PYTHON MASTERY
Specialization | 81 Course Series | 59 Mock Tests
This Python Training Certification includes 81 courses with 363 hours of video tutorials and One year access. You will also get verifiable certificates when you complete each of the courses. This Python course has almost everything in Python - Programming, Game Development, Hacking, Data Science & Machine Learning, Ai - Everything included!
Offer ends in:
What you'll get
- 363 Hours
- 81 Courses
- Course Completion Certificates
- One year access
- Self-paced Courses
- Technical Support
- Mobile App Access
- Case Studies
Synopsis
- Courses: You get access to both the 81 courses and projects. You do not need to purchase each course separately.
- Hours: 363 Video Hours
- Core Coverage: Python Fundamentals, Linux System Administration with Python, Cryptography, Django Unchained with Python, Python GUI Programming using Tkinter, Rest API with Flask and Python, Python Pyramid Jupyter-IPython Notebook, Violent Python.
- Course Validity: One year access
- Eligibility: Anyone serious about Python.
- Pre-Requisites: Knowledge of Basics in Any Programming Language would be useful
- What do you get? Certificate of Completion for each of the courses
- Certification Type: Course Completion Certificates
- Verifiable Certificates? Yes, you get verifiable certificates for each course with a unique link. These links can be included in your resume/Linkedin profile to showcase your enhanced skills
- Type of Training: Video Course – Self-Paced Learning
Content
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MODULE 1: PYTHON DEVELOPER
Courses No. of Hours Certificates Details Python for Beginners: 2024 3h 28m ✔ Python Intermediate Training: 2024 2h 9m ✔ Python Advanced Training: 2024 2h 17m ✔ Python Case Study - Create Chatbot 58m ✔ Python Case Study - Expense Manager App 3h 19m ✔ Python Case Study - Instant Markup 3h 28m ✔ Python Case Study - Cryptography 5h 16m ✔ Python Case Study - Sentiment Analysis 57m ✔ Test - Python Developer in 2022 Test - Python Developer 2022 Major 1 Test - Python Developer 2022 Major 2 -
MODULE 2: PYTHON GAME DEVELOPER
Courses No. of Hours Certificates Details Python Game Development - Beginners 1h 55m ✔ Python Game Development - Intermediate 2h 9m ✔ Python Game Development - Advanced 2h 14m ✔ Python Game Development Case Study - Snake Game 1h 43m ✔ Python Game Development Case Study - Flippy Flip Game 2h 18m ✔ Test - Python Game Developer Minor Test 1 Test - Python Game Developer Minor Test 2 Test - Python Game Developer Major Test -
MODULE 3: PYTHON ETHICAL HACKING
Courses No. of Hours Certificates Details Python Hacking - Beginners 5h 39m ✔ Python Hacking Course - Intermediate Level 4h 16m ✔ Python Hacking - Advanced 5h 09m ✔ Python Hacking Case Study - GUI App for Amusement Park 56m ✔ Test - Python Ethical Hacking Minor Test 1 Test - Python Ethical Hacking Minor Test 2 Test - Python Ethical Hacking Major Test -
MODULE 4: PYTHON SCRIPTING
Courses No. of Hours Certificates Details Python Scripting Training 2h 12m ✔ Python Scripting Case Study - To-do List Application 1h 46m ✔ Python Scripting Case Study 48m ✔ Python Scripting Case Study - Creating a Console Application 46m ✔ Test - Python Scripting Minor Test 1 Test - Python Scripting Minor Test 2 Test - Python Scripting Major Test -
MODULE 5: PYTHON GUI
Courses No. of Hours Certificates Details Python GUI Training 3h 13m ✔ Python GUI Case Study - Creating a Windows Application 2h 14m ✔ Python GUI Case Study - Creating a Calculator 1h 42m ✔ Python GUI Programming using Tkinter and Python 4h 35m ✔ Test - Python GUI Minor Test 1 Test - Python GUI Minor Test 2 Test - Python GUI Major Test -
MODULE 6: MATPLOTLIB
Courses No. of Hours Certificates Details Matplotlib for Python Data Visualization - Beginners 4h 12m ✔ Matplotlib for Python Data Visualization - Intermediate 2h 53m ✔ Matplotlib for Python Data Visualization - Advanced 6h 37m ✔ Matplotlib Case Study - E-commerce Data Analysis 2h 03m ✔ Test - Matplotlib Mini Test 1 Test - Matplotlib Mini Test 2 Test - Matplotlib Mock Test -
MODULE 7: NUMPY & PANDAS
Courses No. of Hours Certificates Details NumPy and Pandas Python 4h 8m ✔ Analyzing the Quality of White Wines using NumPy Python 1h 22m ✔ Pandas Python Case Study - Data Management for Retail Dataset 3h 22m ✔ Data Analysis with Pandas and Python 59m ✔ Pandas with Python Tutorial 5h 51m ✔ Test - Numpy and Pandas Mini Test 1 Test - Numpy and Pandas Mini Test 2 Test - Numpy & Pandas Mock Test -
