Python Programming for Financeのトレーニングコース

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

This instructor-led, live training in (online or onsite) is aimed at developers who wish to use the FARM (FastAPI, React, and MongoDB) stack to build dynamic, high-performance, and scalable web applications.

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

• Set up the necessary 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 日本 (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs easier and faster.

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

• Set up the necessary development environment to develop APIs with Python and FastAPI.
• Create APIs quicker and easier 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 日本 (online or onsite) is aimed at cloud administrators, cloud architects, technology heads, and financial analysts who wish to record, manage, monitor, and process financial assets of an organization in the cloud.

By the end of this training, participants will be able to use FinOps practices in an organization to forecast costs, optimize processes, and perform financial management operations in the cloud.

This instructor-led, live training in 日本 (online or onsite) is aimed at intermediate-level finance professionals who wish to gain a comprehensive knowledge of FinOps principles and methodologies, including cloud financial management, optimization strategies, and collaboration among finance, engineering, and business teams.

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

• Understand the FinOps framework, principles, and phases.
• Manage cloud costs effectively through data analysis and governance.
• Collaborate between finance, engineering, and business units to align cloud spend.
• Use FinOps tools for cost allocation, forecasting, and optimization.
• Prepare for the FinOps Certified FOCUS Analyst exam.

This instructor-led, live training in 日本 (online or onsite) is aimed at advanced-level cloud financial management professionals who wish to validate their expertise in financial operations (FinOps) related to cloud cost management.

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

• Gain advanced knowledge required for the FinOps Certified Professional exam.
• Understand complex FinOps practices, including cost optimization, budget management, and reporting.
• Develop practical skills in applying FinOps strategies in real-world scenarios.
• Prepare for a successful completion of the FinOps Certified Professional exam.

In this instructor-led, live training in 日本, participants will learn how to use GnuCash to manage business accounting and finance projects and tasks.

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

• Manage financial and accounting tasks including invoicing, billing, payments, VAT, reporting, etc.
• Track bank accounts, stocks, income, and expenses.
• Track multiple accounts in a multiple-department business.
• Use GnuCash to manage multi-currency business accounts.

This instructor-led, live training in 日本 (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 (onsite or remote) is aimed at accountants and bookkeepers who wish to use Xero for bookkeeping.

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

• Get a real-time view of cashflow.
• Link bank accounts to Xero for bank reconciliation.
• Prepare and check VAT (Value Added Tax) returns in Xero.
• Create reports for sharing amongst team members.

This instructor-led, live training in 日本 (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 日本 (online or onsite) is aimed at developers who wish to use Open Bank Project API to develop and test decentralized applications that can be integrated easily with digital banking systems.

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

• Set up the necessary development environment to start developing applications with OBP API.
• Understand the Open Bank Project architecture, technology, and concepts.
• Learn how to use and customize OBP API to develop and build applications for banking.
• Explore the features, tools, APIs, and sandboxes in OBP.
• Implement security and integrations in OBP API connectors and adapters.

This instructor-led, live training in 日本 (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.