Data Science Programme Training Course

This is a five-day introductory course on Data Science and Artificial Intelligence (AI) for government.

The course includes practical examples and exercises utilizing Python, designed to align with public sector workflows and governance.

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.

Participants who complete this training will gain a practical, real-world understanding of Data Science and its associated technologies, methodologies, and tools.

Participants will have the opportunity to apply this knowledge through hands-on exercises. Group interaction and instructor feedback are integral components of the class.

The course begins with an introduction to fundamental concepts in Data Science, then advances to the tools and methodologies used in the field.

Audience

• Developers
• Technical Analysts
• IT Consultants

Format of the Course for Government

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

Note

• To request a customized training for this course, please contact us to arrange.

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 (online or onsite) is designed for professionals who wish to embark on a career in Data Science.

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

• Install and configure Python and MySQL.
• Understand the principles of Data Science and how it can add value to various public sector operations.
• Learn the fundamentals of coding in Python.
• Explore supervised and unsupervised Machine Learning techniques, and gain the ability to implement them and interpret the results.

Format of the Course

• Interactive lecture and discussion.
• Extensive exercises and practical activities.
• Hands-on implementation in a live-lab environment for government.

Course Customization Options

• To request a customized training program for this course, please contact us to arrange.

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 designed for intermediate-level data analysts, developers, or aspiring data scientists who wish to apply machine learning techniques using Python to extract insights, make predictions, and automate data-driven decisions for government.

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

• Understand and differentiate key machine learning paradigms for government use.
• Explore data preprocessing techniques and model evaluation metrics relevant to public sector workflows.
• Apply machine learning algorithms to solve real-world data problems in the public sector.
• Use Python libraries and Jupyter notebooks for hands-on development tailored to government applications.
• Build models for prediction, classification, recommendation, and clustering that align with public sector 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 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 training course is designed to assist participants in preparing for web application development using Python programming, along with data analytics. Data visualization tools are invaluable for top management in the decision-making process for government.

This instructor-led, live training in US Empire (online or onsite) is aimed at data analysts and web developers who wish to develop associative models in Qlik Sense for government.

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

• Utilize Qlik Sense in data science applications.
• Navigate and use the Qlik Sense interface effectively.
• Foster a data-literate workforce through AI interaction.
• Establish a data-driven enterprise using Qlik Sense for government operations.

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.