AWS Machine Learning Training

About AWS Machine Learning Certification Training Course

AWS Machine Learning Certification Training Course makes you understand the introduction to machine learning, machine learning pipeline, data engineering, exploratory data analysis, and modeling. AWS Machine Learning training course helps you in understanding MI implementation and operations. AWS Machine Learning Certification Training Course is a placement oriented training after which you can work in big corporate houses.

After the completion of the AWS Machine Learning training course, you will get certification like AWS Machine Learning Certificate. The average salary in AWS Machine Learning is $ 137,797.

AWS Machine Learning Online Training

AWS Training Syllabus

Module 1: Linux Fundamentals (Duration-2hrs)

• Overview of all basic commands
• Vim editor modes
• Filesystem hierarchy – Basic topics
• File and directories creation
• Grep
• Filter commands (head,tail,more,less)
• Creating users and groups
• Important files related
• Modifying,deleting users and group
• Linux permissions
• Basic permissions overview
• Software management
• Yellowdog update modifier(yum)
• Yum commands
• Different runlevels
• Services and daemons

AWS Solution Architect Certification Training

Module 2: Why Cloud ? (Duration-1hr)

• Why Cloud and What is Cloud Computing?
• Identify the features and benefits of cloud computing
• Different types of Cloud Computing deployment model
• Public Cloud, Private Cloud, Hybrid Cloud
• Virtualization – An essential in cloud
• Virtualization in Cloud model
• Different types of virtualization
• Hypervisor – Benefits
• Different types of services and its difference in Cloud computing
• IaaS, PaaS, SaaS
• Importance of scaling in cloud computing
• Different types of scaling and its applications
• Issues we overcome using cloud and applications
• Cost model that we use in cloud computing

Module 3: AWS – An overview (Duration-1hr)

• Describe the features of AWS
• The features of AWS marketplace
• Describe the features of Amazon Compute Services
• Describe the features of Amazon Storage Services
• Describe the features of Amazon Network Services
• Describe the features of Amazon Database services
• Describe about various services in AWS
• Global Infrastruture – Regions and Availability Zones
• Create a free tier account in AWS and onboarding
• Introduction AWS management console

Module 4: Understand Identity Access Management of AWS (Duration-2hrs)

• Protect your AWS by different authentication system
• Password policies set for users
• AWS User Account and Groups in detail
• Creating custom policies in AWS
• Introduction about Roles and its use
• Creating Roles and associating policies
• Creating programmatic access and management console access for users
• Associating policies to the user and groups

Module 5: EC2 Instance (Duration-4hrs)

• Describe AMI and AWS Marketplace templates
• Launch a basic EC2 instance
• Different types of Instances Reserved, On-demand, Spot, Dedicated
• Security groups and tags for EC2 instance
• Public key – Private key introduction and protecting EC2 with keys
• Attaching and detaching EBS volumes
• Launch an ec2 instance from an AMI
• Create custom AMI and working with different region
• Make use of amazon EBS volume and create snapshots
• Manage the configuration of your application
• Deploying a new instance from the created AMI

Module 6: Auto-scaling  (Duration-2hrs)

• Get Started with Auto Scaling Using the Console
• Creating Launch configurations and make use of it for autoscaling groups
• Maintain a Fixed Number of Running EC2 Instances
• Dynamic Scaling
• The lifecycle of autoscaling
• Policies of autoscaling

Module 7: Load Balancing (Duration-2hrs)

• Introduction to Loadbalancer (ELB)
• Different types of Loadbalancer in AWS
• Application Load balancer
• Network Load balancer
• Classic Load balancer
• Migrating classic load balancer to new load balancer
• Components and types of load balancing

Module 8: EBS (Elastic Block Storage) (Duration-2hrs)

• Create EBS volumes
• Delete EBS Volumes
• Attach and detach EBS volumes with EC2 instance
• Creating and deleting snapshots

Module 9: Object Storage in Cloud (Duration-3hr)

• Understanding S3 durability and redundancy
• Introduction about S3 Buckets
• How S3 Uploading works and how to Download
• How to S3 Permissions
• How to implement S3 Object Versioning S3 Lifecycle Policies
• Storage Gateway
• Import Export
• S3 Transfer Acceleration
• Glacier storage

Module 10: Cloud Front (Duration-1hr)

• Describing cloud front
• Creating a cloud front distribution
• Hosting a website of cloud front distribution
• Implementing global restrictions
• Configuring origins and behaviors

Module 11: Route53 (Duration-2hrs)

