June 07 2021

AWS Machine Learning Certification Exam | Complete Guide

AWS Machine Learning Certification Exam | Complete Guide
MP4 | Video: h264, 1280x720 | Audio: AAC, 44100 Hz
Language: English | Size: 9.08 GB | Duration: 16h 52m

Update 01/02/2020: Section #13 on Machine Learning Implementation and Operations is released.


What you'll learn

Data Eeering

Data types, Python Libraries (pandas, Numpy, scikit Learn, MatplotLib, Seaborn), data distributions, series, Feature Eeering (imputation, binning, encoding, and normalization)

AWS Services and Algorithms

SageMaker, S3 Storage services, AWS Glue

AWS Kinesis Services (Kinesis firehose, Kinesis video streams, Kinesis data streams, Kinesis analytics)

Redshift, Redshift Spectrum, DynamoDB, Athena, Quicksight, Elastic Map Reduce (EMR)

Rekognition, Lex, Polly, Comprehend, Translate, transcribe, BlazingText Word2Vec, DeepAR, Factorization Machines, Gradient Boosted Trees (XGBoost)

Image Classification (ResNet), IP Insights, K-Means Clustering, K-Nearest Neighbor (k-NN)

Latent Dirichlet Allocation (LDA), Linear Learner (Classification), Linear Learner (Regression)

Neural Topic Modelling (NTM), Object2Vec, Object Detection, Principal Component Analysis (PCA), Random Cut Forest, Semantic Sntation, and Seqence2Sequence

Machine and Deep Learning Basics

Requirements

Basic AI/ML/AWS knowledge

Description

Machine and Deep Learning are the hottest tech fields to master right now! Machine/Deep Learning techniques are widely adopted in many fields such as banking, healthcare, transportation and technology. has recently introduced the AWS machine Learning Certification Speciality exam and its quite challeg! AWS Certified Machine Learning Specialty is targeted at data scientists and developers who design, train and deploy AI/ML models to solve real-world challeg problems.

The bad news: this exam is a very challeg AWS exam since it tests the candidate's knowledge on multiple aspects such as (1) Data Eeering and Feature Eeering, (2) AI/ML Models selection, (3) Appropriate AWS services solution to solve business problem, (4) AI/ML models building, training, and deployment, (5) Model optimization and Hyperparameters tuning. You need to answer these questions in order to pass the exam:

o How to select proper ML technique to solve a given business problem

o Which AWS service could work best for a given problem

o How to design, implement and scale secure ML solutions

o How to choose the most cost-effective solution

The good news: With over 500+ slides and over 50 practice questions, this course is by far the most comprehensive course on the market that provides students with the foundational knowledge to pass the AWS Machine Learning Certification exam like a pro! This course covers the most important concepts without any fillers or irrelevant information.

Who this course is for:

Developers and data scientists wanting to get certified in AWS Machine Learning



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