Inhalt: In 1997, an IBM computer named Deep Blue beat Gerry Kasparov, a world chess champion, after a six-game match. While AI technology has grown in exciting, and often revolutionary, ways since Deep Blue's victory at the chessboard in the late 90s, many of the techniques it implemented are still relevant today. In this course, explore some of these techniques as you learn how to leverage key AI algorithms to create two-player, turn-based games that are challenging enough to keep players guessing. Instructor Eduardo Corpeņo covers using the minimax algorithm for decision-making, the iterative deepening algorithm for making the best possible decision by a deadline, and alpha-beta pruning to improve the running time, among other clever approaches. Plus, he gives you a chance to try out these techniques yourself as he steps through the development of a cat trap game using Python. Umfang: 02:05:47.00
Inhalt: Learn to write embedded software in C and deliver applications that are small, efficient, and fast. In this course, instructor Eduardo Corpeņo explains how C programming and the Internet of Things combine in embedded applications-software that permanently resides on a device. He reviews the challenges involved in this type of programming, ranging from memory, storage, and power limitations to hardware awareness. He explains how different data types can affect the performance of your app and reviews bit manipulation-an area where C shines. Eduardo shows how to manipulate bit-level data using bit masking and bit fields, demonstrating the strengths of both techniques with an Arduino controller. Then learn how to use the volatile and const variables to enforce data correctness and read-only access, and explore alternatives to traditional functions, which may take too long to run, and floating-point math, which consumes CPU. Umfang: 01:43:54.00
Inhalt: Get up to speed with the C standard library, the standardized library of functions available for the C programming language. This course covers over 60 of the most useful and popular functions, as grouped in the header files stdio.h, stdlib.h, stdint.h, string.h, and math.h. Instructor Eduardo Corpeņo starts by reviewing the library's organization and familiarizing you with the header files and syntax. Then he shows how to accomplish a variety of tasks with the library: processing input and output, managing application memory, generating random numbers, sorting and searching for data, manipulating text strings, and performing math. Each chapter includes numerous examples that show the functions in practice, along with programming challenges that allow you to test your new knowledge and skills. Umfang: 02:02:36.00
Inhalt: The C++ Standard Template Library (STL) is a set of classes that implement many popular and commonly used algorithms and data structures. These features help you create more efficient, performant, and reusable code. Programmer Eduardo Corpeņo reviews the most popular elements of the C++ STL, so you can use these tools in your projects as soon as you finish the training. Learn how to use sequence containers such as vectors, lists, stacks, and queues for data storage, and use associative containers like sets and maps to implement associative arrays. Eduardo explains which elements perform best in which scenarios, and shows how to program with STL for maximum efficiency. A series of challenges at the end of each chapter allow you to test your knowledge along the way. Umfang: 02:23:02.00
Inhalt: Field-programmable gate arrays (FPGAs) straddle the boundary between hardware and software. They are customizable circuits that can be updated by customers or designers after manufacturing or deployment in the field. Rather than programming the chip with a series of instructions, FPGA developers create a logic structure from the gates inside the chip, establishing pathways for future data. A low-cost option for electronics prototyping and experimentation, FPGAs programming is a great entry point to digital systems design. This course provides an orientation to FPGAs, exploring the anatomy of the development boards and proprietary hardware description languages, the possibilities for implementation, and a comparison of the two major competing platforms, Xilinx and Intel. Instructor Eduardo Corpeņo also provides demos that show a real application working on both platforms. Umfang: 01:09:38.00
Inhalt: FPGA development requires a big switch from more typical programming processes. In order to get an FPGA-based embedded system up and running, developers must add a hardware description language to their repertoire. In this course, Eduardo Corpeņo helps you learn the fundamentals of one such language: the popular and concise Verilog. Eduardo begins with the basics; he explains what a hardware description language is and some similarities to traditional programming languages. He then covers the basic syntax of Verilog, as well as how to create test bench modules to run simulations, use variables with operators as an advantage of the behavioral level of abstraction, and more. Along the way, he provides demos and programming challenges that allow you to put your new skills to the test. Umfang: 02:02:45.00
Inhalt: Learn about the purpose, structure, and training process of neural networks to improve your machine learning skills. In this project-based course, instructor Eduardo Corpeņo teaches you how to create an intelligent system with a neural network from scratch in C++, as well as how to choose the right neural network architecture and training method for each problem. Eduardo starts by explaining the difference between a neural network and other programming tools. He goes over why this course uses C++ and how to add different types of neural networks to your toolbox. The inspiration for artificial neural networks is the brain, and Eduardo relates parts of a biological neuron to C++ elements, then shows how to use activation functions and perceptrons in building neuron models. Eduardo covers the steps you will need to build and train your network. He explains segment display recognition, then guides you through designing and training your own SDR neural network. Umfang: 01:46:32
Inhalt: Having a variety of great tools at your disposal isn't helpful if you don't know which one you really need, what each tool is useful for, and how they all work. In this course, take a deep dive into the inner workings of neural networks, so that you're able to work more effectively with machine learning tools. Instructor Eduardo Corpeņo helps you learn by example by providing a series of exercises in Python to help you to grasp what's going on inside. Discover how to relate parts of a biological neuron to Python elements, which allows you to make a model of the brain. Then, learn how to build and train a network, as well as create a neural network that recognizes numbers coming from a seven-segment display. Even though you'll probably work with neural networks from a software suite rather than by writing your own code, the knowledge you'll acquire in this course can help you choose the right neural network architecture and training method for each problem you face. Umfang: 01:45:13
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