• Describe Hosted zones and Domain name understanding
• How to create hosted zones
• Hosting a website with custom domain name
• Understanding routing policies

Module 12: AWS Security Management (Duration-1hr)

• Describing Security Practices for Cloud Deployment
• AWS Shared Responsibilities and Securities
• Importance of Cloud Trail
• Describing Trust advisor

Module 13: Amazon Virtual Private Cloud (VPC) (Duration-5hrs)

•  Introduction to Amazon Virtual Private Cloud (VPC).
• VPC Advantages and understanding IP addressing CIDR
• Default and Non-default VPC
• Different Components in VPC
• Describe, create, and manage Amazon Virtual Private Cloud
• Amazon VPC, Private Subnet, and Public Subnet
• AWS Networking, Security Groups, and Network ACLs
• Configuration and management of VPN connectivity
• Subnet and Subnet Mask

Module 14: Relational Database Service (RDS)  (Duration-1hr)

• Introduction to RDS
• Different database services of AWS: Amazon RDS, Dynamo DB, Redshift etc.
• Create MYSQL RDS Instance, Oracle RDS Instance, MS SQL RDS Instance
• Configuring the database
• Configuring backups
• Configuring the maintenance windows
• Connecting to the database

Module 15: NDynamo DB (Duration-1hr)

• Creating a dynamo dB
• Adding data manually
•  Learn about strong and eventual consistency
• Calculating Read write consistency
• Configuring alarms

Module 16: Monitoring Services (Duration-1hr)

• Knowledge on Cloud watch – A monitoring service
• Create and Configuring Monitoring services
• How to perform Setting thresholds and Configuring actions
• Creating a cloud watch alarm
• Getting statistics for ec2 instances
•  Monitoring other AWS services
• Configuring Notifications
• Integrating cloud watch with Autoscaling

MOdule 17: Application Services – An Overview  (Duration-1hr)

• What is SNS
• Creating a topic
• Create subscription
• Subscribed to the subscription
• SQS & SES
• Lambda and Elastic Beanstalk

Module 18: AWS Troubleshooting  (Duration-1hr)

• Troubleshooting EC2 instance
• Troubleshooting using Cloud watch
• Troubleshooting using ELB
• Troubleshooting by using Cloud front

Module 19: AWS Architecture and Design  (Duration-1hr)

• Backup and Disaster Recovery
• How to manage Disaster Recovery and Backups
• Best Practice for DR and Backups
• AWS High Availability Design

Module 20: DevOps Fundamentals  (Duration-1hr)

• An understanding of DevOps and the modern DevOps toolsets
• The ability to automate all aspects of a modern code delivery and deployment pipeline using:
• Source code management tools – CVS, Git
• Build tools – Apache ant, Maven
• Test automation tools – JUnit
• Continuous Integration Tools – Jenkins, Team city
• Configuration management tools – Chef, Puppet, Ansible

Machine Learning Training Syllabus

Module 1- Introduction to Data Analytics (Duration : 04:00:00 hrs)

Objectives:

• This module introduces you to some of the important keywords in R like Business Intelligence, Business Analytics, Data, and Information.
• You can also learn how R can play an important role in solving complex analytical problems.
• This module tells you what is R and how it is used by giants like Google, Facebook, etc.
• Also, you will learn the use of ‘R’ in the industry, this module also helps you compare R with other software in analytics, install R and its packages.

Topics

• Business Analytics, Data, Information
• Understanding Business Analytics and R
• Compare R with other software in analytics
• Install R
• Perform basic operations in R using the command line
• Learn the use of IDE R Studio
• Use the ‘R help’ feature in R

Module 2- Introduction to R programming (Duration: 03:00:00 hrs)

Objectives:

• This module starts with the basics of R programming like data types and functions.
• In this module, we present a scenario and let you think about the options to resolve it, such as which datatype should one to store the variable or which R function that can help you in this scenario.
• You will also learn how to apply the ‘join’ function in SQL.

Topics

• Variables in R
• Scalars
• Vectors
• Matrices
• List
• Data frames
• Using c, Cbind, Rbind, attach and detach functions in R
• Factors

Module 3- Data Manipulation in R (Duration : 04:00:00 hrs)

Objectives:

• In this module, we start with a sample of a dirty data set and perform Data Cleaning on it, resulting in a data set, which is ready for any analysis.
• Thus using and exploring the popular functions required to clean data in R.

Topics

• Data sorting
• Find and remove duplicates record
• Cleaning data
• Recoding data
• Merging data
• Slicing of Data
• Merging Data
• Apply functions

Module 4- Data Import techniques in R (Duration: 04:00:00 hrs)

Objectives:

• This module tells you about the versatility and robustness of R which can take-up data in a variety of formats, be it from a CSV file to the data scraped from a website.
• This module teaches you various data importing techniques in R.

