Master Machine Learning on AWS with Our Comprehensive Course

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The Machine Learning Pipeline on AWS Course Overview

The Machine Learning Pipeline on AWS certification validates the ability to build, train, tune, and deploy machine learning models using AWS services. It's about understanding the mechanisms of data collection, storage, processing, and analysis in order to create insightful predictions. This certification ensures knowledge of AWS machine learning algorithms and their implementation. It's used by businesses across industries to leverage machine learning capabilities to improve efficiency, predictive accuracy, and business outcomes. AWS offers a complete set of tools and services to facilitate this, including data lakes, data warehouses, and business intelligence tools. These skills are essential to stay competitive in the digital economy.


The 1-on-1 Advantage

Get 1-on-1 session with our expert trainers at a date & time of your convenience.

Flexible Dates

Start your session at a date of your choice-weekend & evening slots included, and reschedule if necessary.

4-Hour Sessions

Training never been so convenient- attend training sessions 4-hour long for easy learning.

Destination Training

Attend trainings at some of the most loved cities such as Dubai, London, Delhi(India), Goa, Singapore, New York and Sydney.

You will learn:

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
  • Introduction to Amazon SageMaker
  • Demo: Amazon SageMaker and Jupyter notebooks
  • Hands-on: Amazon SageMaker and Jupyter notebooks
  • 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
  • Overview of data collection and integration, and techniques for data preprocessing and visualization
  • Practice preprocessing
  • Preprocess project data
  • Class discussion about projects
  • 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
  • How to evaluate classification models
  • How to evaluate regression models
  • Practice model training and evaluation
  • Train and evaluate project models
  • Initial project presentations
  • 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
  • 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
Live Online Training (Duration : 32 Hours)
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.

3350 + If you accept merging of other students. Per Participant Incl. Official Course-Book & excluding VAT/GST
8 Hours
Week Days

Start Time : At any time

12 AM
12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Group Training
2150 Per Participant Incl. Official Course-Book & excluding VAT/GST
02 - 05 Oct
09:00 AM - 05:00 PM CST
(8 Hours/Day)
06 - 09 Nov
09:00 AM - 05:00 PM CST
(8 Hours/Day)
Course Prerequisites
- Basic understanding of Machine Learning
- Knowledge of AWS services and architecture
- Familiarity with programming languages, preferably Python or Java
- Experience with basic SQL and database concepts
- Background in statistics and data analysis
- Practical experience in developing, training, and validating ML models
- AWS Certified Developer or AWS Certified Solutions Architect credential preferred.

The Machine Learning Pipeline on AWS Certification Training Overview

AWS Machine Learning Pipeline Certification training provides participants a comprehensive understanding of how to build, train, and deploy machine learning models using the AWS Cloud. The coursework covers major topics including data exploration and visualization, cleaning, preprocessing, model validation, and AWS Machine learning services. Participants learn to leverage data using cloud-based, scalable machine learning algorithms and work with real-world, complex datasets for practical, hands-on experience. The course is ideal for developers, data scientists, and IT professionals.

Why Should You Learn The Machine Learning Pipeline on AWS?

The Machine Learning Pipeline on AWS course offers comprehensive understanding of deploying machine learning algorithms, handling big data, and improving prediction accuracy. It introduces students to Cloud-based machine learning platforms, enhancing their data analytics skills and broadening their career opportunities in the booming field of AI and machine learning.

Target Audience for The Machine Learning Pipeline on AWS Certification Training

- Data scientists
- AI engineers
- IT professionals looking to enhance their machine learning skills
- Professionals involved in designing and implementing ML solutions
- Students studying computer science or data analytics
- IT Managers interested in cloud-based machine learning tools.

Why Choose Koenig for The Machine Learning Pipeline on AWS Certification Training?

- Access to Certified Instructors possessing robust knowledge in Machine Learning Pipeline on AWS.
- Training modules are designed to boost career prospects in the field of Machine Learning.
- Customized Training Programs to meet individual learning needs and professional objectives.
- Offers Destination Training enabling individuals to learn in a dynamic learning environment.
- Affordable Pricing for comprehensive training on Machine Learning Pipeline on AWS.
- Recognized as a Top Training Institute known for quality and effectiveness in training.
- Offers Flexible Dates allowing individuals to choose a suitable training schedule.
- Provides Instructor-Led Online Training for comprehensive learning experience.
- Wide Range of Courses catering to different learning needs and industry demands.
- Accreditation reflects a high standard of training delivery and quality curriculum content.

