Get a comprehensive view of all the training sessions scheduled for the year with our Training Calendar. Now plan your training schedule and choose from a range of courses at your convenience.
Our calendar makes it easier for you to choose from our diverse range of courses. The calendar includes different types of courses, such as one-day sessions & boot camps, enterprise training, and certification courses. Not only do you get a clear picture of what courses are available, but you can also choose courses that best suit your schedule.
Building Agentic AI with Amazon Bedrock AgentCore is an intermediate, 1-day instructor-led AWS classroom training designed to help learners move agentic AI systems from experimentation to enterprise-grade production.
Participants explore agentic AI patterns, understand core agent components and their interactions, and implement production-ready architectures using Amazon Bedrock AgentCore capabilities such as Runtime, Identity, Policy, Gateway, Memory, Observability, and Evaluations.
The course combines presentations, hands-on labs, and group exercises to ensure learners can confidently design, secure, deploy, and monitor agentic AI systems in real-world environments.
Building Advanced Agentic Systems on AWS is a 1‑day advanced-level AWS classroom training designed for developers and technical teams ready to build real-world, production-grade multi-agent systems.
The course covers multi-agent communication patterns, context engineering, security controls, VPC integration, policy-based access, observability, distributed tracing, and evaluation frameworks. Hands-on labs and instructor demonstrations help learners design and deploy scalable agent architectures using Amazon Bedrock AgentCore.
This comprehensive course provides an end-to-end learning journey into the design, implementation, and governance of generative AI systems using AWS services. Participants will explore advanced concepts such as dynamic model selection, resilient deployment patterns, and cross-region reliability strategies. You’ll learn to build vector search and retrieval systems, develop prompt engineering and agent orchestration frameworks, and enforce AI safety, security, and observability controls. The course also emphasizes performance optimization, cost management, and continuous testing methodologies, equipping learners with the skills to deliver secure, compliant, and scalable AI architectures in production environments.
The Data Engineering on AWS course is designed for data professionals who want to learn how to design, build, secure, and optimize data pipelines on AWS. Through a combination of lectures, demonstrations, and hands-on labs, participants will gain practical experience in ingesting, transforming, storing, and analyzing data using AWS data services.
This course covers essential data engineering topics such as data lakes, batch and streaming data processing, orchestration, and automation, enabling learners to create scalable, efficient, and secure data pipelines aligned with AWS best practices.
By the end of this course, learners will have the skills to design and implement data workflows for real-world analytics and machine learning applications.
This course is designed specifically for business users and decision-makers seeking a foundational understanding of generative AI. It covers the distinction between generative AI and other forms of AI, introduces key personas and use cases, and explores the ethical dimensions of responsible AI. Through interactive lectures and case study analysis, the course inspires leaders to explore how generative AI can create impact across business functions using Google Cloud technologies such as Vertex AI and Gemini.
This 1-day, fundamental-level training introduces participants to the principles, components, and AWS services that power Agentic AI. You’ll explore how agentic systems differ from traditional conversational AI, learn workflows, autonomous agents, hybrid architectures, and gain hands-on experience building goal-driven AI solutions with Amazon Bedrock Agents and AgentCore.
This Cloud Operations on AWS course is ideal for systems operators and anyone wanting to learn how to deploy, manage, and operate workloads on AWS. In addition, by attending this Cloud Operations on AWS training, candidates also learn how to automate, secure, monitor, maintain and troubleshoot networks, systems, and services running on AWS to support business applications.
The Cloud Operations on AWS course also offers candidates an understanding of specific AWS features, tools, and best practices related to these functions. This Course includes instructor presentations, hands-on labs, demonstrations, and group knowledge checks.
This training is designed to prepare learners for the Machine Learning Engineering on AWS. It focuses on developing end-to-end ML solutions on AWS. Learners will explore problem framing, data engineering, model training and evaluation, deployment, monitoring, and optimization. Through hands-on labs, real-world scenarios, and exam-focused guidance, students will gain practical ML skills and a thorough understanding of AWS services like SageMaker, S3, Glue, and CloudWatch.
This one-day training course offers a comprehensive introduction to generative AI using AWS services. Participants will explore key concepts, practical use cases, and hands-on labs to optimize AI model performance. The course emphasizes responsible AI principles, security, governance, and compliance, ensuring ethical AI practices. Through real-world demos and a capstone project, attendees will gain the skills needed to implement generative AI projects and integrate them into the development lifecycle. Ideal for career advancement in AI, the course provides networking opportunities and post-training support.
