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AWS online training and certification in Coimbatore | AWS online course in Coimbatore

AWS Certified Machine Learning - Specialty Training and certification in Coimbatore Nux Software Solutions.

Best Training Institute in coimbatore for Amazon Web Services certified Machine learning Training and Certification.

Nux software solutions training institute provides the best cloud computing training class in all over Coimbatore. The AWS is an assured cloud services platform that offers compute power, content delivery, database storage, and other functionality to assist businesses to grow. The AWS cloud training is designed to assist the businesses to adopt an in-depth understanding of AWS architectural principles and services. It will make you able to learn how cloud computing is specifying the rules of IT architecture.

Nux software solutions is one of the best AWS training in Coimbatore, our institute is the leading AWS cloud training institute in Coimbatore and Tamilnadu. It has veteran employers equipped with technical skills and know how to design applications and systems on AWS. They assist the aspirants in building their technical skills as per the way to earn AWS training certification only through the way of recommended courses, labs, and exams.

Moreover, we have designed a lab having the well-equipped infrastructure and 24/7 accessible facility that is ideal even for professionals, corporate, individuals, live project training, industrial training as well.

We have placed above 500 registered companies and 10000+ students and professionals, all are working in the reputed positions.

AWS Certified Machine Learning - Specialty Syllabus 2021

Chapter 1

Course Introduction, About the Training Architect, About the Exam

Chapter 2

Machine Learning Fundamentals, Artificial Intelligence, What Is Machine Learning?, What Is Deep Learning?

Chapter 3

Section Introduction, Machine Learning Lifecycle, Supervised, Unsupervised, and Reinforcement, Optimization, Regularization, Hyperparameters, Validation

Chapter 4

Section Introduction, Feature Selection and Engineering, Principal Component Analysis (PCA), Missing and Unbalanced Data, Label and One Hot Encoding, Splitting and Randomization RecordIO Format

Chapter 5

Machine Learning Algorithms, Section Introduction, Logistical Regression, Linear Regression, Support Vector Machines, Decision Trees, Random Forests, K-Means, K-Nearest Neighbour Latent Dirichlet Allocation (LDA) Algorithm

Chapter 6

Deep Learning Algorithms, Section Introduction, Neural Networks, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN)

Chapter 7

Model Performance and Optimization, Section Introduction, Confusion Matrix, Sensitivity and Specificity, Accuracy and Precision, ROC/AUC, Gini Impurity, F1 Score

Chapter 8

Machine Learning Tools and Frameworks, Section Introduction, Introduction to Jupyter Notebooks, ML and DL Frameworks, TensorFlow, PyTorch, MXNet, Scikit-learn, HANDS-ON LAB Introduction to Jupyter Notebooks (AWS SageMaker), HANDS-ON LAB TensorFlow/Keras Basic Image Classifier (AWS SageMaker), HANDS-ON LAB MXNet Basic Classification (AWS SageMaker) HANDS-ON LAB Scikit-Learn Random Forest Classifier (AWS SageMaker)

Chapter 9

AWS Services, Section Introduction, S3, Glue, Athena, QuickSight, Kinesis, Streams, Firehose, Video, and Analytics, EMR with Spark, EC2 for ML, Amazon ML, HANDS-ON LAB Using Kinesis Data Firehose and Kinesis Data Analytics

Chapter 10

AWS Application Services AI/ML, Section Introduction, Amazon Rekognition (Images) Part 1, Amazon Rekognition (Images) Part 2 - the API, Amazon Rekognition (Video), Amazon Polly, Amazon Transcribe, Amazon Translate, Amazon Comprehend, Amazon Lex, Amazon Service Chaining with AWS Step Functions, HANDS-ON LAB Trigger an AWS Lambda Function from an S3 Event, HANDS-ON LAB Using AWS Step Functions to Manage a Long-Running Process, HANDS-ON LAB Perform Parallel Execution in AWS Step Functions

Chapter 11

Introduction, Section Introduction, What is Amazon SageMaker?, The Three Stages, Control (Console/SDK/Notebooks), SageMaker Notebooks

Chapter 12

Build, Data Preprocessing, Ground Truth, Preprocessing Image Data (Pinehead NotPinehead), Algorithms

Chapter 13

Train, SageMaker Algorithms - Architecture 1, SageMaker Algorithms - Architecture 2, SageMaker Algorithms - Architecture 3, Training an Image Classifier - Part 1 (Pinehead NotPinehead), Training an Image Classifier - Part 2 (Pinehead NotPinehead), Hyperparameter Tuning

Chapter 14

Deploy, inference Pipelines, Real-Time and Batch Inference, Deploy an Image Classifier (Pinehead, NotPinehead), Accessing Inference from Apps, Create a custom API for inference - Part 1 (Pinehead NotPinehead), Create a custom API for inference - Part 2 (Pinehead NotPinehead)

Chapter 15

Security, Securing SageMaker Notebooks, SageMaker and the VPC

Chapter 16

Other AWS Services, Section Introduction, DeepLens - Part 1, DeepLens - Part 2, DeepRacer - Part 1, DeepRacer - Part 2

Chapter 17

The Exam, How to Answer Questions, How to Prepare, PRACTICE EXAM AWS Certified Machine Learning-Specialty (MLS-C01) Final Practice Exam

Chapter 18

Thank You