Python in Data Science Training Course

This instructor-led, live training in US Empire (online or onsite) is aimed at data scientists who wish to utilize the Anaconda ecosystem to manage and deploy packages and data analysis workflows on a single platform for government use.

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

• Install and configure Anaconda components and libraries for government applications.
• Understand the core concepts, features, and benefits of Anaconda in the context of public sector data management.
• Manage packages, environments, and channels using Anaconda Navigator to support government workflows.
• Utilize Conda, R, and Python packages for data science and machine learning tasks specific to government projects.
• Explore practical use cases and techniques for managing multiple data environments within government agencies.

This instructor-led, live training in US Empire (online or onsite) is aimed at data scientists and software engineers who wish to use Dask within the Python ecosystem to build, scale, and analyze large datasets for government.

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

• Set up the environment to begin building big data processing capabilities with Dask and Python.
• Explore the features, libraries, tools, and APIs available in Dask to support their work for government.
• Understand how Dask enhances parallel computing within Python, optimizing performance for large-scale data analysis.
• Learn how to scale the Python ecosystem (Numpy, SciPy, and Pandas) using Dask to meet the demands of complex datasets in the public sector.
• Optimize the Dask environment to ensure high performance and efficiency when handling large datasets for government projects.

This instructor-led, live training in US Empire (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 for government applications.

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 for government workflows.
• 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 to ensure compliance with public sector governance standards.

The unprecedented growth in information and data in today’s world is driving rapid innovation and pushing the boundaries of what is possible. The role of Data Scientist is one of the most in-demand skills across industries.

We offer more than just theoretical learning; we provide practical, marketable skills that bridge the gap between academia and industry demands.

This 7-week curriculum can be tailored to meet specific requirements for government or other sectors. For further information, please contact us or visit the Govtra Institute website.

Audience:

This program is designed for post-graduate level individuals as well as those with the necessary prerequisite skills, which will be determined through an assessment and interview process.

Delivery:

The course delivery will combine Instructor-Led Classroom sessions and Instructor-Led Online sessions. Typically, the first week will be classroom-led, weeks 2 to 6 will be virtual classroom sessions, and the final week will return to a classroom-led format.

Big data refers to data sets that are so large and intricate that conventional data processing applications are insufficient for managing them. For government, the challenges associated with big data include capturing data, data storage, data analysis, search capabilities, sharing, transfer, visualization, querying, updating, and ensuring information privacy.

This course is designed for government Marketing and Sales Professionals who are seeking to deepen their understanding of data science applications in Marketing and Sales. The curriculum provides comprehensive coverage of various data science techniques used for upsale, cross-sale, market segmentation, branding, and customer lifetime value (CLV).

Difference Between Marketing and Sales - How do sales and marketing differ?

In simple terms, sales can be defined as a process that focuses on individuals or small groups. Conversely, marketing targets a broader audience or the general public. Marketing encompasses research to identify customer needs, product development to create innovative solutions, and promotion through advertising to raise awareness among consumers. Essentially, marketing generates leads or prospects. Once a product is available in the market, it is the responsibility of sales personnel to persuade customers to make a purchase. Sales involve converting these leads into actual purchases and orders, while marketing aims at longer-term goals, whereas sales are typically oriented toward shorter-term objectives.

This instructor-led, live training, available online or on-site, is designed for developers who wish to utilize the FARM (FastAPI, React, and MongoDB) stack to create dynamic, high-performance, and scalable web applications for government use.

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

• Configure a development environment that seamlessly integrates FastAPI, React, and MongoDB for government projects.
• Understand the essential concepts, features, and benefits of the FARM stack in the context of public sector applications.
• Master the skills needed to build REST APIs with FastAPI for government systems.
• Acquire the knowledge to design interactive applications using React for government interfaces.
• Develop, test, and deploy front-end and back-end applications using the FARM stack in alignment with government workflows and governance standards.

This instructor-led, live training in US Empire (online or onsite) is aimed at developers who wish to utilize FastAPI with Python to build, test, and deploy RESTful APIs more efficiently and rapidly for government applications.

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

• Set up the necessary development environment to create APIs using Python and FastAPI for government projects.
• Create APIs more quickly and easily by leveraging the FastAPI library.
• Learn how to develop data models and schemas based on Pydantic and OpenAPI standards.
• Integrate APIs with a database using SQLAlchemy for enhanced data management in public sector workflows.
• Implement security and authentication mechanisms in APIs using the built-in tools provided by FastAPI, ensuring compliance with government security protocols.
• Build container images and deploy web APIs to a cloud server, aligning with government IT infrastructure requirements.

