Python Certification Course
Adapt and Excel: Python Skills for the Modern Tech Landscape
Wiculty’s comprehensive Python Course and Training will guide you through the essentials of Python, covering data operations, conditional statements, shell scripting, and Django development. This Python certification program offers hands-on experience to help you build real-world applications, preparing you for a dynamic and rewarding career as a professional Python developer.
Overview
Python Course Syllabus
Master Python programming with Wiculty’s comprehensive course, designed for beginners and professionals. Learn essential concepts like syntax, object-oriented programming, and automation. Gain hands-on experience through real-world projects to advance your career in web development, data analysis, and more.
Why should I learn the Python programming language?
- Python’s design and extensive libraries can enhance productivity tenfold compared to languages like C, C++, or Java.
- In the United States, Senior Python Developers can expect to earn approximately US$102,000, as reported by Indeed.
| Criteria | C++ | Java | Python |
|---|---|---|---|
|
Ease of Use |
Verbose |
Verbose |
Simpler and dynamically typed |
|
Scalability |
Platform-depended |
Cross-platform |
Cross-platform |
|
Deployment |
Android and web application |
Big Data |
Data Science and Machine Learning |
|
Average Salary |
US$78,368 |
US$87,424 |
US$103,492 |
What topics will be covered in this Python online course?
In this course, you can learn various concepts related to Python including OOPs, expressions, data types, looping, functions, operations, classes, Python libraries, exception handling, packages, web scraping, machine learning algorithms in Python, and many more.
What are the prerequisites for taking this Course?
No, there are no mandatory prerequisites for participating in this course. While the training covers all the essential aspects of Python, having prior experience in this field can certainly be an advantage during the course.
Is Python a good language for beginners?
Python programming is used in the backend, and it is one of the top languages for beginners to learn and implement. It is very similar to Ruby. However, it requires comparatively less effort to code. This language is easily approachable, and you are not required to know or have skills in any other programming language to learn it.
Module 01 - Python Environment Setup and Essentials
1.1 Introduction to Python Language
1.2 Features and the advantages of Python over other programming languages
1.3 Python installation – Windows, Mac and Linux distribution for Anaconda Python
1.4 Deploying Python IDE
1.5 Basic Python commands, data types, variables, keywords and more
Module 02 - Python language Basic Constructs
2.1 Built-in data types in Python
2.2 Learn classes, modules, Str(String), Ellipsis Object, Null Object, Ellipsis, Debug
2.3 Basic operators, comparison, arithmetic, slicing and slice operator, logical, bitwise
2.4 Loop and control statements while, for, if, break, else, continue.
Module 03 - OOP concepts in Python
3.1 How to write OOP concepts program in Python
3.2 Connecting to a database
3.3 Classes and objects in Python
3.4 OOPs paradigm, important concepts in OOP like polymorphism, inheritance, encapsulation
3.5 Python functions, return types and parameters
3.6 Lambda expressions
Module 04 - Database Connection
4.1 Understanding the database, need for database
4.2 Installing MySQL on Windows
4.3 Understanding database connections using Python
Module 05 - NumPy for Mathematical Computing
5.1 Introduction to arrays and matrices
5.2 Broadcasting of array math, indexing of array
5.3 Standard deviation, conditional probability, correlation and covariance.
Module 06 - SciPy for Scientific Computing
6.1 Introduction to SciPy
6.2 Functions building on top of NumPy, cluster, linalg, signal, optimize, integrate, subpackages, and SciPy with Bayes’ Theorem
Module 07 - Matplotlib for data visualization
7.1 How to plot graphs and charts with Python?
7.2 Various aspects of line, scatter, bar, histogram, 3D, the API of Matplotlib, and subplots
Module 08 - Pandas for Data Analysis and Machine Learning
8.1 Introduction to Python dataframes
8.2 Importing data from JSON, CSV, Excel, SQL database, NumPy array to dataframe
8.3 Various data operations like selecting, filtering, sorting, viewing, joining, combining
Module 09 - Exception Handling
9.1 Introduction to Exception Handling
9.2 Scenarios in Exception Handling with its execution
9.3 Arithmetic exception
9.4 RAISE of Exception
9.5 What is Random List, running a Random list on Jupyter Notebook
9.6 Value Error in Exception Handling.
Module 10 - Multi-Threading and Race Condition
10.1 Introduction to Thread, the need of threads
10.2 What are thread functions?
10.3 Performing various operations on thread like joining a thread, starting a thread, and enumeration in a thread
10.4 Creating a Multithread, finishing the multithreads.
10.5 Understanding race condition, lock, and synchronization
Module 11 - Packages and Functions
11.1 Introduction to modules in Python, the need for modules
11.2 How to import modules in Python
11.3 Locating a module, namespace, and scoping
11.4 Arithmetic operations on Modules using a function
11.5 Introduction to the search path, global and local functions, filter functions
11.6 Python packages, import in packages, various ways of accessing the packages
11.7 Decorators, pointer assignments, and Xldr
Module 12 - Web Scraping with Python
12.1 Introduction to web scraping in Python
12.2 Installing beautiful soup
12.3 Installing Python parser lxml
12.4 Various web scraping libraries, beautiful soup, scrapy Python packages
12.5 Creating soup object with input HTML
12.6 Searching of tree, full or partial parsing, output print
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10+ Skills Covered
Python Basic Constructs
Exception Handling
Matplotlib
OOPS in Python
Multi-Threading
Python for Apache Spark
Pandas NumPy & SciPy
Web Scraping
Packages & Functions
Database Connections
Python Projects
Performing Analysis on Customer Churn Dataset
As an important part of the project, the learners will be required to analyze employment reliability in the telecom industry and work on real-time analysis of data with multiple labels and data visualization for reliability factors.
Analyzing the Naming Pattern Using Python
This real-life-based project has been included in the training to allow the learners to work with the United States Social Security Administration (SSA), which has made data available on the frequency of baby names from 1880 to 2016.
Python Web Scraping for
Data Science
The project gives practical exposure to the applications of this programming language in web scraping. Also get a chance to work on various web scraping libraries, such as beautiful soup, navigable string, parser, searching tree deployment, and more.
Salary Trends
Training Options
Instructor-Led Learning
Skills assessment & benchmarking
Structured, face-to-face interaction in a physical location.
Direct, in-person communication and real-time feedback.
Guaranteed job interviews through dedicated placement cell
₹30,000
Live Online Training
Skills assessment & benchmarking
Flexible, self-paced learning from anywhere with internet access.
Virtual communication through video calls, chat, and forums.
Guaranteed job interviews through dedicated placement cell
₹30,000
