Python in Data Science Training Course

This five-day program provides an introductory overview of Data Science and Artificial Intelligence (AI).

The course is delivered through practical examples and exercises using Python.

This instructor-led, live training in Turkey (online or onsite) targets 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:

• Set up 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.

This instructor-led live training, held in Turkey (online or onsite), is designed for data scientists who aim to utilize the Anaconda ecosystem to capture, manage, and deploy packages and data analysis workflows in a consolidated 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 Turkey (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 Turkey (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 Turkey (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 Turkey (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.

Upon completing this training, participants will develop a practical, real-world grasp of Data Science, including its associated technologies, methodologies, and tools.

Learners will apply this knowledge through interactive, hands-on exercises. The course places significant emphasis on group collaboration and feedback from the instructor.

The curriculum begins by introducing fundamental Data Science concepts, then advances to explore the specific tools and methodologies employed in the field.

Audience

• Developers
• Technical analysts
• IT consultants

Course Format

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

Note

• For customized training options, please contact us to arrange your schedule.

Big data refers to data sets so vast and complex that conventional data processing software falls short. Key challenges in big data encompass data capture, storage, analysis, searching, sharing, transfer, visualization, querying, updating, and ensuring information privacy.

This instructor-led live training, offered online or onsite, targets developers who want to utilize the FARM stack (FastAPI, React, and MongoDB) to build dynamic, high-performance, and scalable web applications.

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

• Configure the necessary development environment integrating 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 Turkey (online or onsite) is targeted at developers who want to utilize FastAPI with Python to build, test, and deploy RESTful APIs with greater speed and ease.

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

• Configure the necessary development environment for developing APIs with Python and FastAPI.
• Create APIs more quickly and 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 the FastAPI tools.
• Build container images and deploy web APIs to a cloud server.

This instructor-led live training in Turkey (online or on-site) is designed for data scientists and developers who wish to launch or grow 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 principles.
• Perform data analytics exploration.
• Understand the functionalities and operations of Kaggle.

This instructor-led, live training in Turkey (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.

This instructor-led, live training in Turkey (online or onsite) is designed for data scientists and developers who want to use RAPIDS to build GPU-accelerated data pipelines, workflows, and visualizations, while applying machine learning algorithms such as XGBoost, cuML, and others.

Upon completing this training, participants will be able to:

• Configure the required development environment to create data models using NVIDIA RAPIDS.
• Comprehend the features, components, and benefits of RAPIDS.
• Utilize GPUs to speed up end-to-end data and analytics pipelines.
• Execute GPU-accelerated data preparation and ETL processes with cuDF and Apache Arrow.
• Perform machine learning tasks using XGBoost and cuML algorithms.
• Create data visualizations and conduct graph analysis with cuXfilter and cuGraph.