Module 0: Introduction

• Pre-assessment

Module 1: Introduction to Machine Learning and the ML Pipeline

• Overview of machine learning, including use cases, types of machine learning, and key concepts
  Overview of the ML pipeline
  Introduction to course projects and approach

Module 2: Introduction to Amazon SageMaker

• Introduction to Amazon SageMaker
• Demo: Amazon SageMaker and Jupyter notebooks
• Hands-on: Amazon SageMaker and Jupyter notebooks

Module 3: Problem Formulation

• Overview of problem formulation and deciding if ML is the right solution
• Converting a business problem into an ML problem
• Demo: Amazon SageMaker Ground Truth
• Hands-on: Amazon SageMaker Ground Truth
• Practice problem formulation
• Formulate problems for projects

Module 4: Preprocessing

• Overview of data collection and integration, and techniques for data preprocessing and visualization
  Practice preprocessing
  Preprocess project data
  Class discussion about projects

Module 5: Model Training

• Choosing the right algorithm
  Formatting and splitting your data for training
  Loss functions and gradient descent for improving your model
  Demo: Create a training job in Amazon SageMaker

Module 6: Model Evaluation

• How to evaluate classification models
• How to evaluate regression models
• Practice model training and evaluation
• Train and evaluate project models
• Initial project presentations

Module 7: Feature Engineering and Model Tuning

• Feature extraction, selection, creation, and transformation
• Hyperparameter tuning
• Demo: SageMaker hyperparameter optimization
• Practice feature engineering and model tuning
• Apply feature engineering and model tuning to projects
• Final project presentations

Module 8: Deployment

• How to deploy, inference, and monitor your model on Amazon SageMaker
  Deploying ML at the edge
  Demo: Creating an Amazon SageMaker endpoint
  Post-assessment
  Course wrap-up

Additional course details:

Nexus Humans The Machine Learning Pipeline on AWS training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward.

This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts.

Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.

While we feel this is the best course for the The Machine Learning Pipeline on AWS course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.

Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

FAQ for the The Machine Learning Pipeline on AWS Course

Available Delivery Options for the The Machine Learning Pipeline on AWS training.

• Live Instructor Led Classroom Online (Live Online)
• Traditional Instructor Led Classroom (TILT/ILT)
• Delivery at your offices in London or anywhere in the UK
• Private dedicated course as works for your staff.

How many CPD hours does the The Machine Learning Pipeline on AWS training provide?

The 4 day. The Machine Learning Pipeline on AWS training course give you up to 24 CPD hours/structured learning hours. If you need a letter or certificate in a particular format for your association, organisation or professional body please just ask.

Is the The Machine Learning Pipeline on AWS training appropriate for someone learning to use AWS in a professional environment?

Yes the The Machine Learning Pipeline on AWS is appropriate for someone looking to use AWS in a professional workspace or environment. But do make sure to note any prerequisites, read the course outline to ensure it is the right fit for you or your teams requirements and preferences.

What is the correct audience for the The Machine Learning Pipeline on AWS training?

This course is intended for:
Developers
Solutions Architects
Data Engineers
Anyone with little to no experience with ML and wants to learn about the ML pipeline using Amazon
SageMaker

Do you provide training for the The Machine Learning Pipeline on AWS.

Yes we provide corporate training, dedicated training and closed classes for the The Machine Learning Pipeline on AWS. This can take place anywhere in UK including, England, Scotland, Cymru (Wales) or Northern Ireland or live online allowing you to have your teams from across UK or further afield to attend a single training event saving travel and delivery expenses.

What is the duration of the The Machine Learning Pipeline on AWS program.

The The Machine Learning Pipeline on AWS training takes place over 4 day(s), with each day lasting approximately 8 hours including small and lunch breaks to ensure that the delegates get the most out of the day.

Why are Nexus Human the best provider for the The Machine Learning Pipeline on AWS?

Nexus Human are recognised as one of the best training companies as they and their trainers have won and hold many awards and titles including having previously won the Small Firms Best Trainer award, national training partner of the year for UK on multiple occasions, having trainers in the global top 30 instructor awards in 2012, 2019 and 2021. Nexus Human has also been nominated for the Tech Excellence awards multiple times. Learning Performance institute (LPI) external training provider sponsor 2024.

Is there a discount code for the The Machine Learning Pipeline on AWS training.

Yes, the discount code PENPAL5 is currently available for the The Machine Learning Pipeline on AWS training. Other discount codes may also be available but only one discount code or special offer can be used for each booking. This discount code is available for companies and individuals.