Does this course require any specific qualifications?

No, one does not need any specific qualification but a background in math or programming will come in handy.

Is the certification a recognized credential?

Yes, you will receive a completion certificate from 360DigiTMG and it holds immense value in the market.

Is any course material available online?

Yes, we have our own LMS called AISPRY, it has all the valuable learning material accessible to our students at any time.

Are there any group projects available for the students?

Yes, to ensure the concepts are crystal clear to the students we have individual as well as group assignments under the guidance of a mentor who helps students at every stage of the project.

Do you offer any payment plans?

Yes, we have the provision of easy monthly installments where can have to pay a fixed amount every month.

Do I get any assistance with finding a job?

Yes, we provide 100% job assistance and also help you with your resume building and conduct several mock sessions for interview preparations.

Can I pursue this course online?

Yes, we have both classroom and online classes to facilitate the needs of students as well as working professionals.

Certificate Course in

Best ML on Cloud & Auto ML Course Training in Lebanon

Name: Machine Learning on Cloud Course Training in Lebanon - 360DigiTMG
Brand: 360DigiTMG
Rating: 5 (4071 reviews)

Build, train and deploy Machine Learning models using Cloud. Advance your career in this in-demand and powerful field with certification in Machine Learning on Cloud.

Get Trained by Trainers from ISB, IIT & IIM
24 Hours of Intensive Classroom & Online Sessions
60+ Hours of Practical Assignments
2 Capstone Live Projects
AWS Certified Speciality Machine Learning Certification

493 Reviews

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Academic Partners & International Accreditations

The Machine Learning on Cloud course is designed to equip you with the necessary skills needed in this field. Even as we speak, technology is advancing making its way into the domain of Machine Learning which is a part of Artificial Intelligence. Recently machine learning in the cloud has been a boon for businesses and provides many benefits like the pay-per-use model where you pay only for space used resulting in no wasted resources and helping companies cut down on costs. With Google Cloud Platform, Microsoft Azure, and AWS companies now don’t have to worry about having a data science proficient team because now the artificial intelligence features can be functional without requiring any deep or hardcore knowledge. As businesses adopt both machine learning and cloud together, they will need individuals who know both the worlds and can provide value to the organization. The Machine Learning on Cloud Certification course will be a step towards your career growth.

ML on Cloud

machine learning on aws course duration in Lebanon- 360digitmg

Total Duration

1 Month

Prerequisites

Traditional ML Algorithms & DL Algorithms
Programming Knowledge
No cloud knowledge is needed

Machine Learning on Cloud Training Overview

Learn to install Machine Learning models on the cloud in the most comprehensive program. Learn the various ML algorithms to handle large data and to derive patterns and predict results. Explore how Machine Learning models are designed, deployed, configured, and managed on the various cloud platforms. You will also learn about the various benefits of Machine learning on the cloud and also draw a comparison of machine learning services on various cloud platforms like AWS, Azure, and Google Cloud.

The course commences with an introduction to AWS and Amazon SageMaker. Learn the various benefits of Amazon SageMaker and explore all ML Algorithms in-built in SageMaker. In this course, you will also learn about Machine Learning in Azure and how its UI-based interface and predefined algorithms help in building training models. Learn ML model handling using AutoML or advanced model optimization and infuse cutting-edge AI technologies into your applications via tools like TensorFlow and TPUs while learning Google Cloud Platform. Also, explore the features of IBM Watson's cognitive computing technology. This course is designed for Data Science Enthusiasts, Statisticians, Cloud engineers, Software and IT engineers, Software Architects, etc.

Machine Learning on Cloud Learning Outcomes

Machine learning focuses on developing applications that learn from data and improves its efficiency. This course will equip students to give end-to-end packaged ML solutions for any organization. Students will learn to apply a machine-learning algorithm to categorize data and make appropriate predictions. This course prepares you to work in large organizations to meet the ML needs of the organizations. Students will also learn about machine learning and cloud computing capabilities that help resolve IT problems and how it can analyze large amounts of data with speed and agility in performance. Students will learn about AWS & Amazon SageMaker and how to handle Machine Learning Models along with working on ML frameworks available in SageMaker. In this course, you will also learn about the machine learning services provided by Microsoft Azure and how to manage data in the cloud, and how to automate the end-to-end machine learning process in the cloud. Students will also explore Google Cloud and Machine Learning wherein they will learn about the various Algorithms and Services available in GCP and how one can compute, store, and process data on Google Cloud Platform (GCP). So, if you want to soar in your career as an ML Cloud engineer join the course on Machine Learning on Cloud.

