Course Outline

Introduction to Python and Google Colab for Government

  • Setting up Google Colab for government use
  • Understanding the Python programming environment for government applications
  • Writing and executing your first Python script for government tasks

Variables and Data Types for Government Use

  • Introduction to variables in a government context
  • Different data types in Python relevant to government operations
  • Operations on numbers and strings for government data processing

Control Structures for Government Applications

  • Conditional statements for decision-making in government processes
  • Loops: for and while, for iterating over government datasets
  • Controlling program flow with decisions to enhance government efficiency

Functions and Modules for Government Use

  • Defining and calling functions to streamline government operations
  • Scope and lifetime of variables in a government context
  • Importing and using modules to enhance government software capabilities

Working with Collections for Government Data

  • Lists and tuples for managing government data sets
  • Dictionaries and sets for efficient data organization in government applications
  • Iterating through collections to process government information effectively

Basic Libraries in Python for Government Use

  • Introduction to libraries like NumPy and Matplotlib for government data analysis
  • Basic data manipulation with Pandas for government datasets
  • Simple data visualization to support government decision-making

Final Project for Government Applications

  • Applying learned concepts to a small project relevant to government operations
  • Best practices for writing and organizing Python code for government use
  • Debugging and troubleshooting techniques for government applications

Summary and Next Steps for Government Use

Requirements

  • No prior programming experience required for government staff.
  • Basic understanding of computer operations.
  • Familiarity with web browsing and simple mathematical concepts.

Audience

  • Developers for government projects.
  • Data analysts for government initiatives.
 14 Hours

Number of participants


Price per participant

Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.

Testimonials (3)

The fact of having more practical exercises using more similar data to what we use in our projects (satellite images in raster format)

Matthieu - CS Group
Course - Scaling Data Analysis with Python and Dask

Very good preparation and expertise of a trainer, perfect communication in English. The course was practical (exercises + sharing examples of use cases)

Monika - Procter & Gamble Polska Sp. z o.o.
Course - Developing APIs with Python and FastAPI

Trainer develops training based on participant's pace

Farris Chua
Course - Data Analysis in Python using Pandas and Numpy

Upcoming Courses

Python Programming Fundamentals using Google Colab

2026-02-10 09:30
14 hours
Olympia, WA
$ 2703 (Online)
$ 3903 (Classroom)

Python Programming Fundamentals using Google Colab

2026-02-24 09:30
14 hours
Seattle, WA - Regus at Seattle City
$ 2703 (Online)
$ 3903 (Classroom)

Python Programming Fundamentals using Google Colab

2026-03-10 09:30
14 hours
Seattle, WA
$ 2703 (Online)
$ 3903 (Classroom)

Python Programming Fundamentals using Google Colab

2026-03-24 09:30
14 hours
Sunnyvale, CA - Regus - California Downtown Sunnyvale
$ 2703 (Online)
$ 3903 (Classroom)

Python Programming Fundamentals using Google Colab

2026-04-07 09:30
14 hours
San Jose, CA - Downtown
$ 2703 (Online)
$ 3903 (Classroom)

Related Courses

Advanced Machine Learning Models with Google Colab

 21 Hours
This instructor-led, live training (conducted online or onsite) is designed for advanced-level professionals who wish to deepen their understanding of machine learning models, refine their hyperparameter tuning skills, and learn effective model deployment using Google Colab. By the end of this training, participants will be able to: - Implement advanced machine learning models using popular frameworks such as Scikit-learn and TensorFlow. - Enhance model performance through hyperparameter tuning. - Deploy machine learning models in real-world applications using Google Colab. - Collaborate and manage large-scale machine learning projects in Google Colab, ensuring alignment with public sector workflows for government.
Read more...

Big Data Analytics with Google Colab and Apache Spark

 14 Hours
This instructor-led, live training (available online or onsite) is designed for intermediate-level data scientists and engineers who wish to utilize Google Colab and Apache Spark for big data processing and analytics. By the end of this training, participants will be able to: - Configure a big data environment using Google Colab and Apache Spark. - Efficiently process and analyze large datasets with Apache Spark. - Visualize big data in a collaborative setting. - Integrate Apache Spark with cloud-based tools for government.
Read more...

Introduction to Google Colab for Data Science

 14 Hours
This instructor-led, live training (conducted either online or onsite) is designed for government data scientists and IT professionals at the beginner level who wish to gain foundational knowledge in data science using Google Colab. By the end of this training, participants will be able to: - Set up and navigate Google Colab. - Write and execute basic Python code. - Import and manage datasets. - Create visualizations using Python libraries for government applications.
Read more...

Computer Vision with Google Colab and TensorFlow

 21 Hours
This instructor-led, live training (online or onsite) is designed for advanced-level professionals who aim to deepen their understanding of computer vision and explore TensorFlow's capabilities for developing sophisticated vision models using Google Colab. By the end of this training, participants will be able to: - Build and train convolutional neural networks (CNNs) using TensorFlow. - Leverage Google Colab for scalable and efficient cloud-based model development. - Implement image preprocessing techniques for computer vision tasks. - Deploy computer vision models for real-world applications. - Use transfer learning to enhance the performance of CNN models. - Visualize and interpret the results of image classification models. This training is tailored to ensure that professionals can apply these skills effectively in their roles, particularly in projects for government.
Read more...

