Live online course

Machine Learning on AWS, Practitioner's Guide

In this practical course, you will learn how to use Amazon Web Services (AWS) for your daily Data Science and Machine Learning activities. We will cover everything starting with quick experimentations on an integrated IDE to fine-tuning and deploying a state-of-the-art NLP model using AWS. As the name suggests, the course will be hands-on and focus on providing practical knowledge through demos and hands-on exercises in each section.

Duration: 6 live sessions start coming soon
Price: €500 Full price (€350 Early bird)
* Get reimbursed by your employer

Data Scientists, Machine Learning Engineers

By enrolling, you will:

Accelerate your machine learning projects with AWS
Improve your productivity by using Amazon SageMaker for experiment tracking and fine-tuning your experimentation environment.
Achieve better data-driven insights with exploratory data analysis on SageMaker.
Save time and increase efficiency by automating the creation and update of Docker images through CICD.
Ensure smooth deployment of your models with the ability to perform batch inference and create synchronous/asynchronous endpoints.

6 live session

Immediate expert input

Real-world skills

Course syllabus

Session 1

ML stack on AWS: Overview

TBA

Intro to AWS

Intro to managed AI Services

Overview of Amazon SageMaker

Experiment tracking

Fine-tuning your experimentation environment

Session 2

Working with Data on AWS

TBA

Storing data in S3

Querying data with Athena

Exploratory Data Analysis on SageMaker

Feature engineering with Processing Jobs

Session 3

Training and fine-tuning ML models

TBA

Built-in algorithms

Built-in estimators for Deep Learning Frameworks e.g. Tensorflow, PyTorch

Bring your own container (BYOC) for training and processing

Session 4

Evaluating and registering models

TBA

Evaluating an ML model

Registering and versioning your models

Session 5

Deploying models

TBA

Performing batch inference

Creating a synchronous endpoint

Creating an asynchronous endpoint

Session 6

Basics of MLOps

TBA

ML orchestrator pipelines

CICD

Managing Docker imaging

Automating creation and update of docker images through CICD

BEIBITBAKTYGALIYEV

Senior Data Scientist

Meet the top expert

Beibit Baktygaliyev, an expert in data science, machine learning, and deep learning, leverages his skills to transform complex concepts into actionable business insights. His career journey includes tenure at globally-renowned organizations, Amazon Web Services (AWS), and Chevron, enhancing his technical and business acumen.

With over seven years in data science and more than fifteen years of professional programming experience, Beibit has a rich, diverse background. This, along with his roles at AWS and Chevron, enables him to articulate intricate ideas in an approachable manner. As a senior data scientist, Beibit has successfully employed machine learning in the cloud to improve large enterprises. He is also a recognized winner in international programming competitions, including the ACM ICPC.