Get certified for Python in 2023! Prepare for your Python Certification Exam and (2023) Professional Practice Test
What you will learn
Structured: This course is well structured, you can test your knowledge after completing your coding chapters..
Interview Preparation: This course is well designed for students and developers who are planning for job interviews.
Beginners: If you have learned your basics of python this exam course will show you how much you’ve learned.
Professionals: Those who have knowledge about python and coding this course will test you from root.
Chapters: All the tests are designed chapter wise, so you can choose test chapters according to your favorite topics.
Explanations: If you were stuck somewhere, well and detailed explanation will be there for you.
Description
Now is the time to get certified for Python!
This course is designed to help you prepare for the Python Professional Certification exam by providing you with a series of chapter-wise practice tests.
This Exams= contains 20 Chapters to give you the best thrilling experience on the Complete Python Programming Exam Tests!
Every Question has complete explanation.
All Questions are carried from the best programming institutes and all the knowledgeable areas.
No matter you are a student or a professional programmer, this exam is well designed for everyone from the experts.
Exam Syllabus (Chapter Wise):
Chapter 1: Introduction to Python
- What is Python?
- History of Python
- Features of Python
- Advantages of using Python
- Setting up the Python environment
- Running a Python program
Chapter 2: Variables, Data Types and Operators
- Variables and Naming Conventions
- Data Types: Numbers, Strings, Booleans
- Type Conversion and Type Checking
- Operators: Arithmetic, Assignment, Comparison, Logical, Bitwise
Chapter 3: Control Statements
- Conditional Statements: if, else, elif
- Looping Statements: for loop, while loop
- Loop Control Statements: break, continue, pass
- Nested loops and conditional statements
Chapter 4: Functions and Modules
- Defining and calling a function
- Function Arguments: Positional, Keyword, Default and Variable-length arguments
- Returning values from a function
- Modules: Creating and importing modules
- Standard Libraries
Chapter 5: Object-Oriented Programming (OOP) concepts
- Classes and Objects
- Data Hiding and Encapsulation
- Inheritance and Polymorphism
- Abstract classes and Interfaces
Chapter 6: File Handling and Input/Output Operations
- Opening and Closing Files
- Reading and Writing to Files
- Binary Files and File Modes
- Working with Directories
Chapter 7: Exception Handling
- What are exceptions?
- Handling exceptions using try and except blocks
- Multiple except blocks and else clause
- Raising exceptions
Chapter 8: Regular Expressions
- What are regular expressions?
- Pattern matching and substitution
- Meta-characters and Character Classes
- Regular Expression functions in Python
Chapter 9: Working with Databases and SQL
- Connecting to a database
- Creating tables and inserting data
- Retrieving data from tables
- Updating and Deleting data
- SQL Injection and Prevention
Chapter 10: Data Structures
- Lists
- Tuples
- Dictionaries
- Sets
- Arrays
Chapter 11: NumPy and SciPy Libraries
- Introduction to NumPy and SciPy
- Arrays in NumPy
- Mathematical Operations on Arrays
- Linear Algebra using SciPy
Chapter 12: Pandas Library
- Introduction to Pandas
- Data Structures in Pandas
- Data Manipulation using Pandas
- Data Analysis using Pandas
Chapter 13: Matplotlib Library
- Introduction to Matplotlib
- Types of Plots: Line, Bar, Scatter, Histogram, etc.
- Customizing Plots
- Subplots and Figures
Chapter 14: Flask Web Framework
- Introduction to Flask
- Creating a Flask Application
- Routing and Requests
- Templates and Forms
Chapter 15: Django Web Framework
- Introduction to Django
- Creating a Django Application
- Models, Views, and Templates
- Admin Interface
Chapter 16: Machine Learning and Data Science with Python
- Introduction to Machine Learning
- Scikit-Learn Library
- Linear Regression
- Classification
- Clustering
Chapter 17: Natural Language Processing (NLP) with Python
- Introduction to NLP
- Text Preprocessing
- Text Classification and Sentiment Analysis
- Named Entity Recognition
Chapter 18: GUI Programming with Tkinter Library
- Introduction to Tkinter
- Creating a GUI Application
- Widgets and Layouts
- Event Handling
Chapter 19: Advanced Python Concepts
- Multithreading and Concurrency
- Networking
- GUI Toolkits: PyQt, Kivy, etc.
- Debugging and Profiling
Note: This exam Covers all the topics on Complete Python Programming from Scratch!
What are you waiting for? Join now and get Certified!