Course Training Modules for Python
Module 1: Introduction to Python
Overview of Python programming language
Setting up the Python development environment
Understanding Python syntax and basic commands
Writing your first Python program
Module 2: Data Types and Variables
Understanding different data types (integers, floats, strings, booleans)
Working with variables and constants
Type casting and type conversion
Basic input and output operations
Module 3: Control Structures
Conditional statements (if, elif, else)
Looping constructs (for, while)
Nested loops and conditional statements
Control flow tools (break, continue, pass)
Module 4: Functions and Modules
Defining and calling functions
Function arguments and return values
Lambda functions and recursion
Importing and using modules and packages
Module 5: Data Structures
Working with lists, tuples, and sets
Understanding dictionaries and their operations
List comprehensions and dictionary comprehensions
Common data structure methods and functions
Module 6: File Handling
Reading from and writing to files
Working with different file modes (read, write, append)
Handling file exceptions
Using context managers for file operations
Module 7: Exception Handling
Understanding exceptions and errors
Try, except, else, and finally blocks
Raising exceptions
Creating custom exceptions
Module 8: Object-Oriented Programming (OOP)
Understanding classes and objects
Attributes and methods
Inheritance and polymorphism
Encapsulation and abstraction
Module 9: Working with Libraries
Introduction to Python libraries
Using NumPy for numerical operations
Data manipulation with Pandas
Data visualization with Matplotlib and Seaborn
Module 10: Web Development Basics
Setting up a basic web server
Creating and managing routes
Handling forms and user input
Implementing basic security measures
Module 11: Database Interaction
Introduction to databases and SQL
Connecting to databases with Python
Performing CRUD operations
Basic database optimization techniques
Module 12: Advanced Topics
Working with APIs and web scraping
Introduction to machine learning with Python
Using Python for automation and scripting
Best practices for writing efficient and readable Python code
Benefits of Python Training at TechQRT
Expert Instructors: Learn from experienced professionals with extensive knowledge in Python programming.
Comprehensive Curriculum: A well-rounded program covering fundamental to advanced topics.
Hands-on Projects: Gain practical experience through real-world projects and case studies.
Latest Tools and Technologies: Stay updated with current trends and tools in Python programming.
Flexible Learning: Options for online and in-person classes to fit your schedule.
Career Support: Receive career counseling, resume building, and interview preparation assistance.
Networking Opportunities: Connect with peers and industry experts through our community events and forums.
Post-Training Support: Access resources and support even after completing the training to help you in your professional journey.
Career Opportunities After Course Completion
Python Developer
Develop applications and scripts using Python
Collaborate with cross-functional teams to deliver software solutions
Data Analyst
Analyze and interpret complex data sets using Python
Create visualizations and reports to communicate findings
Data Scientist
Build and deploy machine learning models using Python
Work with large datasets to extract insights and inform business decisions
Web Developer
Develop and maintain web applications using Python
Integrate front-end and back-end components to deliver web solutions
Software Engineer
Design, develop, and maintain software applications
Use Python to solve complex problems and improve system performance
Automation Engineer
Develop automation scripts and tools using Python
Improve efficiency and productivity through automation solutions
DevOps Engineer
Use Python for automation and orchestration of DevOps tasks
Develop CI/CD pipelines and manage cloud infrastructure
Machine Learning Engineer
Build and deploy machine learning models
Use Python libraries like TensorFlow, Keras, and scikit-learn for ML tasks
Business Analyst
Analyze business data and provide insights using Python
Develop predictive models to support business strategies
Research Scientist
Conduct scientific research using Python for data analysis and modeling
Publish findings and contribute to the scientific community
Completing Python training at TechQRT equips you with the skills and knowledge to pursue various roles in the programming and data science fields, opening up numerous opportunities for career growth and advancement.