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FINAL EXAM ONLY PYTHON_LA

Python – Training Course (Data Science, Machine Learning, Web & Automation)

The Python – Training Course (Data Science, Machine Learning, Web & Automation) provides a comprehensive education on Python 3.x, focusing on key professional application areas. Participants will gain hands-on skills in managing virtual environments and dependencies, writing automated tests with pytest, and manipulating data using libraries such as NumPy and pandas. Advanced topics in machine learning with scikit-learn, web development with Flask and Django, and automation using scripting, APIs, and job scheduling are covered. The teaching approach combines theory, practical exercises, and case studies, emphasizing development best practices according to PEP 8 style guidelines. The course is designed for programmers, analysts, and IT professionals seeking to integrate Python into their projects to enhance efficiency and analytical capabilities. At the end, a certification exam assesses the acquired skills. This training is suitable for those aiming to deepen language proficiency across diverse application fields, improving technical knowledge and operational abilities for professional work.

Exam duration60 min
Pass mark70%
Available questions200
CIWZ PROFESSIONAL ASSESSMENT

High-integrity learning environment

The pathway is designed for managers, executives, function owners, auditors and professionals. Lessons use validated minimum study time and a contextual tutor; assessments use server-side random selection of questions and answers, session-continuity controls, camera and local audio-activity monitoring during protected tests.

Traceability and reliability: integrity events are logged for authorized review; automated signals do not determine the result on their own.

OFFICIAL PATHWAY INFORMATION

Course technical sheet

Purpose, references, delivery method, commercial terms and certificate value, presented clearly and transparently.

01

Learning Objectives

  • Understand and apply core features of Python 3.x
  • Manage virtual environments and dependencies using venv and poetry
  • Develop testable software with pytest and testing best practices
  • Use scientific libraries like NumPy and pandas for data handling
  • Implement basic machine learning models with scikit-learn
  • Design web applications using Flask and Django
  • Automate processes through scripting, APIs, and job scheduling
02

Skills Acquired

  • Writing Python code conforming to PEP 8 standards
  • Building and maintaining isolated development environments
  • Creating unit tests and handling exceptions
  • Analyzing and manipulating complex datasets
  • Creating and validating predictive models
  • Developing RESTful web services
  • Scripting for automation and task management
03

Target Audience

  • Beginner to intermediate Python programmers
  • Early-career data analysts and data scientists
  • Web developers interested in Python frameworks
  • IT technicians and engineers aiming to automate tasks
04

Prerequisites

  • Basic programming knowledge
  • Familiarity with operating systems and command line
05

Syllabus

  • Introduction to Python 3.x and environment setup
  • Dependency management and virtual environments
  • Testing with pytest: unit tests and fixtures
  • Data manipulation with NumPy and pandas
  • Machine learning fundamentals with scikit-learn
  • Web development with Flask: routing, APIs, middleware
  • Django deep dive: models and views
  • Automation: scripting, APIs, job scheduling
06

Teaching Methodology

  • Lectures and theoretical explanations
  • Individual and group practical exercises
  • Real-world case study analysis
07

Evaluation Method

  • Final test requiring at least 70% to pass
  • Multiple choice questions and practical cases
08

Duration

  • 60 minutes
09

Certification

  • Certificate of attendance with final evaluation (certification fee 50 euros)
10

Expected Outcomes

  • Ability to use Python for data science, machine learning, web development, and automation
  • Knowledge of main Python ecosystem libraries and tools
  • Skills to write clean, tested, and maintainable code