Scaling Data Analysis with Python and Dask

 14 Hours
This instructor-led, live training in US (online or onsite) is designed for data scientists and software engineers who wish to utilize 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 necessary environment to begin building big data processing systems using Dask and Python. - Explore the features, libraries, tools, and APIs available in Dask. - Understand how Dask enhances parallel computing capabilities in Python. - Learn techniques for scaling the Python ecosystem (including Numpy, SciPy, and Pandas) using Dask. - Optimize the Dask environment to ensure high performance when handling large datasets.
Read more...

Data Analysis with Python, Pandas and Numpy

 14 Hours

This instructor-led, live training in US (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.
Read more...

Deep Learning with TensorFlow in Google Colab

 14 Hours
This instructor-led, live training in [location] (online or onsite) is designed for intermediate-level data scientists and developers who aim to understand and apply deep learning techniques using the Google Colab environment. By the end of this training, participants will be able to: - Set up and navigate Google Colab for government deep learning projects. - Understand the fundamentals of neural networks. - Implement deep learning models using TensorFlow. - Train and evaluate deep learning models. - Utilize advanced features of TensorFlow for deep learning.
Read more...

Data Visualization with Google Colab

 14 Hours

This instructor-led, live training in US (online or onsite) is aimed at beginner-level data scientists who wish to learn how to create meaningful and visually appealing data visualizations for government.

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

  • Set up and navigate Google Colab for data visualization purposes.
  • Create various types of plots using Matplotlib.
  • Utilize Seaborn for advanced visualization techniques.
  • Customize plots to enhance presentation and clarity.
  • Effectively interpret and present data using visual tools.
Read more...

FARM (FastAPI, React, and MongoDB) Full Stack Development

 14 Hours
This instructor-led, live training (available online or on-site) is designed for developers who aim 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: - Set up a development environment that seamlessly integrates FastAPI, React, and MongoDB. - Understand the fundamental concepts, features, and benefits of the FARM stack. - Learn how to develop REST APIs using FastAPI. - Gain proficiency in designing interactive applications with React. - Develop, test, and deploy both front-end and back-end components of applications using the FARM stack.
Read more...

Developing APIs with Python and FastAPI

 14 Hours
This instructor-led, live training (online or onsite) is aimed at developers who wish to use FastAPI with Python to build, test, and deploy RESTful APIs more efficiently and rapidly for government projects. By the end of this training, participants will be able to: - Set up the necessary development environment to create APIs using Python and FastAPI. - Develop APIs more quickly and easily leveraging the FastAPI library. - Understand how to create data models and schemas based on Pydantic and OpenAPI standards. - Integrate APIs with a database using SQLAlchemy. - Implement security and authentication in APIs utilizing FastAPI tools. - Build container images and deploy web APIs to a cloud server for government use.
Read more...

Machine Learning with Google Colab

 14 Hours
This instructor-led, live training in [location] (online or onsite) is designed for intermediate-level data scientists and developers who aim to apply machine learning algorithms efficiently using the Google Colab environment. By the end of this training, participants will be able to: - Set up and navigate Google Colab for government machine learning projects. - Understand and apply various machine learning algorithms. - Utilize libraries such as Scikit-learn to analyze and predict data. - Implement both supervised and unsupervised learning models. - Optimize and evaluate machine learning models effectively.
Read more...

Accelerating Python Pandas Workflows with Modin

 14 Hours
This instructor-led, live training in US (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 for government applications. - Differentiate between Modin, Dask, and Ray in terms of their suitability for various data processing tasks. - Perform Pandas operations more efficiently using Modin. - Implement the entire Pandas API and functions to enhance data analysis capabilities.
Read more...

Natural Language Processing (NLP) with Google Colab

 14 Hours
This instructor-led, live training in [location] (online or onsite) is aimed at intermediate-level data scientists and developers who wish to apply natural language processing (NLP) techniques using Python in Google Colab for government applications. By the end of this training, participants will be able to: - Understand the core concepts of NLP. - Preprocess and clean text data for NLP tasks. - Perform sentiment analysis using NLTK and SpaCy libraries. - Work with text data using Google Colab for scalable and collaborative development in a government context.
Read more...

Reinforcement Learning with Google Colab

 28 Hours

This instructor-led, live training in US (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of reinforcement learning and its practical applications in AI development for government using Google Colab.

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

  • Understand the core concepts of reinforcement learning algorithms.
  • Implement reinforcement learning models using TensorFlow and OpenAI Gym.
  • Develop intelligent agents that learn through trial and error.
  • Optimize agent performance using advanced techniques such as Q-learning and deep Q-networks (DQNs).
  • Train agents in simulated environments using OpenAI Gym.
  • Deploy reinforcement learning models for real-world applications, enhancing decision-making processes for government.
Read more...

Time Series Analysis with Google Colab

 21 Hours
This instructor-led, live training in [location] (online or onsite) is aimed at intermediate-level data professionals who wish to apply time series forecasting techniques to real-world data using Google Colab for government. By the end of this training, participants will be able to: - Understand the fundamentals of time series analysis. - Use Google Colab to work with time series data. - Apply ARIMA models to forecast data trends. - Utilize Facebook’s Prophet library for flexible forecasting. - Visualize time series data and forecasting results.
Read more...

Related Categories

Python
Python
Google Colab
Google Colab