MODULE 8: SEABORN PYTHON PLOTTING
Courses No. of Hours Certificates Details Seaborn Python - Beginners 2h 28m ✔ Seaborn Python - Intermediate 1h 18m ✔ Seaborn Python - Advanced 1h 56m ✔ Case Studies on Seaborn Python Basics 1h 51m ✔ Seaborn Python Case Study - Data Visualization using Seaborn on Census Dataset 2h 9m ✔ Test - Python Plotting with Seaborn Minor Test 1 Test - Python Plotting with Seaborn Minor Test 2 Test - Python Plotting with Seaborn Major Test -
MODULE 9: PYSPARK
Courses No. of Hours Certificates Details PySpark Python - Beginners 2h 16m ✔ PySpark Python - Intermediate 2h 02m ✔ PySpark Python - Advanced 1h 18m ✔ Apache Spark - Beginners 1h 4m ✔ Apache Spark - Advanced 5h 49m ✔ Project on Apache Spark: Building an ETL Framework 2h 1m ✔ Test - PySpark Developer Mini Test 1 Test - PySpark Developer Mini Test 2 Test - PySpark Developer Mock Test -
MODULE 10: PYTHON DJANGO
Courses No. of Hours Certificates Details Python Django 8h 26m ✔ Python Django MySQL Case Study - Creating a Blog 48m ✔ Test - Python Django Mini Test 1 Test - Python Django Mini Test 2 Test - Python Django Mock Test -
MODULE 11: JUPYTER-IPYTHON NOTEBOOK
Courses No. of Hours Certificates Details Jupyter-IPython Notebook Training - Beginners 6h 05m ✔ Jupyter-IPython Notebook Training - Advanced 7h 5m ✔ Test - Jupyter-IPython Notebook Training Minor 1 Test - Jupyter-IPython Notebook Training Minor 2 Test - Jupyter-IPython Notebook Training Major -
MODULE 12: PYTHON PYRAMID
Courses No. of Hours Certificates Details Python Pyramid - Beginners 6h 04m ✔ Python Pyramid - Advanced 6h 02m ✔ Test - Python Pyramid Minor Test 1 Test - Python Pyramid Minor Test 2 Test - Python Pyramid Major Test -
MODULE 13: LINUX SYSTEM ADMINISTRATION WITH PYTHON
Courses No. of Hours Certificates Details Linux System Administration with Python 13h 12m ✔ Test - Linux System Administration With Python Mini Test 1 Test - Linux System Administration With Python Mini Test 2 Test - Linux System Administration with Python Mock Test -
MODULE 14: MACHINE LEARNING WITH PYTHON
Courses No. of Hours Certificates Details Machine Learning with Python 2024 5h 17m ✔ Machine Learning using Python 3h 26m ✔ Machine Learning with Python Case Study - Covid19 Mask Detector 2h 05m ✔ Deep Learning: Automatic Image Captioning for Social Media with Tensorflow 2h 23m ✔ Develop a Movie Recommendation Engine 51m ✔ Machine Learning Python Case Study - Diabetes Prediction 1h 02m ✔ Predictive Analytics and Modeling with Python 8h 26m ✔ AI Machine Learning in Python 8h 37m ✔ Test - Machine Learning with Python Minor Test 1 Test - Machine Learning with Python Minor Test 2 Test - Machine Learning with Python Major Test -
MODULE 15: DATA SCIENCE WITH PYTHON
Courses No. of Hours Certificates Details Data Science with Python 4h 14m ✔ Statistics Essentials with Python 3h 23m ✔ Advanced Python for Data analysis 6h 29m ✔ Logistic Regression & Supervised Machine Learning in Python 2h 6m ✔ Sales Forecasting using Time Series Analysis in Python 2h 13m ✔ Linear Regression & Supervised Learning in Python 2h 28m ✔ Test - Data Science with Python Test Series Test - Data Science with Python Major 1 Test - Data Science with Python Major 2 -
MODULE 16: Ai ARTIFICIAL INTELLIGENCE WITH PYTHON
Courses No. of Hours Certificates Details AI Artificial Intelligence & Predictive Analysis with Python 6h 15m ✔ Artificial Intelligence with Python - Beginner Level 2h 51m ✔ Artificial Intelligence with Python - Intermediate Level 4h 34m ✔ Artificial Intelligence and Machine Learning Training Course 12h 13m ✔ Face Detection Using OpenCV and Python 1h 52m ✔ Video Analytics using OpenCV and Python Shells 2h 13m ✔ Python Case Study - Sentiment Analysis 57m ✔ Test - AI Artificial Intelligence with Python Minor Test 1 Test - AI Artificial Intelligence with Python Minor Test 2 Test - AI Artificial Intelligence with Python Major Test -
MODULE 17: KUBERNETES
Courses No. of Hours Certificates Details Kubernetes Training 3h 3m ✔ Kubernetes Case Study - Hosting a Web Application as a Container 3h 38m ✔ Kubernetes Case Study - Deploying a Custom Docker Image 1h 22m ✔ Kubernetes - Beginners to Pro 2h 42m ✔ Test - Kubernetes Mini Test 1 Test - Kubernetes Mini Test 2 Test - Kubernetes Mock Test -
