What you'll learn

Master end-to-end machine learning workflows, including data preparation, model training, and deployment using AWS services.
Gain proficiency in AWS tools like SageMaker, Rekognition, and Comprehend to build, train, and deploy scalable ML solutions.
Learn hyperparameter tuning, feature engineering, and performance evaluation to optimize machine learning models for real-world applications.
Apply security, scalability, and cost optimization best practices while designing machine learning pipelines and deploying solutions on AWS.

Requirements

A basic understanding of machine learning concepts, Python programming, and familiarity with AWS services is recommended for this course.

Description

This course is designed for professionals and aspiring individuals aiming to specialize in the field of machine learning (ML) with a focus on AWS technologies. It equips learners with the knowledge and skills to design, deploy, and optimize machine learning solutions on the AWS platform.Key Highlights:Explore the fundamentals of machine learning and deep learning concepts.Learn how to build, train, and deploy ML models using AWS services such as SageMaker, Lambda, and more.Gain expertise in data engineering, feature engineering, and model optimization tailored for scalable solutions.Understand the ethical and practical considerations of AI implementation in cloud environments.Who Should Enroll?This course is ideal for:Data scientists, software engineers, and developers looking to integrate ML into their workflows.IT professionals seeking to enhance their cloud computing skills with a focus on AI.Students and tech enthusiasts aspiring to gain certification and excel in AWS ML engineering roles.Prepare to master the intersection of artificial intelligence and cloud computing while advancing your career in the fast-evolving world of machine learning! This certification opens doors to high-demand roles in AI and ML engineering. Employers worldwide value AWS-certified professionals for their proven expertise in building innovative, scalable machine learning solutions.

Overview

Section 1: Introduction
Lecture 1 Introduction
Lecture 2 lecture2 AWS ML Services and their applications
Section 2: Data Enginereing
Lecture 3 lecture 3 Data Engineering
Lecture 4 Lecture 4 Feature Engineering
Lecture 5 Lecture 5 AWS Tools for data Engineering
Section 3: Section 3 Exploratory Data Analysis
Lecture 6 Lecture 6 EDA
Lecture 7 Data Visualization tools
Lecture 8 Lecture 8 Statistical analysis and data insights
Section 4: Section 4 Machine learning models
Lecture 9 Lecture 9 Machine learning Models
All

Homepage:

https://www.udemy.com/course/aws-certified-machine-learning-engineer-associate-intended/