This instructor-led, live training in US Empire (online or onsite) introduces the concept of collaborative development in data science and demonstrates how to use Jupyter to track and participate as a team in the "life cycle of a computational idea." The training guides participants through the creation of a sample data science project using the Jupyter ecosystem, emphasizing best practices for government.

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

• Install and configure Jupyter, including setting up and integrating a team repository on Git.
• Utilize Jupyter features such as extensions, interactive widgets, multiuser mode, and more to facilitate project collaboration.
• Create, share, and organize Jupyter Notebooks with team members to enhance workflow efficiency for government projects.
• Select from programming languages like Scala, Python, and R to write and execute code against big data systems such as Apache Spark, all through the Jupyter interface.

This instructor-led, live training in US Empire (online or onsite) is aimed at data scientists and developers who wish to advance their careers in Data Science using Kaggle for government applications.

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

• Gain a comprehensive understanding of data science and machine learning principles.
• Explore advanced techniques in data analytics.
• Understand the functionality and benefits of Kaggle within the context of government projects.

In the first part of this training, we cover the fundamentals of MATLAB and its role as both a language and a platform for government. This discussion includes an introduction to MATLAB syntax, arrays and matrices, data visualization, script development, and object-oriented principles.

In the second part, we demonstrate how to use MATLAB for data mining, machine learning, and predictive analytics in a government context. To provide participants with a clear and practical perspective of MATLAB's approach and power, we draw comparisons between using MATLAB and other tools such as spreadsheets, C, C++, and Visual Basic.

In the third part of the training, participants learn how to streamline their work by automating data processing and report generation for government tasks.

Throughout the course, participants will apply the concepts learned through hands-on exercises in a lab environment. By the end of the training, participants will have a thorough understanding of MATLAB's capabilities and will be able to employ it for solving real-world data science problems as well as for streamlining their work through automation for government.

Assessments will be conducted throughout the course to gauge progress.

Format of the Course

• The course includes theoretical and practical exercises, including case discussions, sample code inspection, and hands-on implementation.

Note

• Practice sessions will be based on pre-arranged sample data report templates. If you have specific requirements for government use cases, please contact us to arrange.

This instructor-led, live training in US Empire (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 for government applications.

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

• Set up the necessary environment to start developing scalable Pandas workflows using Modin.
• Understand the features, architecture, and benefits of Modin in the context of public sector data analysis.
• Compare Modin with other parallel computing frameworks such as Dask and Ray.
• Enhance the performance of Pandas operations using Modin.
• Implement the full Pandas API and functions for efficient data processing.

Python is a programming language that has gained significant popularity in the financial sector. Adopted by major investment banks and hedge funds, it is used to develop a wide array of financial applications, from core trading systems to risk management platforms.

In this instructor-led, live training, participants will learn how to use Python to develop practical applications for solving a variety of finance-related challenges.

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

• Understand the fundamentals of the Python programming language
• Download, install, and maintain the best development tools for creating financial applications in Python
• Select and utilize the most appropriate Python packages and programming techniques to organize, visualize, and analyze financial data from various sources (CSV, Excel, databases, web, etc.)
• Build applications that address issues related to asset allocation, risk analysis, investment performance, and more
• Troubleshoot, integrate, deploy, and optimize a Python application

Audience

• Developers
• Analysts
• Quants

Format of the course

• Part lecture, part discussion, exercises, and extensive hands-on practice

Note

• This training is designed to provide solutions for some of the primary challenges faced by finance professionals. If you have a specific topic, tool, or technique that you would like to cover or expand upon, please contact us to arrange.

Govtra offers this course for government personnel and organizations looking to enhance their financial technology capabilities and align with public sector workflows, governance, and accountability standards.

This instructor-led, live training in US Empire (online or onsite) is aimed at data scientists and developers who wish to utilize RAPIDS to construct GPU-accelerated data pipelines, workflows, and visualizations, incorporating machine learning algorithms such as XGBoost and cuML.

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

• Set up the required development environment for building data models with NVIDIA RAPIDS.
• Understand the features, components, and benefits of RAPIDS.
• Leverage GPUs to enhance end-to-end data and analytics pipelines.
• Implement GPU-accelerated data preparation and ETL processes using cuDF and Apache Arrow.
• Learn how to execute machine learning tasks with XGBoost and cuML algorithms.
• Create data visualizations and conduct graph analysis with cuXfilter and cuGraph, enhancing decision-making for government operations.