MODULE 18: PYMONGO
Courses No. of Hours Certificates Details PyMongo - Beginners 2h 33m ✔ PyMongo - Advanced 2h 08m ✔ PyMongo Case Study - Restaurant Management System 2h 26m ✔ PyMongo Case Study - Aggregating Customer Data of a Bank 2h 31m ✔ Test - PyMongo Mini Test 1 Test - PyMongo Mini Test 2 Test - PyMongo Mock Test -
MODULE 19: Mock Tests & Quizzes
Courses No. of Hours Certificates Details Test - Machine Learning Assessment Test - ML Assessment Exam Test - Mock Exam Machine Learning Test - Complete Machine Learning Exam Test - Machine Learning Ultimate Exam
Description
Course Introduction: Welcome to the comprehensive Python Mastery course! This course is meticulously designed to provide a thorough understanding of Python programming language from beginner to advanced levels. Whether you're a novice looking to start your journey in programming or an experienced developer aiming to enhance your skills, this course offers something for everyone. With a wide range of topics covering Python fundamentals, advanced techniques, practical projects, and real-world case studies, participants will gain the knowledge and hands-on experience needed to become proficient Python developers. Throughout the course, you'll learn essential Python concepts, such as data manipulation, statistical analysis, machine learning, web development, data visualization, and much more. Join us on this exciting learning journey and unlock the full potential of Python programming!
Module 1: Python Fundamentals
This module serves as a comprehensive introduction to Python programming, catering to beginners, intermediate learners, and those seeking advanced proficiency. Starting with fundamental concepts and syntax, it gradually progresses to cover more advanced topics such as object-oriented programming and data structures. Practical case studies offer hands-on experience, including building a chatbot, an expense manager app, and exploring cryptography applications.
Module 2: Python Game Development
Designed for aspiring game developers, this module covers Python game development from beginner to advanced levels. Learners will acquire essential skills and techniques for creating various games using Python, including popular titles like Snake and Flappy Bird. Through hands-on case studies, participants gain practical experience in game development, honing their coding and problem-solving abilities.
Module 3: Python Hacking
In this module, learners delve into the realm of ethical hacking and cybersecurity using Python. The curriculum spans from introductory concepts for beginners to advanced techniques for seasoned practitioners. Practical case studies provide insights into building graphical user interface (GUI) applications for tasks such as Amazon S3 bucket management, offering real-world relevance to the theoretical knowledge acquired.
Module 4: Python Scripting
Focusing on automation and scripting, this module equips learners with the skills needed to streamline workflows and perform routine tasks using Python. Participants will learn scripting fundamentals and explore practical applications through case studies, including creating to-do lists and managing CSV files. By mastering Python scripting, learners enhance their efficiency and productivity in various domains.
Module 5: Python GUI Programming
Introducing graphical user interface (GUI) development using Python, this module covers essential GUI frameworks and libraries such as Tkinter and PyQt. Through a combination of theoretical instruction and hands-on projects, learners acquire the skills to design and implement GUI applications. Practical case studies, including creating Windows applications and a calculator, reinforce learning outcomes.
Module 6: Data Visualization with Python
This module focuses on data visualization using Matplotlib, a powerful Python library for creating static, interactive, and animated visualizations. Learners will explore different visualization techniques and gain proficiency in analyzing and presenting data effectively. Through case studies, such as analyzing e-commerce data, participants develop a deeper understanding of data visualization principles and applications.
