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Certificate Course in

Machine Learning on AWS Cloud Training

  • 24 Hours Interactive Online Sessions
  • 80 Hours Assignments & Real-Time Projects
  • Aligned with AWS Certified Machine Learning
  • Complimentary Python Programming
  • Complimentary Machine Learning Primer
machine learning on aws course reviews - 360digitmg
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machine learning on aws course reviews - 360digitmg
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Academic Partners & International Accreditations
  • Machine Learning on AWS Cloud Training course with Microsoft
  • Machine Learning course certification with innodatatics
  • Machine Learning course with nasscomm
  • Machine Learning on AWS Cloud Training course with TUV
  • Machine Learning on AWS Cloud Training Certification Course with SUNY
  • Machine Learning on AWS Cloud Training Certification Course with NEF

"Companies that adopt cloud services experience a 20.5% average improvement in time to market. 80% of all enterprises will move to the cloud by 2025." - (Source). Amazon Web Services is a cloud service platform that offers flexibility and scalability to deploy services and manage data for organizations of all sizes. AWS provides the broadest and deepest set of machine learning services that fit your business needs and help unlock new insights and value. It also provides visualization tools and services that help developers build, train, and deploy machine learning models without having to learn complex machine learning algorithms and technology. In this course, learn to use AWS Machine Learning tools and services to make smart business decisions.

ML on AWS Course Fee in India

INR 40,460 28,320/-

AWS Machine Learning Training Overview

Learn to use the AWS Cloud platform to scale your business growth. Employ AWS EC2, AWS S3, and AWS RDS to seamlessly store and transfer organization data to and from AWS Cloud. Build, train, and deploy AWS Deep Learning models with Machine Learning on AWS Cloud. This program begins with an introduction to cloud computing and the evolution of Amazon Web Services(AWS). The rudiments of Elastic Cloud Compute (EC2), features of EC2 and types of instances of AWS EC2 are imparted to the student. Data Storage with Simple Storage Services (S3), concepts of creating S3 bucket, storage classes, versioning, static website hosting and cross-region replication of data through S3 are elaborated in detail. Learn about AWS Relational Database Service (RDS), deploying RDS instances and much more. Apprehend Machine Learning using Amazon Sagemaker and NLP and Text Mining using Amazon Comprehend. Build Prediction Models using Machine Learning Services.

Definition

Amazon Machine Learning allows a developer to discover hidden patterns in the data through algorithms, construct models, and implement predictive applications based on these patterns. AWS allows developers to build models according to the specified needs of the organization and helps make better business decisions. These models make a prediction based on probability and allow us to test thousands of potential product designs, improve health care outcomes, and enhance customer service responses. AWS provides many benefits like Security, where data is encrypted to provide end-to-end security. Flexibility, where developers can select the operating system language and database. Usability, where it quickly deploys applications, builds new apps and migrates existing ones. Last but least Scalability, where developers can scale up or down as needed.

Machine Learning on AWS Learning Outcomes

Machine Learning is about making predictions using algorithms, modern computing power and simple statistical methods. AWS is designed to securely host your applications and enables you to select the operating system, programming language, and other services you need and pay only for the computing power, storage, and services you use. With Amazon ML one can build data from large data sets, make predictions that are used to solve real-time problems. This course introduces you to the Machine Learning concepts and terminologies, how to create and use machine learning models, how to evaluate that model's performance, and what problems can machine learning solve. Students will learn to build, train, tune, and deploy ML models using the AWS Cloud. Using the Machine Learning web service offered by Amazon you will learn to work with data sources and generate accurate predictions. Explore real-world use cases with Machine Learning (ML) and using Amazon Sage Maker which enables Data Scientists and developers to easily deploy your ML use cases and removes the complexity from each step of the ML workflow also discover common neural network frameworks with Amazon Sage Maker.

Cloud technology and its advantages
Various Machine Learning services offered on AWS
Understand how data is loaded on to cloud storage services
Build predictive models using Amazon Machine Learning services
Connecting Amazon database services and transforming data
Understand how to deploy a model on cloud

Block Your Time

machine learning on aws course - 360digitmg

24 hours

Live Sessions

machine learning on aws course - 360digitmg

40 hours

Assignments

machine learning on aws course - 360digitmg

40 hours

Live Projects

Who Should Sign Up?

  • Data scientists, technology heads, decision-makers
  • Professionals with analytics knowledge
  • Professionals with industry domain experience in various areas (banking, finance, insurance, mechanical, IoT etc.)

