AWS Cloud9 for Data Science Training Course

This instructor-led, live training in US (online or onsite) is designed for intermediate-level professionals who require the ability to automate and manage machine learning workflows, including model training, validation, and deployment, using Apache Airflow.

Upon completion of this training, participants will be prepared to:

• Configure Apache Airflow for machine learning workflow orchestration.
• Automate data preprocessing, model training, and validation tasks.
• Integrate Airflow with machine learning frameworks and tools.
• Deploy machine learning models using automated pipelines.
• Monitor and optimize machine learning workflows in production environments.

This instructor-led, live training in US (available online or onsite) is intended for system administrators and IT professionals at beginner to intermediate levels who aim to obtain practical experience in managing AWS cloud services and preparing for the AWS Certified SysOps Administrator – Associate examination.

Upon completion of this training, participants will be prepared to:

• Establish and configure AWS services and resources with secure protocols.
• Administer user identities, permissions, and access controls for AWS resources.
• Architect and deploy scalable, highly available, and fault-tolerant systems within AWS.
• Implement and oversee data ingress and egress to and from AWS environments.
• Optimize the utilization of AWS services to guarantee operational efficiency and fiscal responsibility.

This instructor-led, live training in US (delivered on-site or remotely) is designed for engineering professionals seeking to deploy and manage IoT devices on the AWS cloud platform for government use.

Upon completion, participants will be equipped to develop an IoT platform encompassing the deployment and management of backend infrastructure, gateways, and devices within the AWS environment.

This instructor-led, live training session in US (delivered on-site or remotely) is tailored for technical personnel seeking to utilize AWS Lambda for the development and deployment of cloud services for government applications. The program eliminates the need for manual provisioning of execution environments, such as servers, virtual machines, containers, and associated infrastructure management tasks.

Upon completion, participants will be able to:

• Configure AWS Lambda to execute defined functional tasks.
• Understand the Functions as a Service (FaaS) paradigm and the strategic advantages of serverless development.
• Develop, upload, and execute AWS Lambda functions effectively.
• Integrate Lambda functions with a variety of event-driven sources.
• Package, deploy, monitor, and troubleshoot applications built on Lambda infrastructure.

This instructor-led live training in US (delivered online or in-person) is designed for beginner-level data scientists and information technology professionals seeking to acquire foundational data science skills using Google Colab.

Upon completion of this training, participants will be proficient in:

• Configuring and navigating Google Colab.
• Authoring and executing fundamental Python code.
• Importing and managing datasets.
• Generating visualizations using Python libraries.

This course provides an ideal introduction to data science for managers, equipping them with the knowledge to utilize this powerful tool for government operations.

This instructor-led, live training in US (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of DevOps practices and streamline development processes using AWS Cloud9.

By the end of this training, participants will be able to:

• Set up and configure AWS Cloud9 for DevOps workflows.
• Implement continuous integration and continuous delivery (CI/CD) pipelines.
• Automate testing, monitoring, and deployment processes using AWS Cloud9.
• Integrate AWS services such as Lambda, EC2, and S3 into DevOps workflows.
• Utilize source control systems like GitHub or GitLab within AWS Cloud9.

This instructor-led, live training in US (online or onsite) is targeted at intermediate-level professionals seeking to effectively build, deploy, and maintain serverless applications on AWS Cloud9 and AWS Lambda.

Upon completion of this training, participants will be capable of:

• Understanding the fundamental concepts of serverless architecture.
• Configuring AWS Cloud9 for serverless application development.
• Developing, testing, and deploying serverless applications using AWS Lambda.
• Integrating AWS Lambda with other AWS services such as API Gateway and S3.
• Optimizing serverless applications for performance and cost efficiency.

KNIME Analytics Platform serves as a premier open-source solution for data-driven governance and innovation. It enables organizations to uncover latent potential within datasets, derive actionable insights, and forecast future trends. With over 1,000 integrated modules, extensive ready-to-use examples, a robust suite of tools, and a comprehensive selection of advanced algorithms, the platform provides a versatile toolkit for data scientists and business analysts working for government.

This training course for KNIME Analytics Platform is designed as an optimal learning opportunity for beginners, advanced users, and experts alike. It introduces the platform, enhances operational effectiveness, and instructs participants on generating clear, comprehensive reports based on KNIME workflows.

This instructor-led, live training (available online or onsite) is tailored for data professionals seeking to leverage KNIME to address complex operational requirements for government.

The program targets audiences without prior programming experience who intend to utilize advanced tools to implement analytics scenarios.

Upon completion of this training, participants will be capable of:

• Installing and configuring KNIME.
• Constructing data science scenarios.
• Training, testing, and validating analytical models.
• Implementing the end-to-end value chain of data science models.

Course Format

• Interactive lectures and facilitated discussions.
• Extensive exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request customized training for this course or to obtain further details on this program, please contact us to arrange.

This instructor-led, live training module in US (delivered online or onsite) targets intermediate-level data analysts, developers, or emerging data scientists aiming to apply Python-based machine learning techniques to derive insights, generate forecasts, and automate data-driven decisions for government.

Upon completion of this course, participants will be capable of:

• Differentiating and applying core machine learning paradigms.
• Implementing data preprocessing techniques and interpreting model evaluation metrics.
• Deploying machine learning algorithms to resolve complex, real-world data challenges.
• Utilizing Python libraries and Jupyter notebooks for practical development tasks.
• Constructing models for prediction, classification, recommendation, and clustering tasks.

This instructor-led, live training conducted in US (online or onsite) is intended to assist participants in preparing for the Microsoft Certified: Data Scientist Associate certification examination (DP-100), supporting professional development for government applications.

The curriculum outlines core principles of data science and machine learning, emphasizing their practical implementation using Microsoft Azure Machine Learning. Participants will gain proficiency in data preparation, the development and training of machine learning models, and cloud-based deployment. The training also addresses performance evaluation and feature engineering to ensure robust analytical outcomes.

This instructor-led live training, conducted in US (online or onsite), is intended for entry-level professionals aiming to understand the application of pre-trained models to address real-world challenges without building models from the ground up.

Upon completion of this training, participants will be able to:

• Comprehend the definition and operational benefits of pre-trained models.
• Examine various architectural designs and their applicable use cases.
• Perform fine-tuning of pre-trained models for designated tasks.
• Deploy pre-trained models within basic machine learning initiatives.