Python for Matlab Users Training Course

This intensive, hands-on course delves into advanced Python techniques, best engineering practices, and commonly used design patterns to create maintainable, testable, and high-performance Python applications. It emphasizes modern tools, typing, concurrency models, architectural patterns, and deployment-ready workflows.

This instructor-led, live training (online or on-site) is designed for intermediate to advanced Python developers who wish to adopt professional practices and patterns for production-grade Python systems.

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

• Apply Python typing, dataclasses, and type-checking to enhance code reliability.
• Use design patterns and architectural principles to build robust applications.
• Implement concurrency and parallelism effectively using asyncio and multiprocessing.
• Develop well-tested code with pytest, property-based testing, and CI pipelines.
• Profile, optimize, and secure Python applications for production.
• Package, distribute, and deploy Python projects using modern tools and containers.

Format of the Course

• Interactive lectures and short demonstrations.
• Hands-on labs and coding exercises each day.
• A capstone mini-project integrating patterns, testing, and deployment.

Course Customization Options

• To request a customized training or to focus on specific areas (data, web, or infrastructure), please contact us to arrange.

This course provides practical engineering techniques for designing, building, testing, and deploying autonomous systems using Python. It covers the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced ML engineers, AI developers, and software engineers who want to build robust, production-ready autonomous agents using Python.

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

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

Format of the Course

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

Course Customization Options

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

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

The course includes practical examples and exercises using Python.

Artificial Intelligence with Python involves developing intelligent systems by leveraging Python’s rich ecosystem of AI and machine learning libraries.

This instructor-led, live training (available online or on-site) is designed for intermediate-level Python programmers who want to design, implement, and deploy AI solutions using Python.

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

• Implement AI algorithms utilizing 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 lectures and discussions.
• Plenty of exercises and practice sessions.
• 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 Uzbekistan (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.

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

• Employ algorithms to buy and sell securities at specialized increments rapidly.
• Reduce costs associated with trade using algorithmic trading.
• Automatically monitor stock prices and place trades.

This is a four-day course that introduces artificial intelligence (AI) and its applications using the Python programming language. An optional extra day is available for participants to work on an AI project after completing the course.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at intermediate-level Python developers who wish to enhance their Python 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.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at beginner-level to intermediate-level developers who wish to use Python to build blockchain and cryptocurrency applications.

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

• Use Python to create and manipulate blockchain and cryptocurrency systems and data.
• Use Python libraries and frameworks such as Flask, PyCrypto, and web3.py to interact with blockchain and cryptocurrency networks and services.
• Use Python to implement smart contracts, consensus algorithms, and cryptographic protocols for blockchain and cryptocurrency applications.
• Use Python to develop and deploy decentralized applications (DApps) that run on blockchain and cryptocurrency platforms.
• Use Python to perform data analysis and visualization on blockchain and cryptocurrency data.

ChatBots are computer programs designed to automatically mimic human responses through chat interfaces. These programs enhance organizational efficiency by offering users faster and more convenient interaction options.

In this instructor-led, live training, participants will learn how to develop chatbots using Python.

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

• Grasp the foundational concepts of building chatbots
• Create, test, deploy, and troubleshoot various chatbots using Python

Audience

• Developers

Format of the course

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

Note

• For a customized training session for this course, please contact us to arrange.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed 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.

This instructor-led, live training in Uzbekistan (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 Uzbekistan (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 Uzbekistan (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 Uzbekistan (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.