Python Security Training Course

This intensive, hands-on course delves into advanced Python techniques, engineering best practices, and widely used design patterns to help you build maintainable, testable, and high-performance Python applications. It places a strong emphasis on modern tooling, typing, concurrency models, architectural patterns, and deployment-ready workflows.

Delivered as instructor-led live training (available online or onsite), this program targets intermediate to advanced Python developers who aim to adopt professional practices and patterns for building production-grade Python systems.

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

• Enhance code reliability by applying Python typing, dataclasses, and type-checking.
• Structure robust applications using established design patterns and architectural principles.
• Correctly implement concurrency and parallelism through asyncio and multiprocessing.
• Develop well-tested code utilizing pytest, property-based testing, and CI pipelines.
• Profile, optimize, and harden Python applications for production environments.
• Package, distribute, and deploy Python projects using modern tools and containerization.

Course Format

• Interactive lectures and brief demonstrations.
• Hands-on labs and coding exercises conducted daily.
• A capstone mini-project that integrates patterns, testing, and deployment strategies.

Course Customization Options

• To request a customized training session or focus on a specific area such as data, web, or infrastructure, please contact us to arrange.

This course imparts practical engineering methodologies for designing, building, testing, and deploying agentic (autonomous) systems using Python. It encompasses the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and considerations for production environments.

Delivered as an instructor-led live training (available online or onsite), this program targets intermediate to advanced ML engineers, AI developers, and software engineers aiming to construct robust, production-ready autonomous agents utilizing Python.

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

• Design and implement the agent loop and decision-making workflows.
• Integrate external tools and APIs to expand agent capabilities.
• Implement short-term and long-term memory architectures for agents.
• Coordinate multi-step orchestrations and agent composability.
• Apply safety, access control, and observability best practices for deployed agents.

Course Format

• Interactive lectures and discussions.
• Hands-on labs focused on building agents with Python and popular SDKs.
• Project-based exercises resulting in deployable prototypes.

Course Customization Options

• To request customized training for this course, please contact us to arrange.

This is a 5-day introductory course covering Data Science and Artificial Intelligence (AI).

The course is delivered with examples and exercises using Python

Artificial Intelligence with Python focuses on creating intelligent systems leveraging Python’s comprehensive ecosystem of AI and machine learning libraries.

This instructor-led live training, available online or onsite, is designed for intermediate Python developers who aim to design, implement, and deploy AI solutions using Python.

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

• Implement AI algorithms using Python’s core AI libraries.
• Work with supervised, unsupervised, and reinforcement learning models.
• Integrate AI solutions into existing applications and workflows.
• Evaluate model performance and optimize for accuracy and efficiency.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led live training in the UAE (online or onsite) is designed for business analysts looking to automate trades using algorithmic trading, Python, and R.

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

• Utilize algorithms to rapidly buy and sell securities at specialized increments.
• Lower trade-related costs by leveraging algorithmic trading.
• Automatically monitor stock prices and execute trades.

This four-day course provides an introduction to Artificial Intelligence and its practical applications using the Python programming language. Upon completion, participants have the option to dedicate an additional day to working on a hands-on AI project.

This instructor-led live training in the UAE (online or on-site) is designed for intermediate-level Python developers seeking to enhance their development experience using AWS Cloud9.

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

• Set up and configure AWS Cloud9 for Python development.
• Understand the AWS Cloud9 IDE interface and features.
• Write, debug, and deploy Python applications in AWS Cloud9.
• Collaborate with other developers using the AWS Cloud9 platform.
• Integrate AWS Cloud9 with other AWS services for advanced deployments.

Chatbots are automated computer programs designed to simulate human interactions through chat interfaces. They assist organizations in enhancing operational efficiency by streamlining and accelerating user engagement.

This instructor-led live training will guide participants through the process of building chatbots using Python.

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

• Grasp the core principles of chatbot development
• Construct, test, deploy, and resolve issues for various types of chatbots using Python

Target Audience

• Software Developers

Course Format

• A blend of lectures, discussions, exercises, and extensive hands-on practice

Note

• For customized training options, please reach out to us to arrange.

This instructor-led, live training in the UAE (online or on-site) is targeted at intermediate-level developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs.

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

• Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
• Create, compile and launch custom CUDA kernels.
• Manage GPU memory.
• Convert a CPU based application into a GPU-accelerated application.

Course Overview

This practical training is tailored for professionals with a data engineering background who aim to develop hands-on expertise in artificial intelligence, Python, and large language models. The program emphasizes real-world applications, focusing on model utilization, prompt engineering, and the development of AI-driven solutions. Participants will engage in progressive exercises that transition from foundational concepts to the creation of deployable AI workflows.

Training Format

• In-person classroom instruction

• Instructor-led sessions featuring guided practice

• Interactive discussions and analysis of real-world case studies

• Daily practical exercises

Course Objectives

• Grasp core AI and machine learning concepts pertinent to modern applications

• Enhance Python proficiency for AI development and data workflows

• Comprehend the mechanics of large language models and learn to utilize them effectively

• Design and optimize prompts to ensure reliable outputs

• Construct end-to-end AI solutions using APIs and frameworks

• Integrate AI capabilities into data engineering pipelines

This instructor-led, live training in the UAE (online or onsite) is tailored for data scientists and software engineers who wish to leverage Dask within 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 the UAE (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, offered online or onsite, targets developers who wish to leverage 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 the UAE (online or onsite) is designed for developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs more efficiently and rapidly.

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

• Configure the essential development environment for API development with Python and FastAPI.
• Accelerate and simplify API creation using the FastAPI library.
• Master the creation of data models and schemas based on Pydantic and OpenAPI.
• Integrate APIs with databases via SQLAlchemy.
• Apply security measures and authentication mechanisms in APIs using FastAPI utilities.
• Construct container images and deploy web APIs to cloud servers.

This instructor-led, live training in the UAE (online or onsite) is designed for 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.