Data Science Training in Belgrade

This instructor-led, live training in Belgrade (online or onsite) is aimed at beginner-level professionals who wish to understand the concept of pre-trained models and learn how to apply them to solve real-world problems without building models from scratch.

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

• Understand the concept and benefits of pre-trained models.
• Explore various pre-trained model architectures and their use cases.
• Fine-tune a pre-trained model for specific tasks.
• Implement pre-trained models in simple machine learning projects.

This instructor-led, live training in Belgrade (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 Belgrade (online or onsite) is aimed at 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 in Belgrade (online or on-site) is designed to help participants prepare for the Microsoft Certified: Data Scientist Associate certification exam (DP-100).

The course covers the basics of data science and machine learning, and how they can be implemented using Microsoft Azure Machine Learning. Participants will learn how to prepare data, build and train machine learning models, and deploy models to the cloud. The course also covers how to evaluate model performance and perform feature engineering.

This instructor-led live training in Belgrade (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 Belgrade (available online or onsite) targets data scientists and developers who aspire to learn and build their careers in Data Science using Kaggle.

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

• Learn about data science and machine learning.
• Explore data analytics.
• Learn about Kaggle and how it works.

Python has become increasingly popular within the financial sector. Widely adopted by major investment banks and hedge funds, it is utilized to develop a broad spectrum of financial applications, from core trading systems to risk management solutions.

Through this instructor-led live training, participants will learn how to leverage Python to create practical applications that address specific finance-related challenges.

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

• Grasp the fundamental concepts of the Python programming language
• Download, install, and manage the optimal development tools for building financial applications in Python
• Select and employ the most appropriate Python packages and programming techniques to organize, visualize, and analyze financial data from diverse sources (such as CSV, Excel, databases, and web APIs)
• Develop applications that solve issues related to asset allocation, risk analysis, investment performance, and other areas
• Troubleshoot, integrate, deploy, and optimize Python applications

Audience

• Developers
• Analysts
• Quants

Format of the course

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

Note

• This training focuses on providing solutions to key challenges faced by finance professionals. If there is a specific topic, tool, or technique you wish to add or explore in greater depth, please contact us to arrange for customization.

Explores practical methodologies for Data Science and AI leveraging Python. It equips professionals with the capabilities to analyze data, construct machine learning models, and implement AI-driven applications within business settings. The curriculum encompasses CRISP-DM workflows, statistical analysis, supervised and unsupervised learning, deep learning via TensorFlow, natural language processing, big data processing with Spark, and data-driven storytelling. This course is ideal for beginners aiming for a Python data science certification and career-ready analytics training.

This instructor-led live training in Belgrade (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 course is an ideal introduction to data science for managers, providing an opportunity to learn about this powerful business instrument.

KNIME Analytics Platform stands out as a premier open-source solution for data-driven innovation. It empowers users to uncover the hidden potential within their data, extract fresh insights, and predict future trends. Boasting over 1,000 modules, numerous ready-to-run examples, a comprehensive suite of integrated tools, and the broadest selection of advanced algorithms, KNIME Analytics Platform serves as the ideal toolbox for any data scientist or business analyst.

This course offers beginners, advanced users, and KNIME experts alike an excellent opportunity to become familiar with KNIME, enhance their proficiency in using it, and learn how to generate clear, comprehensive reports based on KNIME workflows.

This instructor-led live training, available either online or onsite, is designed for data professionals seeking to leverage KNIME to address complex business challenges.

The program is specifically tailored for individuals who may not have a programming background but wish to utilize state-of-the-art tools to implement analytics scenarios.

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

• Install and configure KNIME.
• Develop Data Science scenarios.
• Train, test, and validate models.
• Implement the end-to-end value chain of data science models.

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practical application.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• For customized training requests or further information about this program, please contact us to arrange.

This instructor-led, live training in Belgrade (online or onsite) is designed for intermediate-level data analysts, developers, and aspiring data scientists who wish to apply machine learning techniques in Python to extract insights, make predictions, and automate data-driven decisions.

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

• Understand and differentiate key machine learning paradigms.
• Explore data preprocessing techniques and model evaluation metrics.
• Apply machine learning algorithms to solve real-world data problems.
• Use Python libraries and Jupyter notebooks for hands-on development.
• Build models for prediction, classification, recommendation, and clustering.

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

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

• Set up the necessary development environment to build data models with NVIDIA RAPIDS.
• Understand the features, components, and advantages of RAPIDS.
• Leverage GPUs to accelerate end-to-end data and analytics pipelines.
• Implement GPU-accelerated data preparation and ETL with cuDF and Apache Arrow.
• Learn how to perform machine learning tasks with XGBoost and cuML algorithms.
• Build data visualizations and execute graph analysis with cuXfilter and cuGraph.