Module 7: Data Analysis with Python
Covering essential libraries like NumPy and Pandas, this module enables learners to perform data manipulation, analysis, and management tasks efficiently using Python. Practical case studies provide opportunities to apply data analysis techniques to real-world scenarios, enhancing learners' ability to derive meaningful insights from data.
Module 8: Seaborn Python
Seaborn is a statistical data visualization library in Python that facilitates the creation of informative and attractive visualizations. This module covers Seaborn from beginners to advanced levels, exploring its capabilities in data visualization and analysis. Learners will engage in case studies to deepen their understanding and proficiency in using Seaborn for data visualization.
Module 9: PySpark and Apache Spark
Apache Spark is a powerful open-source distributed computing system that provides an efficient platform for big data processing. This module introduces learners to PySpark, the Python API for Spark, and covers its usage from beginners to advanced levels. Through hands-on projects and case studies, participants gain practical experience in leveraging PySpark for data processing and analysis tasks.
Module 10: Python Django
Django is a high-level Python web framework that enables rapid development of secure and scalable web applications. This module offers comprehensive training on Django, covering its core concepts and features. Learners will explore practical case studies, including building MySQL-based web applications, to reinforce their understanding and proficiency in Django development.
Module 11: Jupyter-IPython Notebook Training
Jupyter Notebook, formerly known as IPython Notebook, is a popular open-source web application that allows users to create and share documents containing live code, equations, visualizations, and narrative text. This module provides training on Jupyter Notebook from beginner to advanced levels, covering its various features and functionalities. Participants will learn to create interactive notebooks, perform data analysis, and develop machine learning models using Jupyter Notebooks. Practical exercises and case studies enhance hands-on learning and reinforce key concepts.
Module 12: Python Pyramid
Python Pyramid is a lightweight and flexible web framework for building web applications. This module offers comprehensive training on Python Pyramid, covering its architecture, routing, views, templates, and other essential components. Participants will gain practical experience through hands-on projects and case studies, including building web applications from scratch. By the end of this module, learners will be proficient in developing robust and scalable web applications using Python Pyramid.
Module 13: Linux System Administration with Python
Linux System Administration with Python is a specialized module that focuses on automating administrative tasks and system management using Python scripting on Linux-based systems. Participants will learn how to leverage Python libraries and tools to automate various system administration tasks, such as file management, user management, network configuration, and monitoring. Practical exercises and case studies provide hands-on experience, enabling participants to develop practical skills in Linux system administration and Python scripting.
Module 14: Machine Learning with Python
Machine learning is a rapidly evolving field that leverages algorithms and statistical models to enable computers to perform tasks without explicit programming instructions. This module offers comprehensive training on machine learning with Python, covering various machine learning algorithms, techniques, and libraries such as scikit-learn, TensorFlow, and Keras. Participants will learn to build and evaluate machine learning models for tasks such as classification, regression, clustering, and neural networks. Practical case studies and projects provide hands-on experience, allowing participants to apply machine learning techniques to real-world problems and datasets.
Module 15: Data Science with Python
Data science is an interdisciplinary field that combines domain knowledge, programming skills, and statistical techniques to extract insights and knowledge from data. This module provides comprehensive training on data science with Python, covering data manipulation, visualization, statistical analysis, machine learning, and predictive modeling. Participants will learn to use Python libraries such as NumPy, Pandas, Matplotlib, and scikit-learn to analyze and visualize data, build predictive models, and derive actionable insights. Practical case studies and projects provide hands-on experience, enabling participants to apply data science techniques to real-world datasets and problems.
Module 16: Artificial Intelligence with Python
Artificial intelligence (AI) is a rapidly growing field that aims to create intelligent machines capable of performing tasks that typically require human intelligence. This module offers comprehensive training on artificial intelligence with Python, covering various AI concepts, techniques, and applications. Participants will learn to implement AI algorithms and models for tasks such as natural language processing, computer vision, and reinforcement learning using Python libraries such as TensorFlow, Keras, and OpenCV. Practical case studies and projects provide hands-on experience, allowing participants to build and deploy AI applications using Python.
Module 17: Kubernetes
Kubernetes is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. This module provides comprehensive training on Kubernetes, covering its architecture, components, features, and best practices for deploying and managing applications on Kubernetes clusters. Participants will learn to deploy, scale, and manage containerized applications using Kubernetes through practical exercises and case studies. By the end of this module, learners will be proficient in using Kubernetes to deploy and manage containerized applications in production environments.
