Whether delivered online or onsite, these instructor-led live Data Science courses provide hands-on experience in extracting meaningful insights from various data formats.
Data Science instruction is offered as either "online live training" or "onsite live training." Online live training (also known as "remote live training") is conducted through an interactive remote desktop session. Onsite live training can be hosted locally at your facilities in Prague or at NobleProg corporate training centers in Prague.
From Prague Main Train Station (Praha hlavní nádraží)
Take tram 9 from Hlavní nádraží toward Sídliště Řepy.
Get off at Újezd.
Walk about 10 minutes toward Malostranské náměstí / Prokopská.
Continue along Prokopská to 296/8.
Alternative: Take the metro C from Hlavní nádraží → Muzeum, change to metro A → Malostranská, then walk across Malá Strana. This involves more walking.
From Prague Bus Station — Florenc
Take metro B from Florenc toward Zličín.
Get off at Můstek.
Change to metro A toward Nemocnice Motol.
Get off at Malostranská.
Walk approximately 10–15 minutes to Prokopská 296/8.
This instructor-led, live training in Prague (online or on-site) is designed for beginner-level professionals who aim to grasp the concept of pre-trained models and learn how to apply them to solve real-world problems without the need to build models from the ground up.
Upon completion of this training, participants will be able to:
Comprehend the concept and advantages of pre-trained models.
Examine various pre-trained model architectures and their specific use cases.
Fine-tune a pre-trained model for designated tasks.
Implement pre-trained models in straightforward machine learning projects.
This instructor-led, live training in Prague (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 Prague (online or onsite) is designed for intermediate-level participants seeking 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 for orchestrating machine learning workflows.
Automate tasks related to 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 a production environment.
This instructor-led, live training session in Prague (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:
This 35-hour instructor-led course in Prague empowers participants to harness Python for developing practical financial applications. It encompasses data analysis, asset allocation, and risk management through an immersive, hands-on methodology that integrates lectures with rigorous practical exercises.
This 35-hour course Prague focuses on applying Data Science and AI using Python. Participants will learn CRISP-DM workflows, machine learning with TensorFlow, NLP, and Big Data processing with Spark. It is designed for beginners looking to gain professional analytics skills and a Python data science certification for business applications.
This instructor-led training introduces Prague using KNIME Analytics Platform for data-driven innovation. Participants will learn to construct data science scenarios, train and validate models, and implement end-to-end data value chains through hands-on labs and practical exercises.
This instructor-led, live training in Prague (online or onsite) is aimed at intermediate-level data analysts, developers, or 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.
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Testimonials (2)
Hands-on exercises related to content really helps to understand more about each topic. Also, style of start class with lecture and continue with hands-on exercise is good and helpful to relate with the lecture that presented earlier.
Nazeera Mohamad - Ministry of Science, Technology and Innovation
Course - Introduction to Data Science and AI using Python
Even with having to miss a day due to customer meetings, I feel I have a much clearer understanding of the processes and techniques used in Machine Learning and when I would use one approach over another. Our challenge now is to practice what we have learned and start to apply it to our problem domain
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