The AWS Cloud Practitioner Essentials covers the following domains:
Cloud Concepts: This domain assesses your understanding of the fundamental aspects of cloud computing and how AWS implements these concepts. It covers topics such as the advantages of using the AWS Cloud, the different types of cloud computing, and the basic global infrastructure of AWS.
Security and Compliance: This domain evaluates your understanding of AWS security and compliance concepts and the shared responsibility model. It covers topics such as the AWS shared responsibility model, AWS security and compliance concepts, and the AWS access management capabilities.
Technology: This domain examines your understanding of AWS Cloud services and their use cases. It covers topics such as the different AWS service categories, key AWS services, and their common use cases.
Billing and Pricing: This domain assesses your understanding of AWS billing, account management, and pricing models. It covers topics such as the fundamentals of AWS billing, pricing models for various AWS services, and account management best practices.
With Designing and Implementing Storage on AWS, you can learn how to choose, design, and optimize secure storage solutions to reduce costs and time, increase performance and scale, and spur innovation. Examine the storage options and services offered by AWS to store, retrieve, and safeguard your data. You will receive guidance from AWS Authorized Instructors on when, how, and where to use various storage services.
Discover how to assess AWS storage service options most effectively to fulfil your use case and business needs. This delves deeply into cloud data storage, management, and security. You will learn how to swiftly provision robust storage solutions in minutes through talks, examples, group activities, and several practical labs.
Do you want generative AI to enhance customer experiences and resolve challenging business issues? Developing Generative AI Applications on AWS teaches you how to create generative AI applications.
During this two-day course, a knowledgeable instructor with experience in Python will walk you through the fundamentals, advantages, and related jargon of generative artificial intelligence as a developer. In order to create generative AI applications using AWS services, you will discover the fundamentals of prompt engineering, how to plan a generative AI project, and more. By the end of the course, you will acquire the knowledge and abilities required to create applications that can answer queries, create and summarize text, and communicate with users via a chatbot interface.
AWS Security Essentials is fundamental-level 1-day course covers fundamental security concepts on AWS Cloud. This course covers AWS access control, data encryption methods, and how to secure the network access to your AWS infrastructure. Learners get to understand AWS Shared Responsibility Model which divides the responsibility of security of the cloud and security in the cloud amongst AWS and customers respectively. Security needs of an organization implemented as Security-oriented services available in AWS will be the highlight of this training.
The MLOps Engineering on AWS course is designed to provide hands-on experience and knowledge in building, training, deploying, monitoring, and managing machine learning models on AWS. The course will guide you through setting up the environment, designing ML pipelines, and implementing the best practices to ensure high-performing and scalable solutions.
Introduction to MLOps on AWS: Understanding the key concepts and principles of MLOps and its importance in the machine learning lifecycle. Exploring the AWS ecosystem for MLOps, including Amazon SageMaker, AWS Lambda, Amazon S3, AWS Batch, and more.
Building and Deploying Machine Learning Models on AWS: Designing and implementing end-to-end machine learning pipelines on AWS. This includes data preprocessing, model training, model evaluation, and model deployment using Amazon SageMaker and other AWS services.
Monitoring and Managing Machine Learning Models on AWS: Monitoring machine learning models in production using Amazon CloudWatch and other AWS monitoring tools. Understanding best practices for managing and scaling machine learning infrastructure on AWS.
Optimizing and Scaling Machine Learning Workloads on AWS: Troubleshooting and optimizing machine learning pipelines for performance and scalability. Exploring strategies for automating and scaling machine learning workloads using AWS Batch, AWS Lambda, and other AWS services.
Introduction to Amazon SageMaker Studio: An overview of SageMaker Studio’s features, including its integrated Jupyter notebooks, model debugging, and experimentation tools.
Data Preprocessing: Techniques for preparing and cleaning datasets for training and inference.
Model Building and Training: How to build and train machine learning models using SageMaker’s built-in algorithms and AutoML capabilities.
Model Deployment and Monitoring: Deploying models to SageMaker endpoints and monitoring their performance.
Continuous Integration/Continuous Deployment (CI/CD) Pipelines: Automating the process of deploying and updating models in production.
