Python Bootcamp Training Course Overview

Python Bootcamp Training Course Overview

Our Python Bootcamp Training is a comprehensive 4-week course designed for those with prior programming knowledge. Participants will master core Python programming concepts, including data structures, file handling, and modules, in the first week. The second week delves into OOP, threading, and multi-processing, while the third covers data cleaning, transformation, and Python libraries like Pandas and Numpy. The final week focuses on advanced techniques, including performance optimization and regular expressions. Through hands-on labs and a capstone project, learners will apply these concepts to solve real-world problems, ensuring not only theoretical understanding but also practical skills in Python development.

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  • Live Training (Duration : 200 Hours)
  • Per Participant
  • Classroom Training fee on request

♱ Excluding VAT/GST

You can request classroom training in any city on any date by Requesting More Information

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Target Audience for Python Bootcamp Training

Introduction: The Python Bootcamp Training by Koenig Solutions is designed for individuals with programming knowledge who seek to enhance their skills in Python for diverse IT applications, ranging from data analysis to automation.


Target Audience and Job Roles:


  • Software Developers and Programmers
  • Data Scientists and Data Analysts
  • Machine Learning Engineers
  • IT Professionals and System Administrators
  • Automation Engineers
  • Technical Consultants
  • Web Developers and Backend Developers
  • Data Engineers and ETL Developers
  • Research Scientists using Python for simulations
  • College Students pursuing IT or computer science
  • IT Training and Educators looking to expand Python knowledge
  • Project Managers overseeing IT and software projects


Learning Objectives - What you will Learn in this Python Bootcamp Training?

  1. The Python Bootcamp Training at Koenig Solutions equips students with essential Python skills, from core programming to advanced data processing, parallel execution, and practical implementation in projects, ensuring a comprehensive mastery of Python.

  2. Learning Objectives and Outcomes:

    • Understand the basic syntax, variables, and data types in Python.
    • Master control flow mechanisms and functions to write efficient Python programs.
    • Utilize and manipulate various data structures, including lists, tuples, sets, and dictionaries.
    • Implement file handling operations and effectively manage exceptions.
    • Gain proficiency in object-oriented programming principles, including encapsulation, inheritance, and polymorphism.
    • Develop skills in threading and multi-processing for parallel execution in Python applications.
    • Conduct data cleaning and transformation, using libraries such as Pandas and Numpy.
    • Analyze and process large datasets, integrating Numpy arrays with Pandas DataFrames.
    • Apply regular expressions for pattern matching and text data processing.
    • Enhance Python code performance through profiling and optimization techniques.

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