Topics

• Reading Data
• Writing Data
• Basic SQL queries in R
• Web Scraping

Module 5- Exploratory data Analysis (Duration: 05:00:00 hrs)

Objectives:

• In this module, you will learn that exploratory data analysis is an important step in the analysis.
• EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis. You will also learn about the various tasks involved in a typical EDA process.

Topics

• Box plot
• Histogram
• Pareto charts
• Pie graph
• Line chart
• Scatterplot
• Developing Graphs

Module 6- Basics of Statistics & Linear & Logistic Regression (Duration : 05:00:00 hrs)

Objectives:

• This module touches the base of Descriptive and Inferential Statistics and Probabilities & ‘Regression Techniques’.
• Linear and logistic regression is explained from the basics with the examples and it is implemented in R using two case studies dedicated to each type of Regression discussed.

Topics

• Basics of Statistics
• Inferential statistics
• Probability
• Hypothesis
• Standard deviation
• Outliers
• Correlation
• Linear & Logistic Regression

Module 7- Data Mining: Clustering techniques, Regression & Classification (Duration : 04:00:00 hrs)

Objectives:

• Linear and logistic regression is explained from the basics with the examples and it is implemented in R using two case studies dedicated to each type of Regression discussed.
• The two Machine Learning types are Supervised Learning and Unsupervised Learning and the difference between the two types.
• We will also discuss the process involved in ‘K-means Clustering’, the various statistical measures you need to know to implement it in this module.

Topics

• Introduction to Data Mining
• Understanding Machine Learning
• Supervised and Unsupervised Machine Learning Algorithms
• K- means clustering

Module 8- Anova & Sentiment Analysis (Duration : 02:00:00 hrs)

Objectives:

• This module tells you about the Analysis of Variance (ANOVA) Technique.
• The algorithm and various aspects of Anova have been discussed in this module
• Additionally, this module also deals with Sentiment Analysis and how we can fetch, extract and my live data from Twitter to find out the sentiment of the tweets.

Topics

• Anova
• Sentiment Analysis

Module 9- Data Mining: Decision Trees and Random Forest (Duration : 03:00:00 hrs)

Objectives:

• This module covers the concepts of Decision Trees and Random Forest.
• The algorithm of Random Forests is discussed in a step-wise approach and explained with real-life examples.

Topics

• Decision Tree
• Concepts of Random Forest
• Working of Random Forest
• Features of Random Forest

Module 10- Project work (Duration: 10:00:00 hrs)

• 2 Real-time projects

Upcoming Batch Schedule for AWS Machine Learning Training

Besant Technologies provides flexible timings to all our students. Here is the AWS Machine Learning Training Classes Schedule in our branches. If this schedule doesn’t match please let us know. We will try to arrange appropriate timings based on your flexible timings.

• 16-12-2024 Mon (Mon - Fri)Weekdays Batch 08:00 AM (IST)(Class 1Hr - 1:30Hrs) / Per Session Get Fees
• 12-12-2024 Thu (Mon - Fri)Weekdays Batch 08:00 AM (IST)(Class 1Hr - 1:30Hrs) / Per Session Get Fees
• 14-12-2024 Sat (Sat - Sun)Weekend Batch 11:00 AM (IST) (Class 3Hrs) / Per Session Get Fees

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Trainer Profile of AWS Machine Learning Online Training

Our Trainers provide complete freedom to the students, to explore the subject and learn based on real-time examples. Our trainers help the candidates in completing their projects and even prepare them for interview questions and answers. Candidates are free to ask any questions at any time.

• More than 7+ Years of Experience.
• Trained more than 2000+ students in a year.
• Strong Theoretical & Practical Knowledge.
• Certified Professionals with High Grade.
• Well connected with Hiring HRs in multinational companies.
• Expert level Subject Knowledge and fully up-to-date on real-world industry applications.
• Trainers have Experienced on multiple real-time projects in their Industries.
• Our Trainers are working in multinational companies such as CTS, TCS, HCL Technologies, ZOHO, Birlasoft, IBM, Microsoft, HP, Scope, Philips Technologies etc

AWS Machine Learning Exams & Certification

Besant Technologies Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher’s as well as corporate trainees.

Our certification at Besant Technologies is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC’s of the world. The certification is only provided after successful completion of our training and practical based projects.

Key Features of AWS Machine Learning Online Training

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