Module 18: PyMongo
PyMongo is a Python library for interacting with MongoDB, a popular NoSQL database. This module offers comprehensive training on PyMongo, covering its usage for performing CRUD (Create, Read, Update, Delete) operations, indexing, aggregation, and working with GridFS. Participants will learn to integrate Python applications with MongoDB databases and perform various data manipulation tasks using PyMongo. Practical case studies and projects provide hands-on experience, enabling participants to apply PyMongo techniques to real-world scenarios.
Module 19: Mock Tests and Quizzes
The Mock Tests and Quizzes module is designed to assess participants' understanding and proficiency in the topics covered throughout the course. This module includes a series of mock tests and quizzes that cover each module's key concepts, theories, techniques, and practical applications. Participants will have the opportunity to test their knowledge, identify areas for improvement, and reinforce their learning through interactive quizzes and practice exams. The mock tests and quizzes are structured to simulate real-world scenarios and challenges, allowing participants to evaluate their readiness for certification exams or professional endeavors. Additionally, the module provides detailed feedback and explanations for each question, enabling participants to learn from their mistakes and enhance their understanding of the course material.
Sample Certificate
Requirements
- Basic Computer Skills: Participants should have a basic understanding of computer operations, such as file management, navigating the operating system, and using common software applications.
- Fundamental Programming Concepts: Familiarity with fundamental programming concepts like variables, data types, loops, conditional statements, and functions will be beneficial for grasping Python programming concepts more easily.
- Mathematics Knowledge: A basic understanding of mathematics, including arithmetic operations, algebraic expressions, and statistical concepts, will aid in comprehending data manipulation and analysis techniques covered in the course.
- Text Editor or IDE Familiarity: It's recommended to have prior experience with using a text editor or integrated development environment (IDE) for writing and executing code. Examples include VSCode, PyCharm, Sublime Text, or Atom.
- Internet Access: Access to the internet is essential for downloading course materials, accessing online resources, and completing assignments or projects. A stable internet connection is recommended for uninterrupted learning.
- Curiosity and Eagerness to Learn: Most importantly, participants should come with a curious mind and a strong desire to learn. Python programming offers vast opportunities, and a proactive attitude will enhance the learning experience and mastery of the language.
Target Audience
- Aspiring Data Scientists: Individuals looking to enter the field of data science and seeking a comprehensive understanding of Python programming and its applications in data analysis, machine learning, and artificial intelligence.
- Software Developers and Programmers: Professionals working in software development or programming roles who want to expand their skill set by learning Python for data manipulation, visualization, and scientific computing.
- Business Analysts: Business analysts seeking to enhance their analytical skills by learning Python for data analysis, statistical modeling, and generating insights from large datasets.
- Students and Academics: Students pursuing degrees in computer science, data science, statistics, or related fields who want to gain proficiency in Python programming for academic projects, research, or future career opportunities.
- Professionals in IT and Engineering: IT professionals and engineers interested in leveraging Python for tasks such as automation, scripting, web development, and system administration.
- Anyone Interested in Data Analytics and Visualization: Individuals with a keen interest in data analytics, visualization, and storytelling who want to learn how to use Python libraries like Pandas, Matplotlib, and Seaborn to analyze and visualize data effectively.
- Career Changers and Job Seekers: Individuals looking to transition into a career in data science, analytics, or related fields and seeking to acquire the necessary skills in Python programming and data analysis to secure job opportunities in these domains.
Course Ratings
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I found this course very helpful. The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills
JIYEON CHOI
Very Informative and Well Organized Course Contents. High Quality Videos. I will recommend this course to anyone I know who interested to learn about Data Analytics.
JOSEPH WONG
I recently completed a data analytics course and found it to be an incredibly valuable learning experience. The course provided a comprehensive introduction to data analytics, covering everything from data collection and cleaning to advanced statistical analysis and data visualization. One thing I appreciated about the course was the hands-on approach to learning. Throughout the course, we worked with real datasets and used industry-standard tools such as Python, R, and Tableau to analyze and visualize the data. This gave me the practical skills and experience I needed to feel confident in my ability to work with data in a professional setting. The course instructors were knowledgeable and engaging, and they were always available to answer questions and provide feedback. The course also had a supportive and active online community, where I was able to connect with other learners and share my experiences and insights. Overall, I would highly recommend this data analytics course to an
Akram Ahmed
The Data Science Fundamentals online course that I recently completed. Overall, I found the course to be highly valuable and informative. The content was well-structured and provided a solid foundation for understanding key concepts in data science.
Priti Gajanan Patole