Python in Data Science Training Course

This five-day course provides an introduction to Data Science and Artificial Intelligence (AI).

Instruction is delivered through practical examples and exercises using Python.

This instructor-led, live training in Uzbekistan (available online or on-site) is designed for intermediate-level participants who wish to automate and manage machine learning workflows, including model training, validation, and deployment, using Apache Airflow.

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

• Configure Apache Airflow to orchestrate machine learning workflows.
• Automate tasks such as data preprocessing, model training, and validation.
• Integrate Airflow with various machine learning frameworks and tools.
• Deploy machine learning models through automated pipelines.
• Monitor and optimize machine learning workflows in production environments.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at data scientists who wish to use the Anaconda ecosystem to capture, manage, and deploy packages and data analysis workflows in a single platform.

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

• Install and configure Anaconda components and libraries.
• Understand the core concepts, features, and benefits of Anaconda.
• Manage packages, environments, and channels using Anaconda Navigator.
• Use Conda, R, and Python packages for data science and machine learning.
• Get to know some practical use cases and techniques for managing multiple data environments.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at intermediate-level data scientists and analysts who wish to use AWS Cloud9 for streamlined data science workflows.

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

• Set up a data science environment in AWS Cloud9.
• Perform data analysis using Python, R, and Jupyter Notebook in Cloud9.
• Integrate AWS Cloud9 with AWS data services like S3, RDS, and Redshift.
• Utilize AWS Cloud9 for machine learning model development and deployment.
• Optimize cloud-based workflows for data analysis and processing.

This instructor-led, live training in Uzbekistan (online or onsite) is aimed at beginner-level data scientists and IT professionals who wish to learn the basics of data science using Google Colab.

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

• Set up and navigate Google Colab.
• Write and execute basic Python code.
• Import and handle datasets.
• Create visualizations using Python libraries.

This instructor-led, live training in Uzbekistan (available online or on-site) is designed for data scientists and software engineers who wish to use 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 begin building big data processing solutions using 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 (including Numpy, SciPy, and Pandas) using Dask.
• Optimize the Dask environment to ensure high performance when handling large datasets.

This instructor-led, live training in Uzbekistan (online or on-site) is designed for intermediate-level Python developers and data analysts who aim to strengthen 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 analyse time series data.
• Visualise data using Matplotlib and other visualisation libraries.
• Debug and optimise their data analysis code.

This is an ideal introduction to data science for managers, giving you the chance to learn about this powerful business tool.

This training equips participants with a hands-on, real-world understanding of Data Science, its methodologies, tools, and related technologies.

Through practical exercises, participants will apply their knowledge, supported by group discussions and instructor feedback, which are integral to the learning experience.

The course begins with foundational Data Science concepts and gradually explores the tools and techniques used in the field.

Audience

• Developers
• Technical analysts
• IT consultants

Format of the Course

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

Note

• For customized training options, please contact us to make arrangements.

This instructor-led live training, offered online or on-site, targets developers aiming to leverage the FARM (FastAPI, React, and MongoDB) stack for building dynamic, high-performance, and scalable web applications.

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

• Set up a 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 on-site) is designed for developers who want to use FastAPI with Python to build, test, and deploy RESTful APIs more efficiently and quickly.

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

• Set up the required development environment for building APIs with Python and FastAPI.
• Create APIs faster and more easily 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 FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

This instructor-led, live training in Uzbekistan (available online or on-site) is tailored for data scientists and developers who aim to learn and advance their careers in Data Science using Kaggle.

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

• Gain a solid understanding of data science and machine learning.
• Explore key concepts in data analytics.
• Learn about Kaggle and how it operates.

This instructor-led, live training in Uzbekistan (available online or on-site) is tailored for data scientists and developers who wish to utilize Modin to build and implement parallel computations with Pandas, thereby achieving faster data analysis.

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

• Set up the necessary environment to begin developing scalable Pandas workflows with Modin.
• Understand the features, architecture, and advantages of Modin.
• Distinguish between Modin, Dask, and Ray.
• Execute Pandas operations more rapidly using Modin.
• Implement the full Pandas API and its functions.

This instructor-led, live training in Uzbekistan (available online or on-site) is intended for data scientists and developers who wish to leverage RAPIDS to build GPU-accelerated data pipelines, workflows, and visualisations, applying machine learning algorithms such as XGBoost, cuML, and others.

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

• Set up the required development environment to build data models using NVIDIA RAPIDS.
• Understand the key features, components, and advantages of the RAPIDS framework.
• Harness the power of GPUs to accelerate end-to-end data and analytics pipelines.
• Implement GPU-accelerated data preparation and ETL processes using cuDF and Apache Arrow.
• Learn how to carry out machine learning tasks using XGBoost and cuML algorithms.
• Create data visualisations and perform graph analysis using cuXfilter and cuGraph.