Machine Learning on Cloud Modules

Each module encapsulates the essential tools to impart machine learning skills using the two most popular programming languages Python and R. You will learn how to establish a gateway between different databases with R and Python and also how to connect to external sources of data. One of the major modules of Data Science is Machine Learning. Learn about the various modules that make up Machine Learning using the two most popular tools R and Python. As a data scientist one will be engaged in a multitude of data mining techniques in both supervised and unsupervised learning. One of the major variants of the same is reinforcement learning that enables machines to learn through rewards. Get introduced to all the supervised techniques of prediction and classification; learn about the major unsupervised learning methods and the application of reinforcement learning in Data Mining.

Learn two of the most powerful programming languages used in Data Analytics. Both R and Python are the top two tools used by Data Analytics professionals world over. Start learning from the very basics, right from installation and work your way up through simple commands, writing small functions and programs.

Both R and Python can connect to a wide variety of data sources. Under this module, learn how to establish a gateway between different databases with R and Python. Also, learn how to connect to external sources of data.

One of the major modules of Data Science is Machine Learning. Learn about the various modules that make up Machine Learning using the two most popular tools R and Python. Get introduced to the broad overview of ML and the various quality metrics with the help of R and Python.

In the real world, oftentimes, the datasets cannot be used as such and some amount of preprocessing activity needs to be done. Imbalance in the output classes is one of the common problems where sometimes the proportion may be as lopsided as 95% to 5% or even higher. Learn about the various methods and algorithms to address this problem of imbalanced data sets.

One of the integral parts of learning Data Science and working on Analytics projects is the sound understanding of Statistical tools. In this module learn about the need to know statistical measures and their application in Data Science. Also, learn how to visualize the data in a concise form to derive various meaningful insights.

The essence of analytics is to be able to get the story from the data. And for the data to be able to truly be useful one needs to munge the raw data to make it legible. Using tools like R and Python, learn how to manipulate data from the raw form to make it ready for subsequent ML algorithms. The topic is all the more important in the current context given that a lot of data is moving to the unstructured format.

Both R and Python while being classified under the object-oriented programming languages category, still require some traditional approach to programming whereby the user-defined function needs to be spelled out and the use of conventional program snippets is of utmost importance. In this module, learn how to create simple to complex user-defined functions and hone your programming skills in the context of machine learning.

As a data scientist one will be engaged in a multitude of data mining techniques in both supervised and unsupervised learning. One of the major variants of the same is reinforcement learning that enables machines to learn through rewards. Under this module, get introduced to all the supervised techniques of prediction and classification; learn about the major unsupervised learning methods and the application of reinforcement learning in Data Mining.

Under supervised learning one of the most popular methods of predicting numeric data is linear regression and for classifying categorical data is logistic regression. These two methods will be covered in detail under this module. And the participant will be introduced to multiple examples using R and Python.

Under the classification modeling, decision trees method has a special place even though they are not truly classification modeling techniques but rule-based algorithms. The popularity of Decision trees is in its simplicity, high accuracy, and most important the ability to explain behind- the- scenes working of the algorithm. Under this module, the participant will be introduced to working with Decision trees using R and Python.

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    Additional Assignments of over 80+ hours
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    Live Free Webinars
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    Resume and LinkedIn Review Sessions
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    Job Placements in Machine Learning on AWS fields
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Cloud Machine Learning Panel of Coaches

Artificial Intelligence & Deep Learning Course Training -360digitmg

Bharani Kumar Depuru

  • Areas of expertise: Data analytics, Digital Transformation, Industrial Revolution 4.0
  • Over 18+ years of professional experience
  • Trained over 2,500 professionals from eight countries
  • Corporate clients include Deloitte, Hewlett Packard Enterprise, Amazon, Tech Mahindra, Cummins, Accenture, IBM
  • Professional certifications - PMP, PMI-ACP, PMI-RMP from Project Management Institute, Lean Six Sigma Master Black Belt, Tableau Certified Associate, Certified Scrum Practitioner, (DSDM Atern)
  • Alumnus of Indian Institute of Technology, Hyderabad and Indian School of Business
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Artificial Intelligence & Deep Learning Course Training -360digitmg

Sharat Chandra Kumar

  • Areas of expertise: Data sciences, Machine learning, Business intelligence and Data
  • Trained over 1,500 professional across 12 countries
  • Worked as a Data scientist for 18+ years across several industry domains
  • Professional certifications: Lean Six Sigma Green and Black Belt, Information Technology Infrastructure Library
  • Experienced in Big Data Hadoop, Spark, NoSQL, NewSQL, MongoDB, Python, Tableau, Cognos
  • Corporate clients include DuPont, All-Scripts, Girnarsoft (College-, Car-) and many more
Read More >
 
Artificial Intelligence & Deep Learning Course Training - 360digitmg

Bhargavi Kandukuri

  • Areas of expertise: Business analytics, Quality management, Data visualisation with Tableau, COBOL, CICS, DB2 and JCL
  • Electronics and communications engineer with over 19+ years of industry experience
  • Senior Tableau developer, with experience in analytics solutions development in domains such as retail, clinical and manufacturing
  • Trained over 750+ professionals across the globe in three years
  • Worked with Infosys Technologies, iGate, Patni Global Solutions as technology analyst
Read More >
 
machine learning on aws cloud certification - 360digitmg

Certificate

Get validation of your advanced skills and knowledge with the Machine Learning on AWS Cloud certificate. Join the growing community of developers and data scientists trained on AWS.

