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.
  • 6 live sessions start September 26, 2023
  • 25 learners per course
  • per seat.
    Use your L&D budget to cover the cost!
  • language: English
Senior Data Scientist
Designed for Data Scientists, Machine Learning Engineers
Gain new skills:
  • 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.
About live online course by Beibit Baktygaliyev
Session 1

ML stack on AWS: Overview

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

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

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

Evaluating an ML model
Registering and versioning your models
Session 5

Deploying models

Performing batch inference
Creating a synchronous endpoint
Creating an asynchronous endpoint
Session 6

Basics of MLOps

ML orchestrator pipelines
Managing Docker imaging
Automating creation and update of docker images through CICD

Meet the top expert leading your course

Senior Data Scientist

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.

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