AWS Certified Machine Learning – Specialty Course in Chennai

1825 Ratings

Master machine learning, artificial intelligence, data engineering, feature engineering, deep learning, model deployment, MLOps, and cloud-based AI solutions with Edubrights' AWS Certified Machine Learning – Specialty Course in Chennai.

This advanced training is designed for students, freshers, software developers, data analysts, data scientists, machine learning engineers, AI professionals, cloud engineers, DevOps engineers, and working professionals who want to build, train, deploy, and manage intelligent machine learning applications using Amazon Web Services (AWS).

Gain hands-on experience with Amazon SageMaker, supervised and unsupervised learning, feature engineering, data preparation, model optimization, deep learning, MLOps pipelines, model monitoring, and real-world AI projects through practical industry use cases.

Key Highlights:

✅ Real-Time Machine Learning Projects & AI Industry Use Cases

✅ Live Instructor-Led Training by Experienced AWS Machine Learning Professionals

✅ Hands-On Practice with Amazon SageMaker & AWS AI Services

✅ Machine Learning Fundamentals, Data Engineering & AI Workflow

✅ Data Collection, Data Cleaning, Feature Engineering & Data Preparation Techniques

✅ Supervised Learning, Unsupervised Learning & Reinforcement Learning Concepts

✅ Model Training, Hyperparameter Tuning & Machine Learning Optimization

✅ Deep Learning using TensorFlow, PyTorch & AWS Machine Learning Services

✅ Computer Vision, Natural Language Processing (NLP) & Predictive Analytics

✅ Machine Learning Model Deployment, Monitoring & MLOps Best Practices

✅ AWS Security, IAM, Data Protection & Responsible AI Implementation

✅ Integration with Amazon SageMaker, AWS Glue, Amazon S3, AWS Lambda, Amazon EMR, AWS Step Functions & Amazon CloudWatch

✅ Resume Building, Machine Learning Portfolio Development & Mock Interview Preparation

✅ Career Guidance, Placement Assistance & AWS Certified Machine Learning – Specialty Certification Support

✅ Flexible Online, Classroom & Weekend Training Options

✅ Corporate Training for IT Companies, AI Startups, Data Science Teams, Cloud Service Providers, Software Development Companies & Enterprise Organizations

Build practical machine learning expertise, develop intelligent AI-powered applications, automate data-driven decision-making, deploy scalable machine learning models on AWS, create an impressive cloud AI portfolio, and become industry-ready for careers in Machine Learning, Artificial Intelligence, Data Science, MLOps, Cloud AI Engineering, and Intelligent Application Development.

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₹20000

₹42000

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Enroll Now View Syllabus

Case Studies and Projects

Hours of Training

20+

Placement Assurance

100%

Expert Support

Yes

Support & Access

Lifetime

Certification

Yes

Skill Level

All

Language

All

Course Objectives

Q1. Why should I learn AWS Certified Machine Learning – Specialty?

This course helps you develop practical machine learning skills using AWS cloud services. You will learn how to build, train, deploy, and optimize machine learning models for real-world business applications while preparing for the AWS certification.

Q2. What practical knowledge will I gain from this course?

You will gain hands-on experience with data engineering, feature engineering, Amazon SageMaker, deep learning, model deployment, and MLOps. The practical projects help you understand how machine learning solutions are implemented in modern cloud environments.

Q3. How does this course support career growth?

Machine learning and artificial intelligence continue to drive innovation across industries. This course strengthens your cloud AI expertise, improves problem-solving skills, and prepares you for advanced machine learning and cloud-focused roles.

Q4. What are the major learning outcomes of this training?

After completing this training, learners will be able to design, build, deploy, monitor, and optimize machine learning solutions on AWS while following industry best practices and preparing confidently for the AWS Certified Machine Learning – Specialty certification.

Popular Techniques Covered in This Course

Machine Learning Fundamentals

Data Engineering

Feature Engineering

Amazon SageMaker

Model Training

Deep Learning

MLOps

Model Deployment

AI Security

Machine Learning Optimization

Get Hands-on Knowledge about Real-Time Projects

Project 1

Customer Churn Prediction System

Develop a machine learning model using Amazon SageMaker to predict customer churn based on historical customer behavior and business data. This project helps learners understand data preprocessing, feature engineering, model training, evaluation, and predictive analytics using AWS machine learning services.

Project 2

Real-Time Product Recommendation Engine

Build an intelligent recommendation system that suggests relevant products based on customer preferences and purchasing patterns. Learners gain hands-on experience with recommendation algorithms, data pipelines, model deployment, and scalable machine learning solutions on AWS.

Project 3

Image Classification with Deep Learning

Create an image classification solution using Amazon SageMaker and deep learning frameworks to identify and categorize images automatically. This project provides practical experience in computer vision, neural networks, model optimization, and cloud-based AI deployment.

Project 4

Fraud Detection and Model Deployment Pipeline

Design an end-to-end fraud detection solution that analyzes transaction data to identify suspicious activities using machine learning models. Learners implement data engineering workflows, model training, deployment, monitoring, and MLOps practices to build a scalable and secure AI application on AWS.