The Machine Learning Pipeline on AWS Skills Measured

After completing The Machine Learning Pipeline on AWS training, individuals can acquire skills such as understanding AWS's Machine Learning algorithms, managing the Machine Learning process, and using AWS SageMaker to simplify the integration of Machine Learning into applications. They will also learn how to perform data engineering tasks on the AWS platform, ingest data using AWS Glue, visualize using Quicksight & Athena, and manage the Machine Learning process, model training, tuning, and deployment.

Top Companies Hiring The Machine Learning Pipeline on AWS Certified Professionals

Top tech companies like Amazon, Microsoft, IBM, Oracle, and Salesforce are actively hiring Machine Learning Pipeline on AWS certified professionals. These professionals are in constant demand for their expertise in managing data, building, training, and deploying machine learning models using AWS services.

Learning Objectives - What you will Learn in this The Machine Learning Pipeline on AWS Course?

The learning objectives of The Machine Learning Pipeline on AWS course are to enable learners to comprehend and apply AWS tools and practices for deploying machine learning algorithms. By the end of the course, participants should be able to use AWS services for data exploration and cleaning, model training, and deployment. They will be proficient in implementing machine learning algorithms on AWS, managing ML workflows, and optimizing models for performance. Additionally, learners will gain a deep understanding of dealing with structured and unstructured data, different machine learning concepts, and experience using SageMaker for developing and deploying machine learning applications on AWS.
Student Name Feedback
Sri Venkatesh Durgumahanthi
United States
A1. Very professional, Concept oriented and knowledgeable
United States
A1. This training was very interactive and engaging. Huge thanks to the Trainer.
United States
A1. Trainer has done a great job in explaining all the theoretical concepts.
United States
A1. Trainer is really good . He is able to cover all the important topics of ML in a short time and in effective manner
United States
A1. Amazing trainer...wonderful energy and profound knowledge about AWS services
United States
A1. very engaging
Sandeep Deveraj Nagshetty
United States
A1. Sachin was proactive in clearing the doubts and the concepts.
Aakriti Rana
United States
A1. Highly energetic trainer, with a very engaging way of teaching
United States
A1. Sachin is very knowledgeable trainer, he explained the concepts clearly and took extra step to beyond to explain complex topics. I certainly enjoyed his classes.
Dhanya Jacob
United States
A1. Great explanation
Ishita Singh
United States
A1. Sachin is an excellent trainer, really appreciate the way he teaches and explain a particular topic. He keeps the session lively and interactive. Looking forward to attend more training sessions from him.
Balu Subramoniam Vadivel Murugan
United States
A1. Conducted the training very well. Right pace while balancing to course content along with answering questions and helping with Lab. Keep it up.
Archana Devi T
United States
A1. Sachin is very passionate in delivering the session. He patiently answers each and every question. He was always high on energy which motivates us to to have 100% concentration in virtual mode
Rahul Kumar Sharma
United States
A1. I am happy to complete my AWS machine learning training. All the session were very knowledgeable.
James Issac
United States
A1. He was very patient and subject expert. he took all side slowly and gave time for labs.


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1-on-1 Public - Select your start date. Other students can be merged.
1-on-1 Private - Select your start date. You will be the only student in the class.
You will receive the letter of course attendance post training completion via learning enhancement tool after registration.
Yes, Koenig follows a BYOL(Bring Your Own Laptop) policy.
Yes you can.
You can request a refund if you do not wish to enroll in the course.
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Buy-Now. Pay-Later option is available using credit card in USA and India only.
Yes, course requiring practical include hands-on labs.
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Yes, we also offer weekend classes.
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Yes, we do offer corporate training More details
It is recommended but not mandatory. Being acquainted with the basic course material will enable you and the trainer to move at a desired pace during classes.You can access courseware for most vendors.
Yes, this is our official email address which we use if a recipient is not able to receive emails from our email address.
Yes, we do. For details go to flexi
Yes, we do.
The Fee includes:
  • Official Course-Book
  • Testing Via Qubits
Yes, Koenig Solutions is a AWS Learning Partner
Schedule for Group Training is decided by Koenig. Schedule for 1-on-1 is decided by you.
In 1 on 1 Public you can select your own schedule, other students can be merged. Choose 1-on-1 if published schedule doesn't meet your requirement. If you want a private session, opt for 1-on-1 Private.
Duration of Ultra-Fast Track is 50% of the duration of the Standard Track. Yes(course content is same).

Prices & Payments

Yes of course.
Yes, We are

Travel and Visa

Yes we do after your registration for course.

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