Alumni Speak

Pavan Satya

"The training was organised properly, and our instructor was extremely conceptually sound. I enjoyed the interview preparation, and 360DigiTMG is to credit for my successful placement.”

Pavan Satya

Senior Software Engineer

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Chetan Reddy

"Although data sciences is a complex field, the course made it seem quite straightforward to me. This course's readings and tests were fantastic. This teacher was really beneficial. This university offers a wealth of information."

Chetan Reddy

Data Scientist

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Santosh Kumar

"The course's material and infrastructure are reliable. The majority of the time, they keep an eye on us. They actually assisted me in getting a job. I appreciated their help with placement. Excellent institution.”

Santosh Kumar

Business Intelligence Analyst

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Kadar Nagole

"Numerous advantages of the course. Thank you especially to my mentors. It feels wonderful to finally get to work.”

Kadar Nagole

Data Scientist

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Gowtham R

"Excellent team and a good atmosphere. They truly did lead the way for me right away. My mentors are wonderful. The training materials are top-notch.”

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Wan Muhamad Taufik

"The instructors improved the sessions' interactivity and communicated well. The course has been fantastic.”

Wan Muhamad Taufik

Associate Data Scientist

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Venu Panjarla

"The instructors went above and beyond to allay our fears. They assigned us an enormous amount of work, including one very difficult live project. great location for studying.”

Venu Panjarla

AVP Technology

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FAQs on Cloud Machine Learning Certification

After you have completed the online sessions, you will receive assignments through the online Learning Management System that you can access at your convenience. You will need to complete the assignments in order to obtain your data scientist certificate.

In this blended programme, you will be attending 24 hours of online sessions of 2.5 months. After completion, you will have access to the online Learning Management System for another three months for recorded videos and assignments. The total duration of assignments to be completed online is 80+ hour.

There are plenty of jobs available for cloud professionals. Once you complete the training, assignments and the live projects, we will send your resume to the organisations with whom we have formal agreements on job placements.

We also conduct webinars to help you with your resume and job interviews. We cover all aspects of post-training activities that are required to get a successful placement.

If you miss a class, we will arrange for a recording of the session. You can then access it through the online Learning Management System.

We assign mentors to each student in this programme. Additionally, during the mentorship session, if the mentor feels that you require additional assistance, you may be referred to another mentor or trainer.

Jobs in the field of Machine Learning on AWS in India

Jobs in the field of Machine Learning in AWS

The increasing demand for Machine learning on AWS has given rise to several high paying jobs like Special Solution Architect AI/ML, Machine Learning Engineer, Cloud Developer, AWS Solutions Architect, DevOps Engineer, etc.

Salaries in India for AWS

Salaries in India for AWS

Machine learning engineers with the right skills and experience enjoy highly promising positions. The salary of a Machine learning Scientist at amazon is between 20L to 40 LPA and a Machine Learning engineer in India can expect a salary of Rs 8,21,546.

Machine Learning on AWS Course Projects in India

AWS Projects in India

You can work on various projects using Amazon Web Services like Hosting an application on a website, building a secure online store, designing a database for a mobile app, creating an audio transcript, and deploying a Python web application to name a few.

Role of Open Source Tools in machine learning on AWS Course

Role of Open Source Tools in AWS

With Amazon Machine Learning you can build and train predictive models, host an application, design a database for a mobile app, or identify potential customers for a marketing campaign. In this course, we will learn to customize machine learning algorithms using TensorFlow, and PyTorch.

Modes of Training for Machine Learning on AWS course with Python

Modes of Training for Machine Learning on AWS

The course in India is designed to suit the needs of students as well as working professionals. We at 360DigiTMG give our students the option of Interactive Live online learning. We also support e-learning as part of our curriculum.

Industry Application of Machine Learning on AWS Course

Industry Application of Machine Learning on AWS

Machine Learning applications are used in fraud detection, self- driving cars, virtual personal assistants, product recommendations, traffic alerts, etc.

Companies That Trust Us

360DigiTMG offers customised corporate training programmes that suit the industry-specific needs of each company. Engage with us to design continuous learning programmes and skill development roadmaps for your employees. Together, let’s create a future-ready workforce that will enhance the competitiveness of your business.

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