Python Programming Professional Certification
Master Python in 6 weeks: OOP, data handling, multithreading, databases & real-world projects. Earn a professional certification to boost your career.
Instructor
Cognovera
Category
- Description
- Curriculum
- FAQ
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This 6-week professional certification program is designed for intermediate learners aiming to strengthen their Python programming expertise. The course covers core Python concepts, advanced OOP, data structures, file handling, regular expressions, libraries (NumPy, Pandas, Matplotlib), multithreading, networking, and database connectivity. Learners will gain hands-on experience with real-world applications and a final capstone project. By completion, students will be well-prepared for data science, automation, web development, or professional certifications.
Week 1: Python Foundations & OOP Basics
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1
Day 1: Python Environment Setup- Installing Python, IDEs (PyCharm, VS Code, Jupyter)
- Running Python scripts, interactive mode
- Introduction to syntax & indentation
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2
Day 2: Python Basics
- Variables, data types, operators
- Type conversions & input/output
- Expressions & precedence
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3
Day 3: Control Flow
- Conditional statements (if, elif, else)
- Loops (for, while)
- Loop control (break, continue, pass)
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4
Day 4: Functions
- Defining & calling functions
- Parameters & return values
- Scope & global vs local variables
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5
Day 5: Introduction to OOP in Python
- Classes & objects
- Constructors (__init__)
- Instance vs. class variables
Week 2: Advanced OOP & Error Handling
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6
Day 1: Inheritance
- Single & multiple inheritance
- super() function
- Method overriding
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7
Day 2: Polymorphism
- Duck typing
- Operator overloading
- Abstract base classes
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8
Day 3: Encapsulation & Special Methods
- Private & protected members
- Dunder methods (__str__, __len__)
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9
Day 4: Exception Handling
- Try-except-finally
- Raising exceptions
- Custom exception classes
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10
Day 5: Modules & Packages
- Importing built-in modules
- Creating custom modules
- Organizing with packages
Week 3: Data Structures & File Handling
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11
Day 1: Strings & Lists
- String methods & formatting
- List operations, slicing, comprehensions
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12
Day 2: Tuples, Sets, Dictionaries
- Immutable & mutable types
- Dictionary operations & methods
- Set operations
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13
Day 3: Iterators & Generators
- Iterators & iter(), next()
- Generator functions & expressions
- Use cases of generators
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14
Day 4: File Handling
- Opening, reading, writing files
- With statement & file modes
- Handling CSV, JSON files
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15
Day 5: Regular Expressions
- re module basics
- Pattern matching, searching, replacing
- Practical regex use cases
Week 4: Libraries & Data Handling
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16
Day 1: Working with NumPy
- Arrays, indexing, slicing
- Array operations
- Broadcasting
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17
Day 2: Pandas for Data Manipulation
- DataFrames & Series
- Importing/exporting data
- Data cleaning & filtering
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18
Day 3: Matplotlib & Visualization
- Plotting basics
- Line, bar, scatter, histogram plots
- Customizing charts
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19
Day 4: Date & Time Handling
- datetime module
- Formatting & parsing dates
- Timedelta operations
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20
Day 5: Virtual Environments & Dependency Management
- venv & pip
- Requirements.txt
- Best practices
Week 5: Advanced Python Concepts
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21
Day 1: Functional Programming
- Lambda functions
- map(), filter(), reduce()
- Closures
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22
Day 2: Decorators
- Function decorators
- Chaining decorators
- Use cases (logging, access control)
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23
Day 3: Multithreading & Multiprocessing
- Threading module basics
- Synchronization
- Multiprocessing module
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24
Day 4: Networking with Python
- Sockets basics
- Client-server communication
- HTTP requests (requests module)
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25
Day 5: Database Connectivity
- SQLite with Python
- CRUD operations
- SQLAlchemy ORM basics
Week 6: Testing, Advanced Features & Project
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26
Day 1: Unit Testing with PyTest/Unittest
- Writing test cases
- Assertions & fixtures
- Test-driven development basics
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27
Day 2: Python 3 Advanced Features
- Context managers (with)
- Type hints & annotations
- Dataclasses
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28
Day 3: Web Scraping
- BeautifulSoup basics
- Scraping structured data
- Handling requests & parsing
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29
Day 4: Capstone Project Development
- Building a real-world application (options: Expense Tracker, Student Management System, Data Analyzer)
- Integrating OOP, data handling, and libraries
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30
Day 5: Project Presentation & Certification Assessment
- Final project evaluation
- Certification test (MCQs + Coding)
- Feedback & next learning paths
Q1. Do I need prior Python knowledge to enroll?
Basic familiarity with Python is recommended, but not mandatory. The course starts with fundamentals before moving into advanced topics.
Q2. What kind of project will I build?
You will build a capstone project (e.g., Expense Tracker, Student Management System, Data Analyzer) that applies OOP, data handling, and libraries.
Q3. Will this certification help me in a career shift?
Yes. Python is widely used in data science, AI, web development, and automation. This certification strengthens your job profile.
Q4. Do I get lifetime access to materials?
Yes. All code files, lecture slides, and project templates will be shared for lifetime reference.
Q5. Can this prepare me for advanced fields like Data Science or AI?
Absolutely. This course builds the professional Python foundation, which is essential for progressing into Machine Learning, AI, or Cloud Development.
Skills You Will Learn in This Course
- Writing efficient, modular, and object-oriented Python code
- Implementing advanced OOP (inheritance, polymorphism, abstraction)
- Working with data structures (lists, dicts, sets, tuples)
- Handling files, CSV, JSON, and regular expressions
- Data analysis with NumPy, Pandas, Matplotlib
- Implementing multithreading & multiprocessing
- Building networked & database-connected applications
- Writing unit tests with PyTest/Unittest
- Web scraping with BeautifulSoup
- Designing & presenting a real-world Python project
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Course details
Lectures
30
Level
Beginner
Basic info
- Program Name: Python Programming Professional Certification
- Duration: 6 Weeks (5 days per week)
- Level: Intermediate
- Mode: Classroom / Online (Instructor-led)
- Final Assessment: Capstone Project + Certification Exam
- Outcome: Professional Certification in Python Programming
Course requirements
- Basic programming knowledge (variables, loops, conditionals)
- Prior exposure to Python fundamentals (recommended but not mandatory)
- Laptop/PC with Python 3.x installed
- IDE/Jupyter Notebook (VS Code, PyCharm, or Anaconda)
- Commitment to coding practice
Intended audience
- Students pursuing computer science, IT, or related fields
- Developers with basic Python knowledge who want to advance
- Professionals transitioning into data science, AI, or automation
- Web developers and backend engineers expanding their skill set
- Anyone aiming for a career in Python-based software development
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