Python Data Structures ( Hands On Code Implementation)



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Are you looking forward to get well versed with Python that is designed to ground you up from zero to hero in the shortest time? Then this is the perfect course for you.

This course can be of utmost important to you as it guides you in many different ways such as learning basics of data structures, linked lists, and arrays along with coding tuples in Python followed by an example that shows how to program dicts and sets in Python. You will also be shown shown how to apply different algorithms such as Graph traversal, Shortest Path, Minimum Spanning Tree, Maximum Flow tree, and DAG topological sorting. It aslo demonstration on how to realize a hash table in Python.

By end of this Learning Path,  you’ll be well versed with Implementing Classic Data Structures and Algorithms Using Python along with building your own CV.

Contents and Overview

This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.

The first course, Learn Python in 3 Hours illustrates how u can be up-to-speed with Python in a short period of time, but your search has so far come up with disconnected, unrelated tutorials or guides.

Learn Python in 3 hours is a fast-paced, action-packed course that maximizes your time; it’s designed from the ground up to bring you from zero to hero in the shortest time. The course is based on many years of Python development experience in both large enterprises and nimble startups. In particular, the course’s hands-on and practical approach comes from the author’s experience in rapidly iterating and shipping products in a startup setting, where responsiveness and speed are key.

With Learn Python in 3 hours, you will be up-and-running with Python like you are with your other languages, proving your value and expertise to your team today, and building your CV and skill set for tomorrow.

The second course, Python Data Structures and Algorithms is about data structures and algorithms. We are going to implement problems in Python. You will start by learning the basics of data structures, linked lists, and arrays in Python. You will be shown how to code tuples in Python followed by an example that shows how to program dicts and sets in Python. You will learn about the use of pointers in Python. You will then explore linear data structures in Python such as stacks, queues, and hash tables. In these you will learn how to implement a stack and code queues and deques. There will also be a demonstration on how to realize a hash table in Python. Following this you will learn how to use tree/graph data structures including binary trees, heaps and priority queues in Python. You will program priority queues and red-black trees in Python with examples. Finally, you will be shown how to apply different algorithms such as Graph traversal, Shortest Path, Minimum Spanning Tree, Maximum Flow tree, and DAG topological sorting

Read more course:  Python MTA 98-381 Exam - Complete Preparation Course Tips (Updated)

This course teaches all these concepts in a very practical hands-on approach without burdening you with lots of theory. By the end of the course, you will have learned how to implement various data structures and algorithms in Python.

About the Authors:    

Rudy Lai is the founder of Quant Copy, a sales acceleration startup using AI to write sales emails to prospects. By taking in leads from your pipelines, Quant Copy researches them online and generates sales emails from that data. It also has a suite of email automation tools to schedule, send, and track email performance—key analytics that all feed back into how our AI generated content. Prior to founding Quant Copy, Rudy ran High Dimension.IO, a machine learning consultancy, where he experienced firsthand the frustrations of outbound sales and prospecting. As a founding partner, he helped startups and enterprises with High Dimension.IO’s Machine-Learning-as-a-Service, allowing them to scale up data expertise in the blink of an eye. In the first part of his career, Rudy spent 5+ years in quantitative trading at leading investment banks such as Morgan Stanley. This valuable experience allowed him to witness the power of data, but also the pitfalls of automation using data science and machine learning. Quantitative trading was also a great platform from which to learn a lot about reinforcement learning and supervised learning topics in a commercial setting. Rudy holds a Computer Science degree from Imperial College London, where he was part of the Dean’s List, and received awards such as the Deutsche Bank Artificial Intelligence prize.

Harish Garg, founder of BignumWorks Software LLP is a data scientist and a lead software developer with 17 years’ software Industry experience. BignumWorks Software LLP is an India based Software Consultancy that provides consultancy services in the area of software development and technical training. Harish has worked for McAfee\Intel for 11+ years. He is an expert in creating Data visualizations using R, Python, and Web-based visualization libraries.

Mithun Lakshmanaswamy, part of BignumWorks Software LLP, has been developing Applications in Python for more than nine years. He has written enterprise level distributed applications that are deployed on scores of servers and have the ability to support thousands of users simultaneously. Some of the applications he has developed are related to parsing millions of virus definitions, analyzing network packets from an enterprise setup, etc. He is also quite proficient in the teaching technical concepts and is quite involved with his current org’s training programmes. He has worked on multiple projects working with Python, AWS etc implementing the concepts of concurrent and distributed computing.

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