This course will teach you how to use Amazon EMR, an enterprise-grade managed service for Apache Spark and Apache Hadoop, to create batch data analytics solutions. You will discover how AWS services such as AWS Glue and AWS Lake Formation, as well as open-source initiatives such as Apache Hive, Hue, and HBase, are integrated with Amazon EMR. In the context of Spark and Hadoop, the course covers data ingestion, cataloging, storage, and processing. You will gain knowledge on how to support workloads related to machine learning and analytics using EMR Notebooks. Additionally, you will learn best practices for cost management, performance, and security when using Amazon EMR.
Building Data Analytics Solutions using Amazon Redshift
This course guides you through creating an end-to-end analytics solution using Amazon Redshift, a managed cloud-based data warehouse. It covers the complete data lifecycle—from gathering and ingesting data to organizing, storing, and transforming it for analysis. You will also learn how to integrate Redshift with a data lake to support advanced analytics and machine learning scenarios. Along the way, the course highlights practical approaches to ensure data security, improve system performance, and manage costs effectively.
Building Streaming Data Analytics Solutions on AWS
Through a combination of instructor-led presentations, practice labs, demonstrations, and in-class exercises, the course delves deeply into Amazon Kinesis and Amazon MSK so that you can leave with an understanding of how to create a streaming data analytics solution on AWS. Along with these skills, you’ll learn how to use Amazon Kinesis and Amazon MSK to scale streaming applications, optimize data storage, choose and implement the best options for ingesting, transforming, storing, and analyzing data.
The Architecting on AWS Course teaches candidates about the fundamentals of building IT infrastructure on the AWS platform. Candidates attending this Architecting on AWS training to learn how to optimize the AWS Cloud and how to use the AWS to fit into cloud-based solutions.
The Architecting on AWS training covers best practices and design patterns to help candidates to learn how to architect optimal IT solutions on the AWS Cloud and build and explore a variety of infrastructures through guided discussions and hands-on activity. The course comprises presentations, group exercises, and hands-on labs.
PL-300: Design and manage analytics solutions using Power BI
PL-300 is a Microsoft certification exam focusing on the tool Power BI, including designing solutions, creating solutions, implementing solutions, and supporting organizational adoption of the Power Platform.
The Microsoft PL-300 Power BI course is structured to provide instruction on utilizing Power BI, a business intelligence tool that empowers users to analyze and visualize data from diverse sources. PL-300 power bi course covers the following topics:
Introduction to Power BI: This section provides an overview of Power BI, including its capabilities, architecture, and data sources.
Connecting to Data: This section covers how to establish connections with diverse data sources, such
as Excel, SQL Server, and cloud-based data sources.
Data Modeling: Learn to create relationships between tables, develop calculated columns and measures, and build hierarchies.
Visualizations: Discover how to create and customize visualizations, such as tables, charts, maps, and gauges.
Dashboards and Reports: Understand how to create dashboards and reports to meaningfully visualize data and share it with others.
Publishing and Sharing: Learn to publish and share dashboards and reports within your organization.
Power BI Service: Explore the Power BI service, including accessing it, working in workspaces, and collaborating.
The PL 300 certification course typically includes hands-on labs and exercises to reinforce your learning. Upon completing the course, you will have a solid understanding of Power BI, enabling you to create visualizations, dashboards, and reports that provide valuable insights from data.
Microsoft Power BI Data Analyst-Exam Details (PL 300)
Certification Name
Microsoft Certified: Power BI Data Analyst Associate
Question Type
Multiple-choice and Multiple response questions
Exam Cost
USD 165.00*
Total Questions
40 – 60 Questions
Exam Duration
100 minutes (to answer the questions)
PL-200: Microsoft Power Platform Functional Consultant
In PL-200 Power Platform Functional Consultant certification training course from CloudThat, students will learn to perform discovery, capture requirements, engage subject matter experts and stakeholders, translate requirements, and configure Power Platform solutions and apps. They will supplement their learnings with hands-on labs to create application enhancements, custom user experiences, system integrations, data conversions, custom process automation, and custom visualizations. The Power Platform empowers organizations to automate business processes, develop their own rich app experiences, and connect with customers better and faster.
