Python Security Training Course
This course provides an introduction to the Python programming language. Upon completing this class, students will be able to write complex Python programs that cover a wide range of topics. The curriculum covers essential elements such as language components, using a professional Integrated Development Environment (IDE), control flow structures, strings, input/output operations, collections, classes, modules, and regular expressions. The course is enriched with numerous hands-on labs, solutions, and code examples.
After completing the course, students will be able to demonstrate their knowledge and understanding of Python security principles.
This course is available as onsite live training in Serbia or online live training.Course Outline
- Python object types
- Numeric types
- Strings
- Lists and dictionaries
- Python statements
- Assignments, expressions, and prints
- If tests and syntax rules
- Repetition statements
- Functions
- Modules
Requirements
Basics of any programming language
Basics of information Security
Open Training Courses require 5+ participants.
Python Security Training Course - Booking
Python Security Training Course - Enquiry
Python Security - Consultancy Enquiry
Testimonials (2)
Hands-on exercises related to content really helps to understand more about each topic. Also, style of start class with lecture and continue with hands-on exercise is good and helpful to relate with the lecture that presented earlier.
Nazeera Mohamad - Ministry of Science, Technology and Innovation
Course - Introduction to Data Science and AI using Python
Examples/exercices perfectly adapted to our domain
Luc - CS Group
Course - Scaling Data Analysis with Python and Dask
Upcoming Courses
Related Courses
Advanced Python: Best Practices and Design Patterns
28 HoursThis intensive, hands-on course delves into advanced Python techniques, engineering best practices, and commonly used design patterns to help you build maintainable, testable, and high-performance Python applications. The course emphasizes modern tooling, typing, concurrency models, architecture patterns, and deployment-ready workflows.
This instructor-led, live training (available online or onsite) is designed for intermediate to advanced Python developers who wish to adopt professional practices and patterns for production-grade Python systems.
By the end of this training, participants will be able to:
- Apply Python typing, dataclasses, and type-checking to enhance code reliability.
- Utilize design patterns and architecture principles to create robust applications.
- Implement concurrency and parallelism effectively using asyncio and multiprocessing.
- Build well-tested code with pytest, property-based testing, and CI pipelines.
- Profile, optimize, and secure Python applications for production environments.
- Package, distribute, and deploy Python projects using modern tools and containers.
Format of the Course
- Interactive lectures and short demonstrations.
- Hands-on labs and coding exercises each day.
- A capstone mini-project that integrates patterns, testing, and deployment.
Course Customization Options
- To request a customized training or to focus on specific areas such as data, web, or infrastructure, please contact us to arrange.
Agentic AI Engineering with Python — Build Autonomous Agents
21 HoursThis course offers practical engineering methods for designing, constructing, testing, and deploying autonomous systems using Python. It covers the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.
This instructor-led, live training (available online or on-site) is targeted at intermediate to advanced ML engineers, AI developers, and software engineers who aim to build robust, production-ready autonomous agents using Python.
By the end of this training, participants will be able to:
- Design and implement the agent loop and decision-making processes.
- Integrate external tools and APIs to enhance agent capabilities.
- Develop short-term and long-term memory architectures for agents.
- Coordinate multi-step orchestrations and ensure agent composability.
- Apply best practices for safety, access control, and observability in deployed agents.
Format of the Course
- Interactive lectures and discussions.
- Hands-on labs for building agents with Python and popular SDKs.
- Project-based exercises that result in deployable prototypes.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Introduction to Data Science and AI using Python
35 HoursThis is a five-day introductory course on Data Science and Artificial Intelligence (AI).
The course includes practical examples and exercises using Python.
Artificial Intelligence with Python (Intermediate Level)
35 HoursArtificial Intelligence with Python involves the development of intelligent systems using Python’s rich ecosystem of AI and machine learning libraries.
This instructor-led, live training (available online or onsite) is designed for intermediate-level Python programmers who want to design, implement, and deploy AI solutions using Python.
By the end of this training, participants will be able to:
- Implement AI algorithms using Python’s core AI libraries.
- Work with supervised, unsupervised, and reinforcement learning models.
- Integrate AI solutions into existing applications and workflows.
- Evaluate model performance and optimize for accuracy and efficiency.
Format of the Course
- Interactive lectures and discussions.
- Plenty of exercises and practical activities.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Algorithmic Trading with Python and R
14 HoursThis instructor-led, live training in Serbia (online or onsite) is aimed at business analysts who wish to automate trade with algorithmic trading, Python, and R.
By the end of this training, participants will be able to:
- Employ algorithms to buy and sell securities at specialized increments rapidly.
- Reduce costs associated with trade using algorithmic trading.
- Automatically monitor stock prices and place trades.
Applied AI from Scratch in Python
28 HoursThis is a four-day course designed to introduce artificial intelligence and its applications using the Python programming language. An optional extra day is available for participants to work on an AI project upon completing the course.
AWS Cloud9 and Python: A Practical Guide
14 HoursThis instructor-led, live training in Serbia (online or onsite) is aimed at intermediate-level Python developers who wish to enhance their Python development experience using AWS Cloud9.
By the end of this training, participants will be able to:
- Set up and configure AWS Cloud9 for Python development.
- Understand the AWS Cloud9 IDE interface and features.
- Write, debug, and deploy Python applications in AWS Cloud9.
- Collaborate with other developers using the AWS Cloud9 platform.
- Integrate AWS Cloud9 with other AWS services for advanced deployments.
Building Chatbots in Python
21 HoursChatBots are computer programs designed to automatically simulate human responses through chat interfaces. These programs help organizations enhance their operational efficiency by offering more convenient and faster interaction options for users.
In this instructor-led, live training, participants will learn how to develop chatbots using Python.
By the end of this training, participants will be able to:
- Grasp the foundational concepts of building chatbots
- Create, test, deploy, and troubleshoot various chatbots using Python
Audience
- Developers
Format of the course
- A combination of lectures, discussions, practical exercises, and extensive hands-on practice
Note
- To request a customized training for this course, please contact us to arrange.
GPU Programming with CUDA and Python
14 HoursThis instructor-led, live training in Serbia (online or onsite) is aimed at intermediate-level developers who wish to use CUDA to build Python applications that run in parallel on NVIDIA GPUs.
By the end of this training, participants will be able to:
- Use the Numba compiler to accelerate Python applications running on NVIDIA GPUs.
- Create, compile and launch custom CUDA kernels.
- Manage GPU memory.
- Convert a CPU based application into a GPU-accelerated application.
Scaling Data Analysis with Python and Dask
14 HoursThis instructor-led, live training in Serbia (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.
Data Analysis with Python, Pandas and Numpy
14 HoursThis instructor-led, live training in Serbia (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.
FARM (FastAPI, React, and MongoDB) Full Stack Development
14 HoursThis 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.
Developing APIs with Python and FastAPI
14 HoursThis instructor-led, live training in Serbia (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.
Fraud Detection with Python and TensorFlow
14 HoursThis instructor-led, live training in Serbia (online or onsite) is aimed at data scientists who wish to use TensorFlow to analyze potential fraud data.
By the end of this training, participants will be able to:
- Create a fraud detection model in Python and TensorFlow.
- Build linear regressions and linear regression models to predict fraud.
- Develop an end-to-end AI application for analyzing fraud data.
Accelerating Python Pandas Workflows with Modin
14 HoursThis instructor-led, live training in Serbia (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.