Practical Quantum Computing Training Course

This is a 5 day introduction to Data Science and Artificial Intelligence (AI).

The course is delivered with examples and exercises using Python 

This instructor-led, live training in Brazil (online or onsite) is aimed at advanced-level professionals who wish to leverage quantum computing to enhance AI capabilities.

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

• Understand hybrid AI-quantum systems and their potential applications.
• Implement quantum machine learning algorithms.
• Optimize AI models using quantum computing resources.
• Overcome challenges in scaling and integrating quantum AI systems.

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

In this instructor-led, live training in Brazil, participants will learn the fundamentals of quantum computing as they step through the development of algorithms targeting quantum computers.

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

• Set up the necessary development environment to start creating quantum circuits.
• Control gate behavior using the gate's native counterpart.
• Improve on quibit inaccuracies using Cirq.
• Write and execute a quantum circuit to run against a NISQ based quantum computer simulator.

This instructor-led, live training in Brazil (online or onsite) is aimed at beginner-level participants who wish to understand the fundamentals of quantum computing, explore Google Willow’s capabilities, and learn how to get started with quantum programming.

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

• Understand the principles of quantum computing and qubits.
• Explore Google Willow and its advancements in quantum error correction.
• Write and execute basic quantum programs using Qiskit.
• Identify real-world applications of quantum computing.

This instructor-led, live training in Brazil (online or onsite) is aimed at data scientists and developers who wish 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.

This instructor-led, live training in Brazil (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.

This instructor-led, live training in Brazil (online or onsite) is aimed at developers who wish to learn about ProjectQ and how to utilize it for implementing quantum programs.

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

• Learn what is ProjectQ and what it is used for.
• Use the ProjectQ framework to perform quantum programming.
• Translate quantum programs to any back-end.

This instructor-led, live training in Brazil (online or onsite) is aimed at computer scientists and engineers who wish to understand the principles behind quantum computing and utilize them in developing algorithms for quantum computer implementations.

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

• Comprehend the fundamentals of quantum computing.
• Understand and apply quantum physics concepts into computational methods.
• Create algorithms for quantum computers.
• Solve computational problems efficiently with quantum computers.
• Integrate quantum behaviors into existing computational models.
• Perceive the potential of quantum computing in the advancement of other technologies.

This instructor-led, live training in Brazil (online or onsite) is aimed at beginner-level to intermediate-level AI professionals and AI researchers who wish to understand the fundamentals of Quantum AI and its potential applications.

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

• Grasp the basic principles of quantum mechanics as they apply to quantum computing.
• Understand the workings of quantum algorithms and their implementation.
• Recognize the potential of Quantum AI in revolutionizing various industries.
• Develop a foundational quantum machine learning model.
• Evaluate the challenges and ethical considerations of Quantum AI.

This instructor-led, live training in Brazil (online or onsite) is aimed at beginner-level to intermediate-level business and technology leaders who wish to understand the fundamentals of quantum computing and its potential impact on industries such as cryptography, logistics and financial modeling, and learn how quantum computing could be applied within their sectors.

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

• Understand the fundamental principles of quantum computing, including qubits and quantum entanglement.
• Identify potential applications of quantum computing in cryptography, logistics, and financial modeling.
• Gain insight into the current limitations and future developments of quantum technology.
• Recognize the basics of quantum algorithms and their impact on business challenges.

In this instructor-led, live training in Brazil, participants will learn the fundamentals of quantum computing and Q# as they step through the development of simple quantum programs.

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

• Install and configure Microsoft's Quantum Development Kit.
• Understand the concepts behind quantum computing.
• Build, test, execute, and troubleshoot a quantum program using Q#, Visual Studio and a local quantum computing simulator.

This instructor-led, live training in Brazil (online or onsite) is aimed at computer scientists who wish to create, edit, and invoke a quantum circuit using IBM Quantum Experience.

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

• Set up the necessary development environment to start creating quantum circuits.
• Improve on inaccuracies in quibits using IBM Quantum Experience and its simulations.
• Control gate behavior using the gate's native counterpart.
• Schedule the time of gate events.

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

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.