Course information

Practical Data Science with Amazon SageMaker Training​ Course Outline

Module 1: Introduction to Machine Learning

  • Types of ML
  • Job Roles in ML
  • Steps in the ML Pipeline

Module 2: Introduction to Data Prep and SageMaker

  • Training and Test Dataset Defined
  • Introduction to SageMaker
  • SageMaker Console
  • Launching a Jupyter Notebook

Module 3: Problem formulation and Dataset Preparation

  • Business Challenge: Customer Churn
  • Review Customer Churn Dataset

Module 4: Data Analysis and Visualisation

  • Loading and Visualising Your Dataset
  • Cleaning the Data

Module 5: Training and Evaluating a Model

  • Types of Algorithms
  • XGBoost and SageMaker
  • Training the Data
  • Hyper Parameter Tuning with SageMaker
  • Evaluating Model Performance

Module 6: Automatically Tune a Model

  • Automatic Hyper Parameter Tuning with SageMaker

Module 7: Deployment / Production Readiness

  • Deploying a Model to an Endpoint
  • A/B Deployment for Testing
  • Auto Scaling
  • Configure and Test Auto Scaling
  • Check Hyper Parameter Tuning Job
  • AWS Auto Scaling

Module 8: Relative Cost of Errors

  • Cost of Various Error Types
  • Binary Classification Cutoff

Module 9: Amazon SageMaker Architecture and Features

  • Accessing Amazon SageMaker Notebooks in a VPC
  • Amazon SageMaker Batch Transforms
  • Amazon SageMaker Ground Truth
  • Amazon SageMaker Neo

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Who should attend this Practical Data Science with Amazon SageMaker Training Course?

The Practical Data Science with Amazon SageMaker Course is designed for data professionals and analysts who want to harness the power of Amazon SageMaker for effective and practical data science projects. The following professionals can greatly benefit from attending this course:

  • Data Scientists
  • Data Analysts
  • Machine Learning Engineers
  • Cloud Solutions Architects
  • Business Analysts
  • Data Engineers
  • IT Professionals

Prerequisites of the Practical Data Science with Amazon SageMaker Training Course

There are no formal prerequisites for this Practical Data Science with Amazon SageMaker Course. However, familiarity with Python programming language and Machine Learning can be beneficial for the delegates.

Practical Data Science with Amazon SageMaker Training Course Overview

Amazon SageMaker is a powerful cloud-based machine learning platform that simplifies the process of building, training, and deploying machine learning models at scale. With the growing demand for data-driven decision-making, organisations need tools that streamline workflows and enhance productivity. Amazon SageMaker meets this need by providing an integrated environment for data scientists and developers to harness the power of machine learning without extensive infrastructure management.

This Practical Data Science with Amazon SageMaker Training is particularly beneficial for data scientists, machine learning engineers, data analysts, and business intelligence professionals seeking to deepen their understanding of data science methodologies and Amazon SageMaker. Additionally, IT professionals and project managers involved in data-driven projects can also gain valuable insights from this training.

This 1-day Practical Data Science with Amazon SageMaker Training by The Knowledge Academy equips professionals with the practical skills needed to leverage Amazon SageMaker effectively. Delegates will learn to create and deploy machine learning models, streamline their data science workflows, and implement best practices for model optimisation and monitoring. The hands-on approach ensures delegates can apply their learning immediately to real-world scenarios.

Course Objectives

  • To understand the fundamentals of machine learning and data science
  • To navigate the Amazon SageMaker interface effectively
  • To build, train, and deploy machine learning models
  • To implement data pre-processing techniques
  • To evaluate and optimise models for better performance
  • To explore various machine learning algorithms available in SageMaker

Upon completion of the Practical Data Science with Amazon SageMaker Training, delegates will possess the skills to implement data science projects using Amazon SageMaker, enabling them to drive business insights and innovation through effective machine learning solutions. This practical knowledge can significantly enhance their contributions to data-driven initiatives within their organisations.

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What’s included in this Practical Data Science with Amazon SageMaker Training Course?

  • World-Class Training Sessions from Experienced Instructors
  • Practical Data Science with Amazon SageMaker Certificate
  • Digital Delegate Pack

Why choose us

Our Mississauga venue

Includes..

Free Wi-Fi

To make sure you’re always connected we offer completely free and easy to access wi-fi.

Air conditioned

To keep you comfortable during your course we offer a fully air conditioned environment.

Full IT support

IT support is on hand to sort out any unforseen issues that may arise.

Video equipment

This location has full video conferencing equipment.

Mississauga is the sixth largest city in Canada. It is in the south of the province of Ontario in the region of peel. The city is estimated to have a population of around 715,000 people. The rapid growth of this city is attributed to its proximity to Toronto. It was originally built as suburb of Toronto. Education in Canada is mostly free and publicly funded. It is overseen by the federal, provincial and local governments, with the education within provincial jurisdiction and the curriculum overseen by the province. Education is compulsory in most provinces up to the age of 16. Mississauga is served by the Peel District School Board, which operates the secular English speaking public schools. There is also a school board that runs the local catholic schools and a board that runs the French speaking schools in the area, one for the secular French schools and one for the catholic French schools. There are a number of schools in the area that offer specialised programs. These include the French immersion schools such as Clarkson Secondary School and Streetsville Secondary School. There are three schools in the areas that off a Regional Arts Program and two that offer a specialist sci-tech program for students who are gifted in these areas. There is also two schools that offer support for those studying for the international baccalaureate plus numerous other programs. Canada’s higher has a very good reputation. However there is no formal ranking system and students will often choose colleges and universities bases on geographic convenience and the reputation of a particular course. Mississauga is home to one of the three campuses run by the University of Toronto. This university is ranked as the 34th best university in the world and is the second highest ranked Canadian university in the rankings. The campus was established in 1967 and is the universities second largest division. It is home to 12,000 students. They have 15 academic departments and pupils can choose from 148 programs to participate in from 89 areas of study. Students can study both undergraduate and graduate programs on this campus. This campus also has an excellent research environment that has helped the staff and researchers become internationally recognised for their work. The university includes Institutes for Management and Innovation, and Communication, Culture, Information and Technology.