In PL-400 Microsoft Power Platform Developer Associate certification course from CloudThat, In PL-400 Microsoft Power Platform Developer Associate certification course from CloudThat, candidates learn to design, test, develop, secure, and troubleshoot Microsoft Power Platform solutions. Candidates also learn how to implement system integrations, application enhancements, data conversions, custom user experiences, and custom process automation. The Microsoft Power Platform helps organizations optimize operations by simplifying, automating, and transforming business tasks and processes.
Note: Exam PL-400 replaced exam MB-400 which retired on 31st December 2020.
The AZ-104 Microsoft Azure Administrator Associate certification training from CloudThat offers candidates proper training and relevant study material to clear the new this exam targeted for Azure Administrators. Taking up this Azure 104 certification training and passing the exam will meet all the Azure certification requirements necessary to be a certified Microsoft Azure 104 Administrator Associate.
As part of a larger team, Azure administrator performs various roles, including implementation of an organization’s cloud infrastructure. In addition, the responsibilities of Azure AZ 104 administrator also include managing, implementing, and monitoring identity, storage, governance, compute, and virtual networks in a cloud environment, along with monitoring and adjusting resources when required.
CloudThat’s AZ-204 Certification Training: Developing Solutions for Microsoft Azure teaches candidates how to develop, deploy and maintain cloud solutions on Microsoft Azure. This AZ 204 Certification course also teaches candidates how to develop Azure storage and compute solutions, monitor, troubleshoot, and optimize Azure solutions, as well as how to implement Azure security. This Azure 204 certification course is ideal for cloud developers who work with cloud administrators, cloud DBAs, and clients to implement solutions on Azure.
The Microsoft AZ-204 certification fulfills the criteria for earning the Microsoft Certified Azure Developer Associate certification. Participants in our AZ-204 certification training gain access to a meticulously crafted curriculum and engage in interactive sessions facilitated by our Microsoft-certified trainers.
This course from CloudThat is for the Azure Fundamentals exam AZ-900 targeted for anyone looking to demonstrate foundational level knowledge of Cloud services and how those services are provided with Microsoft Azure. Taking this course and passing the AZ-900 exam meets all the requirements for Microsoft Certified Azure Fundamentals certification.
The exam is intended for candidates with non-technical backgrounds, such as those involved in selling or purchasing Cloud-based solutions and services or who have some involvement with Cloud-based solutions and services, as well as those with a technical background who have a need to validate their foundational level knowledge around Cloud services.
The course will cover general Cloud computing concepts as well as general Cloud computing models and services such as Public, Private and Hybrid Cloud and Infrastructure-as-a-Service (IaaS), Platform-as-a-Service(PaaS) and Software-as-a-Service (SaaS). It will also cover some core Azure services and solutions, as well as key Azure pillar services concerning security, privacy, compliance and trust. It will finally cover pricing and support services available with Azure.
This AZ-500 certification training course from CloudThat is designed to train IT professionals who plan to take the Microsoft AZ-500 certification exam. This course and passing the AZ-500 exam will meet all the requirements to become a Microsoft Certified Azure Security Engineer Associate.
The Microsoft Certified Azure Security Engineer Associate certification offers in-depth knowledge and understanding of Azure Security Technologies.
Azure security engineers often serve as part of a larger team to plan and implement cloud-based management and security. The responsibilities of an Azure security engineer include managing the security posture, identifying and remediating vulnerabilities, performing threat modeling, implementing threat protection, and responding to security incident escalations.
AZ-400: Designing and Implementing Microsoft DevOps Solutions
The AZ-400 certification exam places significant emphasis on DevOps practices and tools tailored for Microsoft environments. AZ 400 Exams is designed for DevOps experts who adeptly integrate individuals, procedures, and technologies to consistently provide valuable products and services aligned with end-user requirements and business goals. DevOps professionals excel in enhancing the delivery process by refining methodologies, enhancing communication and cooperation, and implementing automation. The AZ-400 exam course and course are pivotal for individuals seeking to validate their expertise in this domain. objectives. DevOps professionals streamline delivery by optimizing practices, improving communications and collaboration, and creating automation.
As this is an Expert level certification program, we will deep dive into End-to-End DevOps Practices, Starting from
How to get started with DevOps?
How to work in a team collaboratively and obtain best outcome?
You will learn, how to use Source control management system.?
How to implement Continuous Integration and Continuous Delivery/ Deployment?
How can you manage your Artifacts and maintain it in a repository?
