Get your team access to Udemy's top 2,500 courses anytime, anywhere. If you have started using Python, by now you must have come to know the simplicity of the language. This course is designed to help you get more comfortable with programming in Python. It covers completely, the concept of linked list using Python as the primary language. You need to be equipped with the basics of Python such as variables, lists, dictionary and so on.

It addresses all manufacturing organizations, from OEMs through their supply chains, to small independent producers. It is mostly focused on, but not limited to, creating mechanical parts. It is intricately linked with the Sketcher Workbench.

It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or make business forecasting related decisions. Learning multiple regression analysis is indispensable for business analysis, financial analysis or data science applications in areas such as consumer analytics, finance, banking, health care, science, e-commerce and social media. It is also essential for academic careers in data science, applied statistics, economics, econometrics or quantitative finance. And it is necessary for any business forecasting related decision. But as learning curve can become steep as complexity grows, this course helps by leading you through step by step real world practical examples for greater effectiveness.

This video course is a practical guide for developers who want to get started with building computer vision applications using Python 3. The video is divided into six sections: Throughout this video course, three image processing libraries: Pillow, Scikit-Image, and OpenCV are used to implement different computer vision algorithms. The course will help you build Computer Vision applications that are capable of working in real-world scenarios effectively. Some of the applications that we look at in the course are Optical Character Recognition, Object Tracking and building a Computer Vision as a Service platform that works over the internet. Saurabh Kapur is a computer science student at Indraprastha Institute of Information Technology, Delhi. His interests are in computer vision, numerical analysis, and algorithm design.

In this Python Beyond the Basics - Object-Oriented Programming training course, expert author David Blaikie will teach you how to design Python classes, and how to implement object-oriented programming concepts in Python. This course is designed for users that already have a basic working knowledge of Python. You will start by learning about classes, including defining a class, class attributes, and working with class and instance data. From there, David will teach you about inheritance and polymorphism. This video tutorial also covers advanced features, such as implementing core syntax, subclassing built-ins, and new style classes.

Both represent the same principle, but for our purposes it's easier to explain using the geometric definition. In geometry slope represents the steepness of a line. It answers the question: how much does or change given a specific change in? But what if I asked you, instead of the slope between two points, what is the slope at a single point on the line? In this case there isn't any obvious "rise over run" to calculate.

Python features numerous numerical and mathematical toolkits such as: Numpy, Scipy, Scikit learn and SciKit, all used for data analysis and machine learning. With the aid of all of these, Python has become the language of choice for data scientists for data analysis, visualization, and machine learning. This video aims to teach Python developers how to perform data analysis with the language by taking advantage of the core data science libraries in the Python ecosystem. The learning objective for viewers is to understand how to locate, manipulate, and analyse data with Python, with the ability to analyse large and small sets of data using libraries such as Numpy, pandas, IPython and SciPy. This is a two part series.

Systems administration is the field of IT that's responsible for maintaining reliable computers systems in a multi-user environment. In this course, you'll learn about the infrastructure services that keep all organizations, big and small, up and running. You'll learn how to manage and configure servers, how to use industry tools to manage computers, user information, and user productivity. Finally, you'll learn how to recover your organization's IT infrastructure in the event of a disaster. By the end of this course you'll be able to: - utilize best practices for choosing hardware, vendors, and services for your organization.

This course is about data structures and algorithms. We are going to implement the problems in Python, but I try to do it as generic as possible: so the core of the algorithms can be used in C or Java. I highly recommend typing out these data structures and algorithms several times on your own in order to get a good grasp of it. In the first part of the course we are going to learn about basic data structures such as linked lists, stacks, queues, binary search trees, heaps and some advanced ones such as AVL trees and red-black trees.. The second part will be about graph algorithms such as spanning trees, shortest path algorithms and graph traversing.

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