PYTHON MASTERY
Specialization | 81 Course Series | 59 Mock Tests

The Python Mastery program offers a complete learning path from beginner to advanced levels. It empowers learners to build functional Python applications, analyze and interpret data, design interactive visualizations, develop web-based solutions, and implement AI and machine learning techniques. With hands-on projects, real-world case studies, and self-paced video lessons, participants gain both theoretical knowledge and practical expertise to become proficient Python developers.

Module 1: Python Fundamentals

Covers Python basics, object-oriented programming, and data structures, with hands-on projects like chatbots, expense managers, and cryptography applications.

Module 2: Python Game Development

Teaches game development with Python, including popular games like Snake and Flappy Bird, emphasizing coding and problem-solving skills.

Module 3: Python Hacking

Introduces ethical hacking and cybersecurity applications with practical GUI-based projects for real-world relevance.

Module 4: Python Scripting

Focuses on automation and workflow optimization through scripting, including file management, CSV handling, and task automation.

Module 5: Python GUI Programming

Covers GUI frameworks such as Tkinter and PyQt for building interactive desktop applications, including calculators and Windows apps.

Module 6: Data Visualization with Python

Teaches visualizing data with Matplotlib, with practical projects such as analyzing e-commerce datasets.

Module 7: Data Analysis with Python

Introduces data manipulation and analysis using NumPy and Pandas to extract actionable insights from real-world datasets.

Module 8: Seaborn Python

Covers statistical data visualization with Seaborn, enabling the creation of clear and attractive data plots.

Module 9: PySpark and Apache Spark

Provides hands-on training in big data processing and distributed computing using PySpark.

Module 10: Python Django

Teaches Django for building secure, scalable web applications with practical MySQL-based projects.

Module 11: Jupyter-IPython Notebook Training

Focuses on interactive notebooks for coding, visualizations, and machine learning projects.

Module 12: Python Pyramid

Covers lightweight web application development with Pyramid, including routing, templates, and building applications from scratch.

Module 13: Linux System Administration with Python

Teaches Linux administration automation, including file and user management, network configuration, and monitoring.

Module 14: Machine Learning with Python

Introduces ML algorithms, libraries like scikit-learn and TensorFlow, and hands-on projects for classification, regression, and neural networks.

Module 15: Data Science with Python

Covers data manipulation, analysis, visualization, and predictive modeling using Python libraries for real-world projects.

Module 16: Artificial Intelligence with Python

Teaches AI concepts and applications, including NLP, computer vision, and reinforcement learning, with Python tools.

Module 17: Kubernetes

Provides practical training in deploying, scaling, and managing containerized applications using Kubernetes.

Module 18: PyMongo

Covers integration with MongoDB for CRUD operations, indexing, aggregation, and handling GridFS through hands-on projects.

Module 19: Mock Tests and Quizzes

Assesses understanding with interactive quizzes and mock tests, offering detailed feedback and practice for professional readiness.

• Basic computer skills, including file management and navigating operating systems.
• Understanding of core programming concepts like variables, loops, and functions.
• Fundamental math knowledge, including arithmetic, algebra, and statistics.
• Familiarity with a text editor or IDE (e.g., VSCode, PyCharm, Sublime Text).
• Stable internet access for course materials, projects, and online resources.
• Curiosity and a strong eagerness to learn for maximum engagement and skill mastery.

• This course is ideal for individuals aiming to start a career in data science, analytics, and software developers or IT professionals seeking to broaden their Python expertise.
• It also benefits business analysts, students, and academics seeking proficiency in data analysis, visualization, and machine learning applications.
• Anyone interested in data analytics, scripting, automation, or web development can gain practical Python expertise to enhance career opportunities.