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Python ML: Data Structures, Algorithms & More

10.00

Dive into the world of algorithms and data structures with this extensive Python course. Whether you’re a beginner or an experienced programmer, this course will equip you with the knowledge and skills needed to implement various algorithms and data structures efficiently using Python. From understanding the fundamentals of data structures to exploring advanced graph algorithms and machine learning techniques, each topic is covered in detail with practical examples and hands-on exercises. By the end of the course, you’ll have a solid understanding of how algorithms and data structures work and be able to apply them to solve real-world problems effectively.

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Description

Course Highlights:

Comprehensive coverage of data structures and algorithms in Python
Step-by-step tutorials for implementing graph algorithms and sorting algorithms
Introduction to machine learning concepts and techniques
Hands-on exercises and coding challenges for practical learning
Guidance on implementing regression, classification, and clustering algorithms
Exploration of tree-based algorithms and neural networks in machine learning
Practical tips and best practices for efficient algorithm implementation

Course Topics:

Installing LiClipse
Data Structures
Graph Algorithms
Other Problems
Basic Sorting Algorithms
Machine Learning – Introduction
Machine Learning – Regression
Machine Learning – Classification
Machine Learning – Tree Based Algorithms
Machine Learning – Clustering
Machine Learning – Neural Networks

What’s Included:

Engaging video tutorials and demonstrations
Interactive coding exercises and quizzes
Downloadable resources and supplementary materials
Accessible on multiple devices for flexible learning
Expert support and guidance from experienced instructors

Course Details:

Duration: Self-paced learning format
Skill Level: Intermediate to Advanced
Access: Lifetime access to course materials

Skills You’ll Gain:

Proficiency in implementing algorithms and data structures in Python
Understanding of graph algorithms and sorting techniques
Application of machine learning algorithms for regression, classification, and clustering
Implementation of tree-based algorithms and neural networks in Python

Requirements:

Basic knowledge of Python programming
Familiarity with fundamental programming concepts
Access to a computer with Python installed (installation instructions provided)

Who Should Take This Course:

Python developers interested in mastering algorithms and data structures
Computer science students seeking to deepen their understanding of algorithms
Data scientists and machine learning enthusiasts looking to enhance their Python skills
Professionals aiming to improve their problem-solving abilities with Python algorithms

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