Name: Python Bootcamp
Availability: InStock

What You'll Learn

Gain a thorough understanding of Python syntax, script writing, and core concepts such as variables, data types, and string operations
Master the use of conditional statements and loops in Python to automate and optimize data processing tasks
Learn to design reusable Python functions to perform repetitive tasks efficiently, including recursion and lambda functions
Understand how to use NumPy arrays for complex mathematical computations and effectively handle large datasets with high performance
Master the use of Pandas for data manipulation and analysis; learn how to explore, clean, and transform data into a suitable format
Develop the ability to create insightful visual representations of data using Matplotlib and Seaborn libraries of Python
Gain hands-on experience with Scikit-Learn, applying supervised and unsupervised learning algorithms to solve real-world machine learning problems
Understand the fundamentals of Deep Learning and neural networks, forming the foundation to work with TensorFlow and PyTorch frameworks
Build and evaluate deep learning models in PyTorch, including projects such as Fashion MNIST classification and cancer prediction

Requirements

No prior experience in Python or data analysis is required; just basic computer skills and access to a computer with an internet connection are necessary to start this course.

Complete beginners who want to learn Python programming step by step, starting from the basics and moving towards advanced applications.
Aspiring data scientists and analysts who want a structured, hands-on pathway to mastering Python libraries like NumPy, Pandas, Matplotlib, Seaborn, and Scikit-Learn.
Software developers, engineers, and IT professionals looking to expand their skill set into data analysis, machine learning, and deep learning.
Students and academic researchers who want to apply Python programming to analyze datasets, visualize results, and gain actionable insights for projects and publications.
Professionals working with business data, marketing analytics, or finance who want to automate data processing and generate meaningful insights efficiently.
Enthusiasts interested in deep learning, and neural networks who want practical exposure to frameworks like TensorFlow and PyTorch through real-world projects.

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