How to secure your process to avoid Attacks?
How to maintain quality throughout the process?
How to work with infrastructure as a Code?
How to implement testing and Release Management?
This full-fledged course is a mix of graphics, reference links, module review questions, and optional hands-on lab including Exam Guides.
This course covers Managing Microsoft Teams and maintaining internal and external collaboration and communication solutions using Teams and Microsoft 365.
This course helps in configuring and managing teams, channels, chat, apps, calling, meetings, and events. How we can manage phone numbers and services for Teams Phone. How to manage the operational aspects of Teams, clients and devices. How to collaborate with owners of other workloads, including networking, identity, licensing, information management, and user adoption.
The course will help you learn concepts for how to work with Microsoft teams and manage the various features available in Teams.
AI-102: AI-102 equips you with the expertise to design, develop, and implement AI solutions using Azure AI. This course integrates your existing programming and AI knowledge to manage AI solution planning, image and video processing, natural language processing, knowledge mining, and conversational AI implementation.
AZ-700: Designing and Implementing Microsoft Azure Networking Solutions
This AZ-700AZURE NETWORK ENGINEERcertification training course equips the aspirants with required skills and knowledge to be a successful network administrator with all the necessary skills and get a qualifying AZ-700 certificate.
Advanced Architecting on AWS training explores available AWS services and features as solutions to the problem. It helps you to gain insights by participating in problem-based discussions and learning about the AWS services that you could apply to meet the challenges. Over three days, this Advanced Architecting on AWS training goes beyond the basics of cloud infrastructure and covers topics to meet a variety of needs for AWS customers.
Course modules focus on managing multiple AWS accounts, hybrid connectivity, networking with a focus on AWS Transit Gateway connectivity, container services, automation tools for continuous integration/continuous delivery (CI/CD), security and distributed denial of service (DDoS) protection, data lakes and data stores, edge services, migration options, and managing costs. Advanced Architecting on AWS concludes by presenting you with scenarios and challenges to identify the best solutions. This course includes presentations, group discussions, use-cases, assessments, and hands-on labs.
This course demonstrates how to efficiently use AWS security services to stay secure in the AWS Cloud. The course focuses on the security practices that AWS recommends for enhancing the security of your data and systems in the cloud. It highlights the security features of AWS key services including compute, storage, networking, and database services. You will also learn how to leverage AWS services and tools for automation, continuous monitoring and logging, and responding to security incidents. This course includes presentations, demonstrations, and hands-on labs.
This DevOps Engineering on AWS course teaches candidates how to use the combination of DevOps cultural philosophies, practices, and tools to increase the organization’s ability to develop, deliver, and maintain applications and services at high velocity on AWS.
This DevOps Engineering on AWS course covers Continuous Integration (CI), Continuous Delivery (CD), infrastructure as code, microservices, monitoring and logging, and communication and collaboration. Hands-on labs give you experience building and deploying AWS CloudFormation templates and CI/CD pipelines that build and deploy applications on Amazon Elastic Compute Cloud (Amazon EC2), serverless applications, and container-based applications.
The DevOps Engineering on AWS course comprises presentations, group exercises, and hands-on labs. In addition, labs for multi-pipeline workflows and pipelines deployed to multiple environments are also included.
The course content usually covers the following key topics:
Introduction to AWS: Overview of the AWS platform, its global infrastructure, and key service domains.
AWS Architecture: Understanding the basic architectural principles of AWS, including regions, availability zones, and edge locations.
Compute Services: Overview of various compute services offered by AWS, such as Amazon Elastic Compute Cloud (EC2) and AWS Lambda.
Storage Services: Introduction to different storage services, including Amazon Simple Storage Service (S3), Amazon Elastic Block Store (EBS), and Amazon Glacier.
Networking and Content Delivery: Basic networking concepts within AWS, including Amazon Virtual Private Cloud (VPC), Route 53, and CloudFront.
Databases on AWS: Overview of database services provided by AWS, including Amazon Relational Database Service (RDS) and Amazon DynamoDB.
Security and Identity Services: Introduction to the security and identity services available on AWS, such as AWS Identity and Access Management (IAM) and AWS Key Management Service (KMS).
AWS Management Tools: Overview of various management and monitoring tools, including AWS CloudTrail, AWS CloudWatch, and AWS Trusted Advisor.