Examine the various Machine learning offering provided by various cloud services

Learn about the application and benefits of AWS, GCP, IBM Watson and Azure cloud platforms

Understand how to develop, train and deploy ML models on Cloud

Apply the various Machine Learning Algorithms to segregate data and make predictions

Explore hoe to compute, store and process data on various cloud Platforms

Block Your Time

machine learning on Cloud course in Vietnam- 360digitmg

24 hours

Classroom Sessions

60 hours

Assignments

60 hours

Live Projects

Enroll Now

Who Should Sign Up?

IT Engineers
Data and Analytics Manager
Business Analysts
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

Machine Learning on Cloud is a unique program that helps you learn about machine learning capabilities in the cloud. With the adoption of cloud computing, many companies have realized that the ‘One cloud fit all’ approach doesn’t work anymore. Therefore, this course includes concepts of Machine Learning across various platforms. The course commences with the module on the introduction of AWS cloud and benefits of Amazon SageMaker and how it facilitates the building, training, and deploying of machine learning models at any scale. Then the students will learn about the Microsoft Azure Machine Learning Services and then further students will be introduced to Google Cloud Platform followed by features of cognitive computing and IBM Watson. Join this certification program if you aspire to learn the fundamentals of Machine Learning on the Cloud.

1. Machine Learning on Cloud & AutoML

Introduction to Cloud Computing
The ML development Life Cycle
Automated ML
How automated ML works
Democratization of Data Science
Debunking automated ML myths
Automated ML Ecosystem
Automated Feature Engineering
Automated Model Selection and Hyperparameter Tuning
Automated Neural Network Architecture Selection
Automated Model choosing and Hyperparameter Optimization
Automated ML Challenges and Limitations
AutoML and AutoAI
Four levels of Automation
- Basic Automation
- Process Automation
- Integration Automation
- AI Automation
AutoML with Open Sources
TPOT – Tree-based Pipeline Optimization Tool
AutoML - AutoKeras
AutoML with Cloud Platforms

2. Amazon Web Services & Amazon SageMaker

3. AWS Machine Learning Services

4. Microsoft Azure Machine Learning Services

Introduction to Microsoft Azure ML Services
Pipeline Building for ML Solutions
Varied Machine Learning Microsoft Azure Services
Azure GUIs and Workspace
AML Studio
Creating your first AMLS workspace
Building compute to run your AutoML jobs
Working with data in AMLS
Understanding how AutoML works on Azure
Feature Engineering on Azure
Feature Extraction after Data Pre-processing
Building ML Pipeline Workflows using Designer
Building ML Models on Automated ML
Hyperparameter Tuning in Azure
Model Deployment on Azure
Real-Time vs Batch Scoring Services
Constant Real-Time Monitoring of Model Deployments

5. Machine Learning with Google Cloud Platform

Introduction to GCP
Primer to Machine Learning in GCP
Services Available in GCP
Compute, Storage and Processing in GCP
Building ML Pipeline in GCP
Building XGBoost in GCP
Using Pretrained Models in GCP
NLP for Document Classification using AutoML NLP
AutoML Vision APIs for Handling Image AI Problems
Building a Big Data Cloud ML Engine
Batch Processing and Real-Time Prediction using Cloud ML Engine
Compute & Monitoring Options for Training the Model Jobs
Model Versioning of Saved Models
Model Deployment on GCP
Prediction with Service Endpoints
Usage of Google Cloud DialogFlow & Google Cloud Dataproc

6. IBM Watson Machine Learning

IBM Watson Studio
IBM Watson Machine Learning architecture and services
Data Preparation
Analyzing data and building models
Evaluate models
Deploying and managing models with Watson Machine Learning

7. eXplainable AI (XAI)

Defining XAI
The key features of XAI
Executive function XAI
Different forms and methods of XAI - Pre, During, Post
XAI timeline from conception to production
AI accountability

Trends in Machine Learning on Cloud

Organizations today are focusing on machine learning and artificial intelligence areas. AI and Machine Learning with Cloud Computing turn out to be more cost-effective and increase production too. It is believed that AI and ML will be the reason for cloud adoption in the future. Machine Learning basically can be enhanced when coupled with cloud technology and we will see continuous growth of a hybrid cloud environment. The other trend we will see will be the significance of retaining compliance in an increasingly complex environment to protect vital information from getting hacked. With small and large organizations using more and more cloud services without any control over the costs. This scenario will have to change and businesses will have to make it a priority to control cloud costs.

The global cloud computing market is predicted to go over $651 by 2025 and close to 80% of businesses are forecasted to migrate to the cloud. From eliminating the hassles of maintaining hardware to providing stability and security, a cloud-powered future is starting to shape. As businesses and cloud providers realize the potential of Machine learning in the cloud and how machine learning makes cloud computing more efficient and scalable, it will only spur the demand for Cloud Machine Learning Platforms. So, if you want to gain skills in this in-demand and influential field, join the course in Machine Learning on Cloud.