K Labs goes along with you providing you with its Certified Trainers, Training Laboratories, Exam Simulators, the Test Center and a dedicated Tutor that helps you to prepare for the exam. 
 

Thanks to our support, the percentage of candidates who obtain the certification at the first attempt is very close to 100%.
 

fabio-oyxis2kalvg-unsplash (1).jpeg
939869167014516ec34430a26728e18e 2

Keep yourself updated on latest courses.

Subscribe!

Keep yourself updated on latest courses.

Subscribe!

logo k labs nuovo-white

€0.00 (Pre-Order)

OBJECTIVES
This course is structured into four domains: data engineering, exploratory data analysis, modeling, and machine learning implementation and operations.

PREREQUISITES
Professional Certification for a public cloud provider (Azure, Google) or equivalent knowledge
Some existing familiarity with machine learning
An AWS account is needed to perform the hands-on lab exercises

WHO SHOULD ATTEND
Individuals performing a development or data science role seeking certification in machine learning and AWS.

TOPICS
S3 data lakes
AWS Glue and Glue ETL
Kinesis data streams, firehose, and video streams
DynamoDB
Data Pipelines, AWS Batch, and Step Functions
Using scikit_learn
Data science basics
Athena and Quicksight
Elastic MapReduce (EMR)
Apache Spark and MLLib
Feature engineering (imputation, outliers, binning, transforms, encoding, and normalization)
Ground Truth
Deep Learning basics
Tuning neural networks and avoiding overfitting
Amazon SageMaker, in depth
Regularization techniques
Evaluating machine learning models (precision, recall, F1, confusion matrix, etc.)
High-level ML services: Comprehend, Translate, Polly, Transcribe, Lex, Rekognition, and more
Security best practices with machine learning on AWS
machine-learning-fast-track
logo k labs nuovo-white

K Labs S.R.L. 

Tel. +39 059 8212 29 | info@klabs.it

VAT IT02034520367

 

©2024  K LABS Srl - RESERVED RiGHTS

©2024  K LABS Srl - RESERVED RiGHTS

FOLLOW US

FOLLOW US