprehend, Amazon Rekognition, Amazon Translate and others.
- Know how to use AWS console and identify the services available for Machine Learning.
- Explore the basics of chatbots and chatbot design.
- Effectively create a Chatbot with Natural Language
Course audience
- Business and technology leaders
- Business Unit Managers
- Business Development Consultants
- General Managers / Regional Managers
- Senior and mid-level leaders
- Individual leaders of all levels in the organization
- Art Director
- Marketing Consultants
- Marketing Development Manager
Course Outline | Day 01
Introduction to Machine Learning
- What is Artificial Intelligence?
- What is Machine Learning?
- What is Deep Learning?
- Understanding Neural Networks
- Machine Learning Algorithms Explained
Course Outline | Day 02
Amazon AI Services: Computer Vision
- Introduction to Amazon Rekognition
- Introduction to AWS DeepLens
- Hands-on Rekognition: Automated Video Editing
- Deep Dive on Amazon Rekognition
Introduction to Amazon Web Services
- The basics of working on AWS using S3.
- Importing and exporting data.
- Using the AWS console and identifying the services available for Machine Learning.
- Create an S3 bucket and import text data into it.
Course Outline | Day 03
Amazon AI Services: NLP
- Introduction to Amazon Comprehend
- Introduction to Amazon Comprehend Medical
- Introduction to Amazon Translate
- Introduction to Amazon Transcribe
- Deep Dive with Amazon Transcribe
Summarize Text Documents using NLP
- Use Amazon Comprehend to detect the language in which a document is written.
- Extract information such as entities (persons or places), key phrases (noun phrases indicative of the content), and emotional sentiment from a set of documents.
- Sample project: Set up a Lambda function to process and analyze the imported text using Comprehend.
Course Outline | Day 04
Perform Topic Modeling and Theme Extraction
- Understand what business use cases to apply the machine learning algorithm (Latent Dirichlet Allocation (LDA)) that is used for topic modeling.
- Extract and analyze common themes through topic modeling with Amazon Comprehend.
- Sample project: Perform topic modeling on a set of documents and analyze the results.
Course Outline | Day 05
Creating a Chatbot with Natural Language
- Explore the basics of chatbots and chatbot design.
- Set up with the Amazon Lex service and create a sample chatbot to order flowers.
- Create a custom chatbot that will look up market prices for a given stock.
BOOST’s Professional Attendance Certificate “BPAC”
BPAC is always given to the delegates after completing the training course,and depends on their attendance of the program at a rate of no less than 80%,besides their active participation and engagement during the program sessions.
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