Python Programming Fundamentals using Google Colab Training Course

This instructor-led, live training in Lithuania (online or onsite) is aimed at cloud engineers and developers who wish to use CloudFormation to manage infrastructure resources within the AWS ecosystem.

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

• Implement CloudFormation templates to automate infrastructure management.
• Integrate existing AWS resources into CloudFormation.
• Use StackSets to manage stacks across multiple accounts and regions.

This instructor-led, live training in Lithuania (online or onsite) is aimed at developers who wish to integrate a DynamoDB NoSQL database into a web application hosted on AWS.

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

• Set up the necessary development environment to start integrating data into DynamoDB.
• Integrate DynamoDB into web applications and mobile applications.
• Move data in AWS with AWS services.
• Implement operations with AWS DAX.

This instructor-led, live training in Lithuania (onsite or remote) is aimed at engineers who wish to deploy and manage IoT devices on AWS.

By the end of this training, participants will be able to build an IoT platform that includes the deployment and management of a backend, gateway, and devices on top of AWS.

This instructor-led, live training in Lithuania (online or onsite) is aimed at developers who wish to learn how to build microservices on Microsoft Azure Service Fabric (ASF).

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

• Use ASF as a platform for building and managing microservices.
• Understand key microservices programming concepts and models.
• Create a cluster in Azure.
• Deploy microservices on premises or in the cloud.
• Debug and troubleshoot a live microservice application.

This instructor-led, live training in Lithuania (online or onsite) is aimed at engineers who wish to use AWS CloudFormation to automate the process of managing AWS cloud infrastructure.

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

• Enable AWS services to get started managing infrastructure.
• Understand and apply the principle of "infrastructure as code".
• Improve quality and lower the costs of deploying infrastructure.
• Write AWS CloudFormation Templates using YAML.

This instructor-led, live training in Lithuania (online or onsite) is aimed at data scientists and software engineers who wish to use Dask with the Python ecosystem to build, scale, and analyze large datasets.

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

• Set up the environment to start building big data processing with Dask and Python.
• Explore the features, libraries, tools, and APIs available in Dask.
• Understand how Dask accelerates parallel computing in Python.
• Learn how to scale the Python ecosystem (Numpy, SciPy, and Pandas) using Dask.
• Optimize the Dask environment to maintain high performance in handling large datasets.

This instructor-led, live training in Lithuania (online or onsite) is aimed at intermediate-level Python developers and data analysts who wish to enhance their skills in data analysis and manipulation using Pandas and NumPy.

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

• Set up a development environment that includes Python, Pandas, and NumPy.
• Create a data analysis application using Pandas and NumPy.
• Perform advanced data wrangling, sorting, and filtering operations.
• Conduct aggregate operations and analyze time series data.
• Visualize data using Matplotlib and other visualization libraries.
• Debug and optimize their data analysis code.

This instructor-led, live training in (online or onsite) is aimed at developers who wish to use the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.

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

• Set up the necessary development environment that integrates FastAPI, React, and MongoDB.
• Understand the key concepts, features, and benefits of the FARM stack.
• Learn how to build REST APIs with FastAPI.
• Learn how to design interactive applications with React.
• Develop, test, and deploy applications (front end and back end) using the FARM stack.

This instructor-led, live training in Lithuania (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs easier and faster.

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

• Set up the necessary development environment to develop APIs with Python and FastAPI.
• Create APIs quicker and easier using the FastAPI library.
• Learn how to create data models and schemas based on Pydantic and OpenAPI.
• Connect APIs to a database using SQLAlchemy.
• Implement security and authentication in APIs using the FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

This instructor-led, live training in Lithuania (online or onsite) is aimed at programmers and developers who wish to use Fn in creating serverless applications and services.

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

• Set up Fn to create directories and functions.
• Create applications using different programming languages.
• Monitor functions to resolve issues at the development and deployment stages.

This instructor-led, live training in Lithuania (online or onsite) is aimed at data scientists and developers who wish to use Modin to build and implement parallel computations with Pandas for faster data analysis.

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

• Set up the necessary environment to start developing Pandas workflows at scale with Modin.
• Understand the features, architecture, and advantages of Modin.
• Know the differences between Modin, Dask, and Ray.
• Perform Pandas operations faster with Modin.
• Implement the entire Pandas API and functions.

This instructor-led, live training in Lithuania (onsite or remote) is aimed at developers who wish to use OpenFaas to create, build, test, debug and deploy event-driven functions without needing to worry about managing the underlying server infrastructure.

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

• Install and configure OpenFaas.
• Package any binary or code as a serverless function without repetitive boiler-plate coding.
• Decouple from AWS Lambda to avoid lock-in.
• Deploy event-driven functions to an on-premise server or to the cloud.

This instructor-led, live training in Lithuania (online or onsite) is aimed at software engineers who wish to develop parallel applications using OpenMP.

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

• Understand and use parallel programming with Fortran in OpenMP.
• Calculate fractals in parallel to render multiple pixels and characters.
• Implement vector programming with SIMD extensions for HPC systems.
• Add parallel blocks for specifying shared memory parallelism.

This instructor-led, live training in Lithuania (onsite or remote) is aimed at developers who wish to use Serverless Framework on AWS and other cloud platforms to create and deploy microservice applications.

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

• Set up Serverless Framework to work with compute services such as AWS Lambda.
• Reduce the complexity and cost of deploying microservices on different cloud platforms.
• Emit and capture events and execute functions automatically.

This instructor-led, live training in Lithuania (online or onsite) is aimed at developers and DevOps engineers who wish to utilize a serverless approach for building enterprise applications in Kubernetes.

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

• Setup and configure the Kubernetes system to start developing with a serverless architecture.
• Understand the concepts and principles foundational to serverless environments.
• Operate toolchains necessary to serverless development and integrate it with Kubernetes components.
• Practice their skill in Python programming language and apply it to implement  serverless systems.
• Secure enterprise applications that are deployed through a serverless framework on Kubernetes.
• Utilize modern cloud computing methods in optimizing DevOps task processing workflows.