Key Features

Edubrights offers AWS Certified Machine Learning – Specialty Training in virtual mode with expert trainers. Here are the key features,

40 Hours Course Duration

100% Job Oriented Training

Industry Expert Faculties

Free Demo Class Available

Completed 500+ Batches

Certification Guidance

Curriculum

Module 1: Machine Learning Fundamentals and AWS Overview

Introduction to Artificial Intelligence and Machine Learning
Types of Machine Learning
AWS Machine Learning Services
Machine Learning Lifecycle
AWS Global Infrastructure
AWS Shared Responsibility Model

Module 2: Data Collection and Data Engineering

Data Sources
Amazon S3 for Data Storage
AWS Glue
AWS Lake Formation
Data Cleaning Techniques
Data Transformation

Module 3: Feature Engineering

Data Preprocessing
Feature Selection
Feature Scaling
Data Encoding
Handling Missing Values
Feature Store Concepts

Module 4: Exploratory Data Analysis

Data Visualization
Statistical Analysis
Correlation Analysis
Data Distribution
Outlier Detection
Business Insights

Module 5: Machine Learning Algorithms

Supervised Learning
Unsupervised Learning
Classification Algorithms
Regression Algorithms
Clustering
Recommendation Systems

Module 6: Amazon SageMaker

SageMaker Studio
Model Training
Built-in Algorithms
Hyperparameter Tuning
Distributed Training
Model Deployment

Module 7: Deep Learning on AWS

Neural Networks
TensorFlow
PyTorch
Computer Vision
Natural Language Processing
Transfer Learning

Module 8: Model Evaluation and Optimization

Performance Metrics
Cross Validation
Model Explainability
Bias Detection
Model Optimization
Performance Monitoring

Module 9: MLOps and Automation

Machine Learning Pipelines
CI/CD for ML
Model Versioning
Automation Workflows
Monitoring Models
Continuous Improvement

Module 10: Security and Governance

IAM for Machine Learning
Data Security
Encryption
Compliance
Responsible AI
Governance Best Practices

Module 11: Real-Time Machine Learning Applications

Fraud Detection
Predictive Analytics
Recommendation Engines
Forecasting
Image Recognition
Text Analytics

Module 12: AWS Certified Machine Learning – Specialty Exam Preparation

Certification Overview
Exam Domains
Architecture Scenarios
Mock Tests
Best Practices
Certification Readiness

Receive Training From Our Skilled and Effective Trainers

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Up-to-Date Knowledge Trainers keep content current with the latest Adobe Illustrator releases, Generative AI features in Illustrator, vector illustration trends, and evolving professional vector design best practices.

AWS Certified Machine Learning – Specialty Certification Training (Cloud Integration & Serverless APIs)

The AWS Certified Machine Learning – Specialty Course in Chennai is designed to help learners develop advanced machine learning skills using Amazon Web Services. Through hands-on labs, real-world AI projects, data engineering workflows, model development, deployment, and MLOps practices, participants gain practical experience in building intelligent cloud-based solutions. Upon successful completion, learners are well-prepared to pursue the AWS Certified Machine Learning – Specialty certification with confidence.

Course FAQs

1. Who can enroll in the AWS Certified Machine Learning – Specialty Course?

This course is suitable for data scientists, machine learning engineers, software developers, cloud engineers, AI professionals, students, freshers with programming knowledge, and working professionals who want to build practical machine learning skills using AWS cloud services.

2. Are there any prerequisites for learning AWS Machine Learning?

Basic knowledge of programming, mathematics, statistics, and cloud computing is helpful but not mandatory. Familiarity with Python and AWS fundamentals will make it easier to understand advanced machine learning concepts covered in the course.

3. How long does it take to complete the AWS Certified Machine Learning – Specialty training?

The duration depends on the learning schedule and training format. Most learners complete the course over several weeks through instructor-led sessions, practical labs, hands-on projects, and certification preparation activities.

4. Does the course include hands-on practical training?

Yes. The course includes practical exercises using Amazon SageMaker, data engineering workflows, feature engineering, model development, deployment, monitoring, and real-world machine learning projects to build practical cloud AI experience.

5. Is this course aligned with the AWS Certified Machine Learning – Specialty exam?

Yes. The curriculum follows the official AWS certification objectives and includes exam-focused topics, architecture scenarios, practical labs, mock assessments, and certification preparation sessions.

6. What projects are included in the training?

Learners work on projects such as predictive analytics, recommendation systems, fraud detection, image classification, sentiment analysis, and machine learning model deployment using AWS services.

7. What job roles can I pursue after completing this course?

After completing the training, learners can explore opportunities such as Machine Learning Engineer, AI Engineer, Data Scientist, Cloud Machine Learning Engineer, MLOps Engineer, Data Engineer, and AWS Machine Learning Specialist.

8. Is AWS Certified Machine Learning – Specialty certification valuable?

Yes. The certification validates practical knowledge of building, deploying, and managing machine learning solutions on AWS. It demonstrates cloud AI expertise and strengthens professional credibility in machine learning and cloud computing.

9. Can beginners learn AWS Machine Learning?

Yes. Learners with basic programming knowledge can begin with machine learning fundamentals before progressing to advanced AWS services, model development, deployment, and optimization techniques through structured learning.

10. Why choose AWS Certified Machine Learning – Specialty Training in Chennai?

Chennai has a growing demand for AI, data science, and cloud computing professionals. This training equips learners with practical AWS machine learning skills aligned with current industry requirements and modern AI technologies.