The course is intended to provide a broad overview of the AWS platform and its key services, enabling participants to understand the basic building blocks of cloud architecture and how to use various AWS services effectively. It serves as a starting point for individuals looking to gain a foundational understanding of AWS and prepare for more advanced AWS courses.
Networking Essentials for Cloud Applications on AWS
The Networking Essentials for Cloud Applications on AWS course delivers a thorough introduction to networking within the AWS cloud. Tailored for both new and experienced networking professionals, it explores core concepts, recommended practices, and hands-on exercises. The course is designed to develop the expertise required to effectively design, implement, and optimize AWS-based network infrastructures.
MB-800: Microsoft Dynamics 365 Business Central Functional Consultant
This Microsoft Dynamics 365 Business Central Functional Consultant training from CloudThat teaches candidates how to implement and configure the Dynamics 365 Business Central app, set up core app modules and functionality, and migrate data to Business Central. Candidates for the MB-800 exam also learn how to run the user interface in collaboration with the implementation team. They also learn how to configure role centers, including action tiles, adapt insights, cues, charts, and reports, and extend Business Central with the help of Microsoft Power Platform components.
Running Containers on Amazon Elastic Kubernetes Service (Amazon EKS) Training
In this course, you will learn how to use Amazon EKS to manage and orchestrate containers with Kubernetes. With Amazon EKS you can run Kubernetes on AWS without needing to install, operate, and maintain your own Kubernetes control plane. You will manage container images using Amazon Elastic Container Registry (Amazon ECR) and learn how to automate application deployment. You will deploy applications using continuous integration and delivery (CI/CD) tools. You will learn how to monitor and scale your environment by using metrics, logging, tracing, and horizontal and vertical scaling. You will also manage storage for your containerized applications, configure AWS networking services to support the cluster and learn how to secure your Amazon EKS environment.
Practical Data Science with Amazon SageMaker Training
In this Practical Data Science with Amazon Sagemaker certification training course, candidates learn to solve a real-world use case with Machine Learning (ML) using Amazon SageMaker. From analyzing and visualizing a dataset to preparing the data, and feature engineering, candidates taking up this Practical Data Science with Amazon Sagemaker course learn about the different stages of a typical data science process for Machine Learning.
By enrolling in this Practical Data Science with Amazon Sagemaker online course, candidates also learn about the practical aspects of model building, tuning, and deployment with Amazon SageMaker. Trainers use real-life use cases, group exercises, and hands-on labs to deliver engaging sessions on Amazon SageMaker.
The course content usually covers the following key topics:
Introduction to Serverless Computing: An overview of serverless architecture, its advantages, and its relevance in modern application development.
AWS Serverless Services: In-depth exploration of various AWS serverless services, including AWS Lambda, Amazon API Gateway, Amazon DynamoDB, Amazon S3, Amazon SNS, and Amazon SQS, along with their integration patterns.
Serverless Application Development with AWS Lambda: Practical guidance on writing, deploying, and managing AWS Lambda functions for executing code without the need to provision or manage servers.
Serverless Application Deployment Best Practices: Strategies for deploying serverless applications using AWS CloudFormation or other deployment tools to ensure scalability, security, and high availability.
Event-Driven Architectures: Implementation and understanding of event-driven architectures using AWS services, including how to trigger AWS Lambda functions in response to various events.
Serverless Application Security: Best practices for securing serverless applications, encompassing access control, encryption, and the implementation of security measures for data protection.
Monitoring and Debugging Serverless Applications: Techniques for monitoring and troubleshooting serverless applications using AWS CloudWatch, X-Ray, and other monitoring tools.
Best Practices and Optimization Techniques: Guidance on optimizing serverless applications, including performance tuning, cost optimization, and efficient resource management.
Real-World Use Cases: Exploration of real-world use cases and case studies that illustrate the practical application of serverless solutions on the AWS platform.
This course helps experienced developers build web applications by programmatically interacting with AWS services. It covers key architectural concepts, resource selection, and practical use of AWS SDKs and the CLI for development and deployment. You will create a sample application while learning to manage permissions, implement business logic, configure authentication, deploy to the cloud, and troubleshoot issues.
The course also includes code examples and hands-on labs using SDKs for Python, .NET, and Java, along with the AWS CLI and Management Console.