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Address

Robert Speck 2
2 Robert Speck Parkway
Suite 750
Mississauga
Ontario
L4Z 1H8

T: +1 6474932992

Ways to take this course

Experience live, interactive learning from home with The Knowledge Academy's Online Instructor-led Practical Data Science With Amazon SageMaker Training | AWS Training in Mississauga. Engage directly with expert instructors, mirroring the classroom schedule for a comprehensive learning journey. Enjoy the convenience of virtual learning without compromising on the quality of interaction.

Unlock your potential with The Knowledge Academy's Practical Data Science With Amazon SageMaker Training | AWS Training in Mississauga, accessible anytime, anywhere on any device. Enjoy 90 days of online course access, extendable upon request, and benefit from the support of our expert trainers. Elevate your skills at your own pace with our Online Self-paced sessions.

Streamline large-scale training requirements with The Knowledge Academy's In-house/Onsite at your business premises. Experience expert-led classroom learning from the comfort of your workplace and engage professional development.

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Our offers a unique chance for your team to bond and engage in discussions, enriching the learning experience beyond traditional classroom settings

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Practical Data Science With Amazon SageMaker Training | AWS Training in Mississauga FAQs

Machine Learning (ML) is a data analysis process that automates the creation of analytical models. Artificial Intelligence is based on the premise that systems can learn from data, recognise patterns, and make judgments with little or no human input.
Delegates should have a foundational understanding of data science concepts, experience with programming in Python, and familiarity with AWS services to benefit fully from the Practical Data Science with Amazon SageMaker course.
The Practical Data Science with Amazon SageMaker training course is ideal for data scientists, machine learning engineers, software developers, and IT professionals seeking to enhance their skills in building and deploying machine learning models effectively.
Machine learning types include supervised learning, which uses labelled data to train models; unsupervised learning, which identifies patterns in unlabelled data; and reinforcement learning, which optimises actions based on feedback from the environment.
Amazon SageMaker simplifies the machine learning process by providing tools for building, training, and deploying models at scale, enhancing productivity, reducing time to market, and enabling seamless integration with other AWS services.
Easily identifies trends and patterns, no human intervention needed (automation), continuous improvement, handling multi-dimensional and multi-variety data, wide applications, etc., are the advantages of Machine Learning (ML).
During the Practical Data Science with Amazon SageMaker Training course, you will learn various essential topics such as XGBoost and SageMaker, review customer churn dataset, auto-scaling, job roles in ML, A/B deployment for testing, check hyperparameter tuning job, and many more.
Yes, The Knowledge Academy offers 24/7 support for Practical Data Science with Amazon SageMaker Training via phone & email before attending, during, and after the course. Our customer support team is available to assist and promptly resolve any issues you may encounter.
In this course, delegates will have intensive training with our experienced instructors, a digital delegate pack consisting of important notes related to this course, and a certificate after course completion.
This course takes 1-day to complete during which delegates participate in intensive learning sessions that cover various course topics.
You should receive the confirmation details for the Practical Data Science with Amazon SageMaker Course within 24-48 hours after registration. If you haven't received it by then, please check your spam folder or contact our support team for assistance.
Essential skills for attending the Practical Data Science with Amazon SageMaker Certification include proficiency in Python programming, a grasp of data analysis techniques, familiarity with machine learning concepts, and basic knowledge of AWS services.
Industries such as finance, healthcare, retail, and technology, along with job roles like data scientists, machine learning engineers, and business analysts, can significantly benefit from the Practical Data Science with Amazon SageMaker certification.
Yes, the Practical Data Science with Amazon SageMaker Certification Course is suitable for individuals at various career stages, from beginners seeking foundational knowledge to experienced professionals aiming to enhance their machine learning skills and deploy models effectively.
While prior experience is not mandatory, having a basic understanding of data science concepts and proficiency in Python programming will greatly enhance the learning experience for those taking the Practical Data Science with Amazon SageMaker Training Course.
The Knowledge Academy provides flexible self-paced training for this course. Self-paced training is beneficial for individuals who have an independent learning style and wish to study at their own pace and convenience.
Yes, we provide corporate training for this course, tailored to fit your organisation’s requirements.
If you are unable to access your Practical Data Science With Amazon SageMaker Training, contact the support team at The Knowledge Academy via their customer service email or phone number provided on their website for prompt assistance and resolution of your issue.
Yes, the Practical Data Science with Amazon SageMaker training course includes hands-on activities and practical components, allowing delegates to apply their learning through real-world scenarios and gain experience in building and deploying machine learning models.
The Knowledge Academy in Mississauga stands out as a prestigious training provider known for its extensive course offerings, expert instructors, adaptable learning formats, and industry recognition. It's a dependable option for those seeking this course.
The training fees for Practical Data Science with Amazon SageMaker Trainingin Mississauga starts from CAD3395
The Knowledge Academy is the Leading global training provider for Practical Data Science with Amazon SageMaker Training.
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