This course teaches the fundamentals and best practices for building a cloud-based data warehouse using Amazon Redshift. It covers how to collect, store, and process data efficiently while explaining Redshift’s features and its role in solving business and technical challenges. You will also learn solution design using the Well-Architected Framework, along with integration, performance optimization, orchestration, security, and monitoring.
Building Data Lakes on AWS helps learn how to build an operational data lake to analyze both structured and unstructured data. Taking up this training on building Data Lakes on AWS, candidates are trained to use the various components and features of AWS services to create a data lake.
This Building Data Lakes on AWS training teaches candidates how to use AWS Glue to build a data catalog, AWS Lake Formation to build a data lake, and Amazon Athena to analyze data. The course comprises presentations, lectures, hands-on labs, and group exercises.
MB-920: Microsoft Dynamics 365 Fundamentals Finance and Operations Apps (ERP)
NOTE: This course is no longer available and has been officially retired. As an alternative, you may consider MB-310 OR MB-330
This MB-920: Microsoft Dynamics 365 Finance and Operations Apps certification training course from CloudThat teaches candidates the capabilities and features of Microsoft Dynamics 365 Finance and Operations Apps. Earning this MB-920 certification helps candidates understand how business operations and finance teams can leverage the power of the Microsoft Dynamics 365 solution to achieve new levels of efficiency and effectiveness across the enterprise.
MB-910: Microsoft Dynamics 365 Fundamentals Customer Engagement Apps (CRM)
Note: This course is no longer available and has been officially retired. As an alternative, you may consider MB-230 or MB-280
This Microsoft Dynamics 365 Fundamentals Customer Engagement Apps (MB-910) certification training course from CloudThat is ideal for tech-savvy individuals having basic knowledge of business functions like sales, marketing, support lifecycles, and services. This exam MB-910 provides candidates fundamental understanding of customer engagement features and capabilities of Dynamics 365 apps.
Candidates taking up this MB-910 certification course are introduced to Dynamics 365 Sales, Dynamics 365 Marketing, Dynamics 365 Field Service, Dynamics 365 Customer Service, and shared features.
The DP-203: Data Engineering on Microsoft Azure course from CloudThat provides comprehensive training and study materials to help candidates prepare for the DP-203 certification exam. This course replaces the DP-200 and DP-201 exams, which retired on June 30, 2021.
Through this updated curriculum, learners gain the necessary skills to successfully clear the DP-203 exam and become certified Azure Data Engineers.
DP-100: Design & Implement Data Science Solution on Azure
The DP 100 certification provides you with the skills to implement machine learning solutions at cloud scale using Azure Machine Learning. This course is designed to integrate your existing Python and machine learning expertise, allowing you to effectively manage data ingestion and preparation, model training, deployment, and solution monitoring using Azure Machine Learning and MLflow.
This DP-900 certification course from CloudThat is designed to help candidates pass the Microsoft DP-900 certification exam. This DP-900 exam is ideal for candidates beginning to work with data in the Cloud. Candidates taking up this training learn about the core data concepts and related Microsoft Azure data services.
Before taking up this Microsoft Azure Data Fundamentals certification, candidates must be familiar with the relational and non-relational data concepts and the different types of data workloads, including transactional or analytical. Candidates can use the Azure Data Fundamentals certification to prepare for other Azure role-based certifications like Azure Data Engineer Associate or Azure Database Administrator Associate. However, it is not a prerequisite for any of them.
MB-300: Microsoft Dynamics 365 Core Finance and Operations
Note- This exam has retired on February 29, 2024. Please Reach out to us for an alternative to this course.
This Microsoft Dynamics 365 Core Finance and Operations (MB-300) certification training course from CloudThat teaches candidates how to implement core features and components of Dynamics 365 Finance and Operations apps to meet business requirements. They also learn how to use Azure DevOps, Lifecycle Services (LCS), Power Platform, and other Microsoft tools to streamline the application lifecycle management (ALM) process.
By taking up this Microsoft Dynamics MB-300 course, candidates will receive training from our in-house subject matter experts to successfully clear the exam. We also provide relevant study material necessary to pass the MB-300 certification exam to become a Microsoft-certified Dynamics 365 Functional Consultant with expertise in Core Finance and Operations.
At CloudThat, we have expert training consultants with years of experience and unique teaching methodologies. Our hands-on approach helps learners build practical skills, and our trainers are available to support the learners even after the course completion.
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